diff options
| author | Sergey Sharybin <sergey@blender.org> | 2021-03-05 16:42:30 +0300 |
|---|---|---|
| committer | Sergey Sharybin <sergey@blender.org> | 2021-03-05 17:05:08 +0300 |
| commit | 0dd9a4a576452007da9d3f02a03499e50a8ddfae (patch) | |
| tree | 3df82ff28a03613a60e5a44b97f40bfffbffaca6 /intern/libmv | |
| parent | e0442a955badbbf7ee6f280bb988054175802bc1 (diff) | |
Cleanup: Libmv, clang-format
Is based on Google style which was used in the Libmv project before,
but is now consistently applied for the sources of the library itself
and to C-API. With some time C-API will likely be removed, and it
makes it easier to make it follow Libmv style, hence the diversion
from Blender's style.
There are quite some exceptions (clang-format off) in the code around
Eigen matrix initialization. It is rather annoying, and there could be
some neat way to make initialization readable without such exception.
Could be some places where loss of readability in matrix initialization
got lost as the change is quite big. If this has happened it is easier
to address readability once actually working on the code.
This change allowed to spot some missing header guards, so that's nice.
Doing it in bundled version, as the upstream library needs to have some
of the recent development ported over from bundle to upstream.
There should be no functional changes.
Diffstat (limited to 'intern/libmv')
151 files changed, 4928 insertions, 4504 deletions
diff --git a/intern/libmv/.clang-format b/intern/libmv/.clang-format index 9d159247d51..fae0530c572 100644 --- a/intern/libmv/.clang-format +++ b/intern/libmv/.clang-format @@ -1,2 +1,34 @@ -DisableFormat: true -SortIncludes: false +BasedOnStyle: Google + +ColumnLimit: 80 + +Standard: Cpp11 + +# Indent nested preprocessor. +# #ifdef Foo +# # include <nested> +# #endif +IndentPPDirectives: AfterHash + +# For the cases when namespace is closing with a wrong comment +FixNamespaceComments: true + +AllowShortFunctionsOnASingleLine: InlineOnly +AllowShortBlocksOnASingleLine: false +AllowShortIfStatementsOnASingleLine: false +AllowShortLoopsOnASingleLine: false +AllowShortCaseLabelsOnASingleLine: true + +# No bin packing, every argument is on its own line. +BinPackArguments: false +BinPackParameters: false + +# Ensure pointer alignment. +# ObjectType* object; +PointerAlignment: Left +DerivePointerAlignment: false + +AlignEscapedNewlines: Right + +IncludeBlocks: Preserve +SortIncludes: true diff --git a/intern/libmv/intern/autotrack.cc b/intern/libmv/intern/autotrack.cc index 7000a422de8..b7110957b15 100644 --- a/intern/libmv/intern/autotrack.cc +++ b/intern/libmv/intern/autotrack.cc @@ -22,15 +22,15 @@ #include "intern/utildefines.h" #include "libmv/autotrack/autotrack.h" +using libmv::TrackRegionOptions; +using libmv::TrackRegionResult; using mv::AutoTrack; using mv::FrameAccessor; using mv::Marker; -using libmv::TrackRegionOptions; -using libmv::TrackRegionResult; -libmv_AutoTrack* libmv_autoTrackNew(libmv_FrameAccessor *frame_accessor) { - return (libmv_AutoTrack*) LIBMV_OBJECT_NEW(AutoTrack, - (FrameAccessor*) frame_accessor); +libmv_AutoTrack* libmv_autoTrackNew(libmv_FrameAccessor* frame_accessor) { + return (libmv_AutoTrack*)LIBMV_OBJECT_NEW(AutoTrack, + (FrameAccessor*)frame_accessor); } void libmv_autoTrackDestroy(libmv_AutoTrack* libmv_autotrack) { @@ -39,7 +39,7 @@ void libmv_autoTrackDestroy(libmv_AutoTrack* libmv_autotrack) { void libmv_autoTrackSetOptions(libmv_AutoTrack* libmv_autotrack, const libmv_AutoTrackOptions* options) { - AutoTrack *autotrack = ((AutoTrack*) libmv_autotrack); + AutoTrack* autotrack = ((AutoTrack*)libmv_autotrack); libmv_configureTrackRegionOptions(options->track_region, &autotrack->options.track_region); @@ -51,18 +51,15 @@ void libmv_autoTrackSetOptions(libmv_AutoTrack* libmv_autotrack, int libmv_autoTrackMarker(libmv_AutoTrack* libmv_autotrack, const libmv_TrackRegionOptions* libmv_options, - libmv_Marker *libmv_tracked_marker, + libmv_Marker* libmv_tracked_marker, libmv_TrackRegionResult* libmv_result) { - Marker tracked_marker; TrackRegionOptions options; TrackRegionResult result; libmv_apiMarkerToMarker(*libmv_tracked_marker, &tracked_marker); - libmv_configureTrackRegionOptions(*libmv_options, - &options); - bool ok = (((AutoTrack*) libmv_autotrack)->TrackMarker(&tracked_marker, - &result, - &options)); + libmv_configureTrackRegionOptions(*libmv_options, &options); + bool ok = (((AutoTrack*)libmv_autotrack) + ->TrackMarker(&tracked_marker, &result, &options)); libmv_markerToApiMarker(tracked_marker, libmv_tracked_marker); libmv_regionTrackergetResult(result, libmv_result); return ok && result.is_usable(); @@ -72,7 +69,7 @@ void libmv_autoTrackAddMarker(libmv_AutoTrack* libmv_autotrack, const libmv_Marker* libmv_marker) { Marker marker; libmv_apiMarkerToMarker(*libmv_marker, &marker); - ((AutoTrack*) libmv_autotrack)->AddMarker(marker); + ((AutoTrack*)libmv_autotrack)->AddMarker(marker); } void libmv_autoTrackSetMarkers(libmv_AutoTrack* libmv_autotrack, @@ -87,19 +84,17 @@ void libmv_autoTrackSetMarkers(libmv_AutoTrack* libmv_autotrack, for (size_t i = 0; i < num_markers; ++i) { libmv_apiMarkerToMarker(libmv_marker[i], &markers[i]); } - ((AutoTrack*) libmv_autotrack)->SetMarkers(&markers); + ((AutoTrack*)libmv_autotrack)->SetMarkers(&markers); } int libmv_autoTrackGetMarker(libmv_AutoTrack* libmv_autotrack, int clip, int frame, int track, - libmv_Marker *libmv_marker) { + libmv_Marker* libmv_marker) { Marker marker; - int ok = ((AutoTrack*) libmv_autotrack)->GetMarker(clip, - frame, - track, - &marker); + int ok = + ((AutoTrack*)libmv_autotrack)->GetMarker(clip, frame, track, &marker); if (ok) { libmv_markerToApiMarker(marker, libmv_marker); } diff --git a/intern/libmv/intern/autotrack.h b/intern/libmv/intern/autotrack.h index 6b49a6908e1..3887983814b 100644 --- a/intern/libmv/intern/autotrack.h +++ b/intern/libmv/intern/autotrack.h @@ -21,9 +21,9 @@ #define LIBMV_C_API_AUTOTRACK_H_ #include "intern/frame_accessor.h" -#include "intern/tracksN.h" -#include "intern/track_region.h" #include "intern/region.h" +#include "intern/track_region.h" +#include "intern/tracksN.h" #ifdef __cplusplus extern "C" { @@ -36,7 +36,7 @@ typedef struct libmv_AutoTrackOptions { libmv_Region search_region; } libmv_AutoTrackOptions; -libmv_AutoTrack* libmv_autoTrackNew(libmv_FrameAccessor *frame_accessor); +libmv_AutoTrack* libmv_autoTrackNew(libmv_FrameAccessor* frame_accessor); void libmv_autoTrackDestroy(libmv_AutoTrack* libmv_autotrack); @@ -45,7 +45,7 @@ void libmv_autoTrackSetOptions(libmv_AutoTrack* libmv_autotrack, int libmv_autoTrackMarker(libmv_AutoTrack* libmv_autotrack, const libmv_TrackRegionOptions* libmv_options, - libmv_Marker *libmv_tracker_marker, + libmv_Marker* libmv_tracker_marker, libmv_TrackRegionResult* libmv_result); void libmv_autoTrackAddMarker(libmv_AutoTrack* libmv_autotrack, @@ -59,7 +59,7 @@ int libmv_autoTrackGetMarker(libmv_AutoTrack* libmv_autotrack, int clip, int frame, int track, - libmv_Marker *libmv_marker); + libmv_Marker* libmv_marker); #ifdef __cplusplus } diff --git a/intern/libmv/intern/camera_intrinsics.cc b/intern/libmv/intern/camera_intrinsics.cc index 628637e12cc..243b26d9fb3 100644 --- a/intern/libmv/intern/camera_intrinsics.cc +++ b/intern/libmv/intern/camera_intrinsics.cc @@ -21,62 +21,56 @@ #include "intern/utildefines.h" #include "libmv/simple_pipeline/camera_intrinsics.h" +using libmv::BrownCameraIntrinsics; using libmv::CameraIntrinsics; using libmv::DivisionCameraIntrinsics; -using libmv::PolynomialCameraIntrinsics; using libmv::NukeCameraIntrinsics; -using libmv::BrownCameraIntrinsics; +using libmv::PolynomialCameraIntrinsics; -libmv_CameraIntrinsics *libmv_cameraIntrinsicsNew( +libmv_CameraIntrinsics* libmv_cameraIntrinsicsNew( const libmv_CameraIntrinsicsOptions* libmv_camera_intrinsics_options) { - CameraIntrinsics *camera_intrinsics = - libmv_cameraIntrinsicsCreateFromOptions(libmv_camera_intrinsics_options); - return (libmv_CameraIntrinsics *) camera_intrinsics; + CameraIntrinsics* camera_intrinsics = + libmv_cameraIntrinsicsCreateFromOptions(libmv_camera_intrinsics_options); + return (libmv_CameraIntrinsics*)camera_intrinsics; } -libmv_CameraIntrinsics *libmv_cameraIntrinsicsCopy( +libmv_CameraIntrinsics* libmv_cameraIntrinsicsCopy( const libmv_CameraIntrinsics* libmv_intrinsics) { - const CameraIntrinsics *orig_intrinsics = - (const CameraIntrinsics *) libmv_intrinsics; + const CameraIntrinsics* orig_intrinsics = + (const CameraIntrinsics*)libmv_intrinsics; - CameraIntrinsics *new_intrinsics = NULL; + CameraIntrinsics* new_intrinsics = NULL; switch (orig_intrinsics->GetDistortionModelType()) { - case libmv::DISTORTION_MODEL_POLYNOMIAL: - { - const PolynomialCameraIntrinsics *polynomial_intrinsics = + case libmv::DISTORTION_MODEL_POLYNOMIAL: { + const PolynomialCameraIntrinsics* polynomial_intrinsics = static_cast<const PolynomialCameraIntrinsics*>(orig_intrinsics); - new_intrinsics = LIBMV_OBJECT_NEW(PolynomialCameraIntrinsics, - *polynomial_intrinsics); - break; - } - case libmv::DISTORTION_MODEL_DIVISION: - { - const DivisionCameraIntrinsics *division_intrinsics = + new_intrinsics = + LIBMV_OBJECT_NEW(PolynomialCameraIntrinsics, *polynomial_intrinsics); + break; + } + case libmv::DISTORTION_MODEL_DIVISION: { + const DivisionCameraIntrinsics* division_intrinsics = static_cast<const DivisionCameraIntrinsics*>(orig_intrinsics); - new_intrinsics = LIBMV_OBJECT_NEW(DivisionCameraIntrinsics, - *division_intrinsics); - break; - } - case libmv::DISTORTION_MODEL_NUKE: - { - const NukeCameraIntrinsics *nuke_intrinsics = + new_intrinsics = + LIBMV_OBJECT_NEW(DivisionCameraIntrinsics, *division_intrinsics); + break; + } + case libmv::DISTORTION_MODEL_NUKE: { + const NukeCameraIntrinsics* nuke_intrinsics = static_cast<const NukeCameraIntrinsics*>(orig_intrinsics); - new_intrinsics = LIBMV_OBJECT_NEW(NukeCameraIntrinsics, - *nuke_intrinsics); - break; - } - case libmv::DISTORTION_MODEL_BROWN: - { - const BrownCameraIntrinsics *brown_intrinsics = + new_intrinsics = LIBMV_OBJECT_NEW(NukeCameraIntrinsics, *nuke_intrinsics); + break; + } + case libmv::DISTORTION_MODEL_BROWN: { + const BrownCameraIntrinsics* brown_intrinsics = static_cast<const BrownCameraIntrinsics*>(orig_intrinsics); - new_intrinsics = LIBMV_OBJECT_NEW(BrownCameraIntrinsics, - *brown_intrinsics); - break; - } - default: - assert(!"Unknown distortion model"); + new_intrinsics = + LIBMV_OBJECT_NEW(BrownCameraIntrinsics, *brown_intrinsics); + break; + } + default: assert(!"Unknown distortion model"); } - return (libmv_CameraIntrinsics *) new_intrinsics; + return (libmv_CameraIntrinsics*)new_intrinsics; } void libmv_cameraIntrinsicsDestroy(libmv_CameraIntrinsics* libmv_intrinsics) { @@ -86,7 +80,7 @@ void libmv_cameraIntrinsicsDestroy(libmv_CameraIntrinsics* libmv_intrinsics) { void libmv_cameraIntrinsicsUpdate( const libmv_CameraIntrinsicsOptions* libmv_camera_intrinsics_options, libmv_CameraIntrinsics* libmv_intrinsics) { - CameraIntrinsics *camera_intrinsics = (CameraIntrinsics *) libmv_intrinsics; + CameraIntrinsics* camera_intrinsics = (CameraIntrinsics*)libmv_intrinsics; double focal_length = libmv_camera_intrinsics_options->focal_length; double principal_x = libmv_camera_intrinsics_options->principal_point_x; @@ -115,191 +109,173 @@ void libmv_cameraIntrinsicsUpdate( } switch (libmv_camera_intrinsics_options->distortion_model) { - case LIBMV_DISTORTION_MODEL_POLYNOMIAL: - { - assert(camera_intrinsics->GetDistortionModelType() == - libmv::DISTORTION_MODEL_POLYNOMIAL); - - PolynomialCameraIntrinsics *polynomial_intrinsics = - (PolynomialCameraIntrinsics *) camera_intrinsics; - - double k1 = libmv_camera_intrinsics_options->polynomial_k1; - double k2 = libmv_camera_intrinsics_options->polynomial_k2; - double k3 = libmv_camera_intrinsics_options->polynomial_k3; - - if (polynomial_intrinsics->k1() != k1 || - polynomial_intrinsics->k2() != k2 || - polynomial_intrinsics->k3() != k3) { - polynomial_intrinsics->SetRadialDistortion(k1, k2, k3); - } - break; + case LIBMV_DISTORTION_MODEL_POLYNOMIAL: { + assert(camera_intrinsics->GetDistortionModelType() == + libmv::DISTORTION_MODEL_POLYNOMIAL); + + PolynomialCameraIntrinsics* polynomial_intrinsics = + (PolynomialCameraIntrinsics*)camera_intrinsics; + + double k1 = libmv_camera_intrinsics_options->polynomial_k1; + double k2 = libmv_camera_intrinsics_options->polynomial_k2; + double k3 = libmv_camera_intrinsics_options->polynomial_k3; + + if (polynomial_intrinsics->k1() != k1 || + polynomial_intrinsics->k2() != k2 || + polynomial_intrinsics->k3() != k3) { + polynomial_intrinsics->SetRadialDistortion(k1, k2, k3); } + break; + } - case LIBMV_DISTORTION_MODEL_DIVISION: - { - assert(camera_intrinsics->GetDistortionModelType() == - libmv::DISTORTION_MODEL_DIVISION); + case LIBMV_DISTORTION_MODEL_DIVISION: { + assert(camera_intrinsics->GetDistortionModelType() == + libmv::DISTORTION_MODEL_DIVISION); - DivisionCameraIntrinsics *division_intrinsics = - (DivisionCameraIntrinsics *) camera_intrinsics; + DivisionCameraIntrinsics* division_intrinsics = + (DivisionCameraIntrinsics*)camera_intrinsics; - double k1 = libmv_camera_intrinsics_options->division_k1; - double k2 = libmv_camera_intrinsics_options->division_k2; + double k1 = libmv_camera_intrinsics_options->division_k1; + double k2 = libmv_camera_intrinsics_options->division_k2; - if (division_intrinsics->k1() != k1 || - division_intrinsics->k2() != k2) { - division_intrinsics->SetDistortion(k1, k2); - } + if (division_intrinsics->k1() != k1 || division_intrinsics->k2() != k2) { + division_intrinsics->SetDistortion(k1, k2); + } - break; + break; + } + + case LIBMV_DISTORTION_MODEL_NUKE: { + assert(camera_intrinsics->GetDistortionModelType() == + libmv::DISTORTION_MODEL_NUKE); + + NukeCameraIntrinsics* nuke_intrinsics = + (NukeCameraIntrinsics*)camera_intrinsics; + + double k1 = libmv_camera_intrinsics_options->nuke_k1; + double k2 = libmv_camera_intrinsics_options->nuke_k2; + + if (nuke_intrinsics->k1() != k1 || nuke_intrinsics->k2() != k2) { + nuke_intrinsics->SetDistortion(k1, k2); } - case LIBMV_DISTORTION_MODEL_NUKE: - { - assert(camera_intrinsics->GetDistortionModelType() == - libmv::DISTORTION_MODEL_NUKE); + break; + } - NukeCameraIntrinsics *nuke_intrinsics = - (NukeCameraIntrinsics *) camera_intrinsics; + case LIBMV_DISTORTION_MODEL_BROWN: { + assert(camera_intrinsics->GetDistortionModelType() == + libmv::DISTORTION_MODEL_BROWN); - double k1 = libmv_camera_intrinsics_options->nuke_k1; - double k2 = libmv_camera_intrinsics_options->nuke_k2; + BrownCameraIntrinsics* brown_intrinsics = + (BrownCameraIntrinsics*)camera_intrinsics; - if (nuke_intrinsics->k1() != k1 || - nuke_intrinsics->k2() != k2) { - nuke_intrinsics->SetDistortion(k1, k2); - } + double k1 = libmv_camera_intrinsics_options->brown_k1; + double k2 = libmv_camera_intrinsics_options->brown_k2; + double k3 = libmv_camera_intrinsics_options->brown_k3; + double k4 = libmv_camera_intrinsics_options->brown_k4; - break; + if (brown_intrinsics->k1() != k1 || brown_intrinsics->k2() != k2 || + brown_intrinsics->k3() != k3 || brown_intrinsics->k4() != k4) { + brown_intrinsics->SetRadialDistortion(k1, k2, k3, k4); } - case LIBMV_DISTORTION_MODEL_BROWN: - { - assert(camera_intrinsics->GetDistortionModelType() == - libmv::DISTORTION_MODEL_BROWN); - - BrownCameraIntrinsics *brown_intrinsics = - (BrownCameraIntrinsics *) camera_intrinsics; - - double k1 = libmv_camera_intrinsics_options->brown_k1; - double k2 = libmv_camera_intrinsics_options->brown_k2; - double k3 = libmv_camera_intrinsics_options->brown_k3; - double k4 = libmv_camera_intrinsics_options->brown_k4; - - if (brown_intrinsics->k1() != k1 || - brown_intrinsics->k2() != k2 || - brown_intrinsics->k3() != k3 || - brown_intrinsics->k4() != k4) { - brown_intrinsics->SetRadialDistortion(k1, k2, k3, k4); - } - - double p1 = libmv_camera_intrinsics_options->brown_p1; - double p2 = libmv_camera_intrinsics_options->brown_p2; - - if (brown_intrinsics->p1() != p1 || brown_intrinsics->p2() != p2) { - brown_intrinsics->SetTangentialDistortion(p1, p2); - } - break; + double p1 = libmv_camera_intrinsics_options->brown_p1; + double p2 = libmv_camera_intrinsics_options->brown_p2; + + if (brown_intrinsics->p1() != p1 || brown_intrinsics->p2() != p2) { + brown_intrinsics->SetTangentialDistortion(p1, p2); } + break; + } - default: - assert(!"Unknown distortion model"); + default: assert(!"Unknown distortion model"); } } void libmv_cameraIntrinsicsSetThreads(libmv_CameraIntrinsics* libmv_intrinsics, int threads) { - CameraIntrinsics *camera_intrinsics = (CameraIntrinsics *) libmv_intrinsics; + CameraIntrinsics* camera_intrinsics = (CameraIntrinsics*)libmv_intrinsics; camera_intrinsics->SetThreads(threads); } void libmv_cameraIntrinsicsExtractOptions( const libmv_CameraIntrinsics* libmv_intrinsics, libmv_CameraIntrinsicsOptions* camera_intrinsics_options) { - const CameraIntrinsics *camera_intrinsics = - (const CameraIntrinsics *) libmv_intrinsics; + const CameraIntrinsics* camera_intrinsics = + (const CameraIntrinsics*)libmv_intrinsics; // Fill in options which are common for all distortion models. camera_intrinsics_options->focal_length = camera_intrinsics->focal_length(); camera_intrinsics_options->principal_point_x = - camera_intrinsics->principal_point_x(); + camera_intrinsics->principal_point_x(); camera_intrinsics_options->principal_point_y = - camera_intrinsics->principal_point_y(); + camera_intrinsics->principal_point_y(); camera_intrinsics_options->image_width = camera_intrinsics->image_width(); camera_intrinsics_options->image_height = camera_intrinsics->image_height(); switch (camera_intrinsics->GetDistortionModelType()) { - case libmv::DISTORTION_MODEL_POLYNOMIAL: - { - const PolynomialCameraIntrinsics *polynomial_intrinsics = - static_cast<const PolynomialCameraIntrinsics *>(camera_intrinsics); - camera_intrinsics_options->distortion_model = + case libmv::DISTORTION_MODEL_POLYNOMIAL: { + const PolynomialCameraIntrinsics* polynomial_intrinsics = + static_cast<const PolynomialCameraIntrinsics*>(camera_intrinsics); + camera_intrinsics_options->distortion_model = LIBMV_DISTORTION_MODEL_POLYNOMIAL; - camera_intrinsics_options->polynomial_k1 = polynomial_intrinsics->k1(); - camera_intrinsics_options->polynomial_k2 = polynomial_intrinsics->k2(); - camera_intrinsics_options->polynomial_k3 = polynomial_intrinsics->k3(); - camera_intrinsics_options->polynomial_p1 = polynomial_intrinsics->p1(); - camera_intrinsics_options->polynomial_p2 = polynomial_intrinsics->p2(); - break; - } + camera_intrinsics_options->polynomial_k1 = polynomial_intrinsics->k1(); + camera_intrinsics_options->polynomial_k2 = polynomial_intrinsics->k2(); + camera_intrinsics_options->polynomial_k3 = polynomial_intrinsics->k3(); + camera_intrinsics_options->polynomial_p1 = polynomial_intrinsics->p1(); + camera_intrinsics_options->polynomial_p2 = polynomial_intrinsics->p2(); + break; + } - case libmv::DISTORTION_MODEL_DIVISION: - { - const DivisionCameraIntrinsics *division_intrinsics = - static_cast<const DivisionCameraIntrinsics *>(camera_intrinsics); - camera_intrinsics_options->distortion_model = + case libmv::DISTORTION_MODEL_DIVISION: { + const DivisionCameraIntrinsics* division_intrinsics = + static_cast<const DivisionCameraIntrinsics*>(camera_intrinsics); + camera_intrinsics_options->distortion_model = LIBMV_DISTORTION_MODEL_DIVISION; - camera_intrinsics_options->division_k1 = division_intrinsics->k1(); - camera_intrinsics_options->division_k2 = division_intrinsics->k2(); - break; - } - - case libmv::DISTORTION_MODEL_NUKE: - { - const NukeCameraIntrinsics *nuke_intrinsics = - static_cast<const NukeCameraIntrinsics *>(camera_intrinsics); - camera_intrinsics_options->distortion_model = - LIBMV_DISTORTION_MODEL_NUKE; - camera_intrinsics_options->nuke_k1 = nuke_intrinsics->k1(); - camera_intrinsics_options->nuke_k2 = nuke_intrinsics->k2(); - break; - } + camera_intrinsics_options->division_k1 = division_intrinsics->k1(); + camera_intrinsics_options->division_k2 = division_intrinsics->k2(); + break; + } + + case libmv::DISTORTION_MODEL_NUKE: { + const NukeCameraIntrinsics* nuke_intrinsics = + static_cast<const NukeCameraIntrinsics*>(camera_intrinsics); + camera_intrinsics_options->distortion_model = LIBMV_DISTORTION_MODEL_NUKE; + camera_intrinsics_options->nuke_k1 = nuke_intrinsics->k1(); + camera_intrinsics_options->nuke_k2 = nuke_intrinsics->k2(); + break; + } - case libmv::DISTORTION_MODEL_BROWN: - { - const BrownCameraIntrinsics *brown_intrinsics = - static_cast<const BrownCameraIntrinsics *>(camera_intrinsics); - camera_intrinsics_options->distortion_model = + case libmv::DISTORTION_MODEL_BROWN: { + const BrownCameraIntrinsics* brown_intrinsics = + static_cast<const BrownCameraIntrinsics*>(camera_intrinsics); + camera_intrinsics_options->distortion_model = LIBMV_DISTORTION_MODEL_BROWN; - camera_intrinsics_options->brown_k1 = brown_intrinsics->k1(); - camera_intrinsics_options->brown_k2 = brown_intrinsics->k2(); - camera_intrinsics_options->brown_k3 = brown_intrinsics->k3(); - camera_intrinsics_options->brown_k4 = brown_intrinsics->k4(); - camera_intrinsics_options->brown_p1 = brown_intrinsics->p1(); - camera_intrinsics_options->brown_p2 = brown_intrinsics->p2(); - break; - } + camera_intrinsics_options->brown_k1 = brown_intrinsics->k1(); + camera_intrinsics_options->brown_k2 = brown_intrinsics->k2(); + camera_intrinsics_options->brown_k3 = brown_intrinsics->k3(); + camera_intrinsics_options->brown_k4 = brown_intrinsics->k4(); + camera_intrinsics_options->brown_p1 = brown_intrinsics->p1(); + camera_intrinsics_options->brown_p2 = brown_intrinsics->p2(); + break; + } - default: - assert(!"Unknown distortion model"); + default: assert(!"Unknown distortion model"); } } void libmv_cameraIntrinsicsUndistortByte( const libmv_CameraIntrinsics* libmv_intrinsics, - const unsigned char *source_image, + const unsigned char* source_image, int width, int height, float overscan, int channels, unsigned char* destination_image) { - CameraIntrinsics *camera_intrinsics = (CameraIntrinsics *) libmv_intrinsics; - camera_intrinsics->UndistortBuffer(source_image, - width, height, - overscan, - channels, - destination_image); + CameraIntrinsics* camera_intrinsics = (CameraIntrinsics*)libmv_intrinsics; + camera_intrinsics->UndistortBuffer( + source_image, width, height, overscan, channels, destination_image); } void libmv_cameraIntrinsicsUndistortFloat( @@ -310,28 +286,22 @@ void libmv_cameraIntrinsicsUndistortFloat( float overscan, int channels, float* destination_image) { - CameraIntrinsics *intrinsics = (CameraIntrinsics *) libmv_intrinsics; - intrinsics->UndistortBuffer(source_image, - width, height, - overscan, - channels, - destination_image); + CameraIntrinsics* intrinsics = (CameraIntrinsics*)libmv_intrinsics; + intrinsics->UndistortBuffer( + source_image, width, height, overscan, channels, destination_image); } void libmv_cameraIntrinsicsDistortByte( const struct libmv_CameraIntrinsics* libmv_intrinsics, - const unsigned char *source_image, + const unsigned char* source_image, int width, int height, float overscan, int channels, - unsigned char *destination_image) { - CameraIntrinsics *intrinsics = (CameraIntrinsics *) libmv_intrinsics; - intrinsics->DistortBuffer(source_image, - width, height, - overscan, - channels, - destination_image); + unsigned char* destination_image) { + CameraIntrinsics* intrinsics = (CameraIntrinsics*)libmv_intrinsics; + intrinsics->DistortBuffer( + source_image, width, height, overscan, channels, destination_image); } void libmv_cameraIntrinsicsDistortFloat( @@ -342,12 +312,9 @@ void libmv_cameraIntrinsicsDistortFloat( float overscan, int channels, float* destination_image) { - CameraIntrinsics *intrinsics = (CameraIntrinsics *) libmv_intrinsics; - intrinsics->DistortBuffer(source_image, - width, height, - overscan, - channels, - destination_image); + CameraIntrinsics* intrinsics = (CameraIntrinsics*)libmv_intrinsics; + intrinsics->DistortBuffer( + source_image, width, height, overscan, channels, destination_image); } void libmv_cameraIntrinsicsApply( @@ -356,7 +323,7 @@ void libmv_cameraIntrinsicsApply( double y, double* x1, double* y1) { - CameraIntrinsics *intrinsics = (CameraIntrinsics *) libmv_intrinsics; + CameraIntrinsics* intrinsics = (CameraIntrinsics*)libmv_intrinsics; intrinsics->ApplyIntrinsics(x, y, x1, y1); } @@ -366,7 +333,7 @@ void libmv_cameraIntrinsicsInvert( double y, double* x1, double* y1) { - CameraIntrinsics *intrinsics = (CameraIntrinsics *) libmv_intrinsics; + CameraIntrinsics* intrinsics = (CameraIntrinsics*)libmv_intrinsics; intrinsics->InvertIntrinsics(x, y, x1, y1); } @@ -381,69 +348,63 @@ static void libmv_cameraIntrinsicsFillFromOptions( camera_intrinsics_options->principal_point_y); camera_intrinsics->SetImageSize(camera_intrinsics_options->image_width, - camera_intrinsics_options->image_height); + camera_intrinsics_options->image_height); switch (camera_intrinsics_options->distortion_model) { - case LIBMV_DISTORTION_MODEL_POLYNOMIAL: - { - PolynomialCameraIntrinsics *polynomial_intrinsics = + case LIBMV_DISTORTION_MODEL_POLYNOMIAL: { + PolynomialCameraIntrinsics* polynomial_intrinsics = static_cast<PolynomialCameraIntrinsics*>(camera_intrinsics); - polynomial_intrinsics->SetRadialDistortion( - camera_intrinsics_options->polynomial_k1, - camera_intrinsics_options->polynomial_k2, - camera_intrinsics_options->polynomial_k3); + polynomial_intrinsics->SetRadialDistortion( + camera_intrinsics_options->polynomial_k1, + camera_intrinsics_options->polynomial_k2, + camera_intrinsics_options->polynomial_k3); - break; - } + break; + } - case LIBMV_DISTORTION_MODEL_DIVISION: - { - DivisionCameraIntrinsics *division_intrinsics = + case LIBMV_DISTORTION_MODEL_DIVISION: { + DivisionCameraIntrinsics* division_intrinsics = static_cast<DivisionCameraIntrinsics*>(camera_intrinsics); - division_intrinsics->SetDistortion( - camera_intrinsics_options->division_k1, - camera_intrinsics_options->division_k2); - break; - } + division_intrinsics->SetDistortion( + camera_intrinsics_options->division_k1, + camera_intrinsics_options->division_k2); + break; + } - case LIBMV_DISTORTION_MODEL_NUKE: - { - NukeCameraIntrinsics *nuke_intrinsics = + case LIBMV_DISTORTION_MODEL_NUKE: { + NukeCameraIntrinsics* nuke_intrinsics = static_cast<NukeCameraIntrinsics*>(camera_intrinsics); - nuke_intrinsics->SetDistortion( - camera_intrinsics_options->nuke_k1, - camera_intrinsics_options->nuke_k2); - break; - } + nuke_intrinsics->SetDistortion(camera_intrinsics_options->nuke_k1, + camera_intrinsics_options->nuke_k2); + break; + } - case LIBMV_DISTORTION_MODEL_BROWN: - { - BrownCameraIntrinsics *brown_intrinsics = + case LIBMV_DISTORTION_MODEL_BROWN: { + BrownCameraIntrinsics* brown_intrinsics = static_cast<BrownCameraIntrinsics*>(camera_intrinsics); - brown_intrinsics->SetRadialDistortion( - camera_intrinsics_options->brown_k1, - camera_intrinsics_options->brown_k2, - camera_intrinsics_options->brown_k3, - camera_intrinsics_options->brown_k4); - brown_intrinsics->SetTangentialDistortion( + brown_intrinsics->SetRadialDistortion( + camera_intrinsics_options->brown_k1, + camera_intrinsics_options->brown_k2, + camera_intrinsics_options->brown_k3, + camera_intrinsics_options->brown_k4); + brown_intrinsics->SetTangentialDistortion( camera_intrinsics_options->brown_p1, camera_intrinsics_options->brown_p2); - break; - } + break; + } - default: - assert(!"Unknown distortion model"); + default: assert(!"Unknown distortion model"); } } CameraIntrinsics* libmv_cameraIntrinsicsCreateFromOptions( const libmv_CameraIntrinsicsOptions* camera_intrinsics_options) { - CameraIntrinsics *camera_intrinsics = NULL; + CameraIntrinsics* camera_intrinsics = NULL; switch (camera_intrinsics_options->distortion_model) { case LIBMV_DISTORTION_MODEL_POLYNOMIAL: camera_intrinsics = LIBMV_OBJECT_NEW(PolynomialCameraIntrinsics); @@ -457,8 +418,7 @@ CameraIntrinsics* libmv_cameraIntrinsicsCreateFromOptions( case LIBMV_DISTORTION_MODEL_BROWN: camera_intrinsics = LIBMV_OBJECT_NEW(BrownCameraIntrinsics); break; - default: - assert(!"Unknown distortion model"); + default: assert(!"Unknown distortion model"); } libmv_cameraIntrinsicsFillFromOptions(camera_intrinsics_options, camera_intrinsics); diff --git a/intern/libmv/intern/camera_intrinsics.h b/intern/libmv/intern/camera_intrinsics.h index eb6176770ec..8a65c93e6a4 100644 --- a/intern/libmv/intern/camera_intrinsics.h +++ b/intern/libmv/intern/camera_intrinsics.h @@ -56,10 +56,10 @@ typedef struct libmv_CameraIntrinsicsOptions { double brown_p1, brown_p2; } libmv_CameraIntrinsicsOptions; -libmv_CameraIntrinsics *libmv_cameraIntrinsicsNew( +libmv_CameraIntrinsics* libmv_cameraIntrinsicsNew( const libmv_CameraIntrinsicsOptions* libmv_camera_intrinsics_options); -libmv_CameraIntrinsics *libmv_cameraIntrinsicsCopy( +libmv_CameraIntrinsics* libmv_cameraIntrinsicsCopy( const libmv_CameraIntrinsics* libmv_intrinsics); void libmv_cameraIntrinsicsDestroy(libmv_CameraIntrinsics* libmv_intrinsics); @@ -76,7 +76,7 @@ void libmv_cameraIntrinsicsExtractOptions( void libmv_cameraIntrinsicsUndistortByte( const libmv_CameraIntrinsics* libmv_intrinsics, - const unsigned char *source_image, + const unsigned char* source_image, int width, int height, float overscan, @@ -94,12 +94,12 @@ void libmv_cameraIntrinsicsUndistortFloat( void libmv_cameraIntrinsicsDistortByte( const struct libmv_CameraIntrinsics* libmv_intrinsics, - const unsigned char *source_image, + const unsigned char* source_image, int width, int height, float overscan, int channels, - unsigned char *destination_image); + unsigned char* destination_image); void libmv_cameraIntrinsicsDistortFloat( const libmv_CameraIntrinsics* libmv_intrinsics, @@ -131,7 +131,7 @@ void libmv_cameraIntrinsicsInvert( #ifdef __cplusplus namespace libmv { - class CameraIntrinsics; +class CameraIntrinsics; } libmv::CameraIntrinsics* libmv_cameraIntrinsicsCreateFromOptions( diff --git a/intern/libmv/intern/detector.cc b/intern/libmv/intern/detector.cc index 455e431f6f4..21f5b46595c 100644 --- a/intern/libmv/intern/detector.cc +++ b/intern/libmv/intern/detector.cc @@ -34,7 +34,7 @@ struct libmv_Features { namespace { -libmv_Features *libmv_featuresFromVector( +libmv_Features* libmv_featuresFromVector( const libmv::vector<Feature>& features) { libmv_Features* libmv_features = LIBMV_STRUCT_NEW(libmv_Features, 1); int count = features.size(); @@ -50,12 +50,12 @@ libmv_Features *libmv_featuresFromVector( return libmv_features; } -void libmv_convertDetectorOptions(libmv_DetectOptions *options, - DetectOptions *detector_options) { +void libmv_convertDetectorOptions(libmv_DetectOptions* options, + DetectOptions* detector_options) { switch (options->detector) { -#define LIBMV_CONVERT(the_detector) \ - case LIBMV_DETECTOR_ ## the_detector: \ - detector_options->type = DetectOptions::the_detector; \ +#define LIBMV_CONVERT(the_detector) \ + case LIBMV_DETECTOR_##the_detector: \ + detector_options->type = DetectOptions::the_detector; \ break; LIBMV_CONVERT(FAST) LIBMV_CONVERT(MORAVEC) @@ -72,7 +72,7 @@ void libmv_convertDetectorOptions(libmv_DetectOptions *options, } // namespace -libmv_Features *libmv_detectFeaturesByte(const unsigned char* image_buffer, +libmv_Features* libmv_detectFeaturesByte(const unsigned char* image_buffer, int width, int height, int channels, @@ -133,7 +133,7 @@ void libmv_getFeature(const libmv_Features* libmv_features, double* y, double* score, double* size) { - Feature &feature = libmv_features->features[number]; + Feature& feature = libmv_features->features[number]; *x = feature.x; *y = feature.y; *score = feature.score; diff --git a/intern/libmv/intern/detector.h b/intern/libmv/intern/detector.h index b36935fc67f..f21e78d7f2b 100644 --- a/intern/libmv/intern/detector.h +++ b/intern/libmv/intern/detector.h @@ -38,7 +38,7 @@ typedef struct libmv_DetectOptions { int min_distance; int fast_min_trackness; int moravec_max_count; - unsigned char *moravec_pattern; + unsigned char* moravec_pattern; double harris_threshold; } libmv_DetectOptions; diff --git a/intern/libmv/intern/frame_accessor.cc b/intern/libmv/intern/frame_accessor.cc index 9fde73f0d71..3a6c753cc8d 100644 --- a/intern/libmv/intern/frame_accessor.cc +++ b/intern/libmv/intern/frame_accessor.cc @@ -36,20 +36,18 @@ struct LibmvFrameAccessor : public FrameAccessor { libmv_ReleaseImageCallback release_image_callback, libmv_GetMaskForTrackCallback get_mask_for_track_callback, libmv_ReleaseMaskCallback release_mask_callback) - : user_data_(user_data), - get_image_callback_(get_image_callback), - release_image_callback_(release_image_callback), - get_mask_for_track_callback_(get_mask_for_track_callback), - release_mask_callback_(release_mask_callback) { } + : user_data_(user_data), + get_image_callback_(get_image_callback), + release_image_callback_(release_image_callback), + get_mask_for_track_callback_(get_mask_for_track_callback), + release_mask_callback_(release_mask_callback) {} - virtual ~LibmvFrameAccessor() { - } + virtual ~LibmvFrameAccessor() {} libmv_InputMode get_libmv_input_mode(InputMode input_mode) { switch (input_mode) { -#define CHECK_INPUT_MODE(mode) \ - case mode: \ - return LIBMV_IMAGE_MODE_ ## mode; +#define CHECK_INPUT_MODE(mode) \ + case mode: return LIBMV_IMAGE_MODE_##mode; CHECK_INPUT_MODE(MONO) CHECK_INPUT_MODE(RGBA) #undef CHECK_INPUT_MODE @@ -59,8 +57,7 @@ struct LibmvFrameAccessor : public FrameAccessor { return LIBMV_IMAGE_MODE_MONO; } - void get_libmv_region(const Region& region, - libmv_Region* libmv_region) { + void get_libmv_region(const Region& region, libmv_Region* libmv_region) { libmv_region->min[0] = region.min(0); libmv_region->min[1] = region.min(1); libmv_region->max[0] = region.max(0); @@ -74,7 +71,7 @@ struct LibmvFrameAccessor : public FrameAccessor { const Region* region, const Transform* transform, FloatImage* destination) { - float *float_buffer; + float* float_buffer; int width, height, channels; libmv_Region libmv_region; if (region) { @@ -86,46 +83,41 @@ struct LibmvFrameAccessor : public FrameAccessor { get_libmv_input_mode(input_mode), downscale, region != NULL ? &libmv_region : NULL, - (libmv_FrameTransform*) transform, + (libmv_FrameTransform*)transform, &float_buffer, &width, &height, &channels); // TODO(sergey): Dumb code for until we can set data directly. - FloatImage temp_image(float_buffer, - height, - width, - channels); + FloatImage temp_image(float_buffer, height, width, channels); destination->CopyFrom(temp_image); return cache_key; } - void ReleaseImage(Key cache_key) { - release_image_callback_(cache_key); - } + void ReleaseImage(Key cache_key) { release_image_callback_(cache_key); } Key GetMaskForTrack(int clip, int frame, int track, const Region* region, FloatImage* destination) { - float *float_buffer; + float* float_buffer; int width, height; libmv_Region libmv_region; if (region) { get_libmv_region(*region, &libmv_region); } - Key cache_key = get_mask_for_track_callback_( - user_data_, - clip, - frame, - track, - region != NULL ? &libmv_region : NULL, - &float_buffer, - &width, - &height); + Key cache_key = + get_mask_for_track_callback_(user_data_, + clip, + frame, + track, + region != NULL ? &libmv_region : NULL, + &float_buffer, + &width, + &height); if (cache_key == NULL) { // No mask for the given track. @@ -133,30 +125,21 @@ struct LibmvFrameAccessor : public FrameAccessor { } // TODO(sergey): Dumb code for until we can set data directly. - FloatImage temp_image(float_buffer, - height, - width, - 1); + FloatImage temp_image(float_buffer, height, width, 1); destination->CopyFrom(temp_image); return cache_key; } - void ReleaseMask(Key key) { - release_mask_callback_(key); - } + void ReleaseMask(Key key) { release_mask_callback_(key); } - bool GetClipDimensions(int /*clip*/, int * /*width*/, int * /*height*/) { + bool GetClipDimensions(int /*clip*/, int* /*width*/, int* /*height*/) { return false; } - int NumClips() { - return 1; - } + int NumClips() { return 1; } - int NumFrames(int /*clip*/) { - return 0; - } + int NumFrames(int /*clip*/) { return 0; } libmv_FrameAccessorUserData* user_data_; libmv_GetImageCallback get_image_callback_; @@ -173,35 +156,35 @@ libmv_FrameAccessor* libmv_FrameAccessorNew( libmv_ReleaseImageCallback release_image_callback, libmv_GetMaskForTrackCallback get_mask_for_track_callback, libmv_ReleaseMaskCallback release_mask_callback) { - return (libmv_FrameAccessor*) LIBMV_OBJECT_NEW(LibmvFrameAccessor, - user_data, - get_image_callback, - release_image_callback, - get_mask_for_track_callback, - release_mask_callback); + return (libmv_FrameAccessor*)LIBMV_OBJECT_NEW(LibmvFrameAccessor, + user_data, + get_image_callback, + release_image_callback, + get_mask_for_track_callback, + release_mask_callback); } void libmv_FrameAccessorDestroy(libmv_FrameAccessor* frame_accessor) { LIBMV_OBJECT_DELETE(frame_accessor, LibmvFrameAccessor); } -int64_t libmv_frameAccessorgetTransformKey(const libmv_FrameTransform *transform) { - return ((FrameAccessor::Transform*) transform)->key(); +int64_t libmv_frameAccessorgetTransformKey( + const libmv_FrameTransform* transform) { + return ((FrameAccessor::Transform*)transform)->key(); } -void libmv_frameAccessorgetTransformRun(const libmv_FrameTransform *transform, - const libmv_FloatImage *input_image, - libmv_FloatImage *output_image) { +void libmv_frameAccessorgetTransformRun(const libmv_FrameTransform* transform, + const libmv_FloatImage* input_image, + libmv_FloatImage* output_image) { const FloatImage input(input_image->buffer, input_image->height, input_image->width, input_image->channels); FloatImage output; - ((FrameAccessor::Transform*) transform)->run(input, - &output); + ((FrameAccessor::Transform*)transform)->run(input, &output); - int num_pixels = output.Width() *output.Height() * output.Depth(); + int num_pixels = output.Width() * output.Height() * output.Depth(); output_image->buffer = new float[num_pixels]; memcpy(output_image->buffer, output.Data(), num_pixels * sizeof(float)); output_image->width = output.Width(); diff --git a/intern/libmv/intern/frame_accessor.h b/intern/libmv/intern/frame_accessor.h index 6bccb305282..39a3bc5eb1d 100644 --- a/intern/libmv/intern/frame_accessor.h +++ b/intern/libmv/intern/frame_accessor.h @@ -32,14 +32,14 @@ extern "C" { typedef struct libmv_FrameAccessor libmv_FrameAccessor; typedef struct libmv_FrameTransform libmv_FrameTransform; typedef struct libmv_FrameAccessorUserData libmv_FrameAccessorUserData; -typedef void *libmv_CacheKey; +typedef void* libmv_CacheKey; typedef enum { LIBMV_IMAGE_MODE_MONO, LIBMV_IMAGE_MODE_RGBA, } libmv_InputMode; -typedef libmv_CacheKey (*libmv_GetImageCallback) ( +typedef libmv_CacheKey (*libmv_GetImageCallback)( libmv_FrameAccessorUserData* user_data, int clip, int frame, @@ -52,9 +52,9 @@ typedef libmv_CacheKey (*libmv_GetImageCallback) ( int* height, int* channels); -typedef void (*libmv_ReleaseImageCallback) (libmv_CacheKey cache_key); +typedef void (*libmv_ReleaseImageCallback)(libmv_CacheKey cache_key); -typedef libmv_CacheKey (*libmv_GetMaskForTrackCallback) ( +typedef libmv_CacheKey (*libmv_GetMaskForTrackCallback)( libmv_FrameAccessorUserData* user_data, int clip, int frame, @@ -63,7 +63,7 @@ typedef libmv_CacheKey (*libmv_GetMaskForTrackCallback) ( float** destination, int* width, int* height); -typedef void (*libmv_ReleaseMaskCallback) (libmv_CacheKey cache_key); +typedef void (*libmv_ReleaseMaskCallback)(libmv_CacheKey cache_key); libmv_FrameAccessor* libmv_FrameAccessorNew( libmv_FrameAccessorUserData* user_data, @@ -73,11 +73,12 @@ libmv_FrameAccessor* libmv_FrameAccessorNew( libmv_ReleaseMaskCallback release_mask_callback); void libmv_FrameAccessorDestroy(libmv_FrameAccessor* frame_accessor); -int64_t libmv_frameAccessorgetTransformKey(const libmv_FrameTransform *transform); +int64_t libmv_frameAccessorgetTransformKey( + const libmv_FrameTransform* transform); -void libmv_frameAccessorgetTransformRun(const libmv_FrameTransform *transform, - const libmv_FloatImage *input_image, - libmv_FloatImage *output_image); +void libmv_frameAccessorgetTransformRun(const libmv_FrameTransform* transform, + const libmv_FloatImage* input_image, + libmv_FloatImage* output_image); #ifdef __cplusplus } #endif diff --git a/intern/libmv/intern/homography.cc b/intern/libmv/intern/homography.cc index 179aeaa08aa..dc1009b5636 100644 --- a/intern/libmv/intern/homography.cc +++ b/intern/libmv/intern/homography.cc @@ -41,10 +41,8 @@ void libmv_homography2DFromCorrespondencesEuc(/* const */ double (*x1)[2], LG << "x2: " << x2_mat; libmv::EstimateHomographyOptions options; - libmv::EstimateHomography2DFromCorrespondences(x1_mat, - x2_mat, - options, - &H_mat); + libmv::EstimateHomography2DFromCorrespondences( + x1_mat, x2_mat, options, &H_mat); LG << "H: " << H_mat; diff --git a/intern/libmv/intern/image.cc b/intern/libmv/intern/image.cc index a6e09277680..564e4762448 100644 --- a/intern/libmv/intern/image.cc +++ b/intern/libmv/intern/image.cc @@ -21,14 +21,14 @@ #include "intern/utildefines.h" #include "libmv/tracking/track_region.h" -#include <cassert> #include <png.h> +#include <cassert> using libmv::FloatImage; using libmv::SamplePlanarPatch; -void libmv_floatImageDestroy(libmv_FloatImage *image) { - delete [] image->buffer; +void libmv_floatImageDestroy(libmv_FloatImage* image) { + delete[] image->buffer; } /* Image <-> buffers conversion */ @@ -63,8 +63,7 @@ void libmv_floatBufferToFloatImage(const float* buffer, } } -void libmv_floatImageToFloatBuffer(const FloatImage &image, - float* buffer) { +void libmv_floatImageToFloatBuffer(const FloatImage& image, float* buffer) { for (int y = 0, a = 0; y < image.Height(); y++) { for (int x = 0; x < image.Width(); x++) { for (int k = 0; k < image.Depth(); k++) { @@ -74,9 +73,9 @@ void libmv_floatImageToFloatBuffer(const FloatImage &image, } } -void libmv_floatImageToByteBuffer(const libmv::FloatImage &image, +void libmv_floatImageToByteBuffer(const libmv::FloatImage& image, unsigned char* buffer) { - for (int y = 0, a= 0; y < image.Height(); y++) { + for (int y = 0, a = 0; y < image.Height(); y++) { for (int x = 0; x < image.Width(); x++) { for (int k = 0; k < image.Depth(); k++) { buffer[a++] = image(y, x, k) * 255.0f; @@ -93,7 +92,7 @@ static bool savePNGImage(png_bytep* row_pointers, const char* file_name) { png_infop info_ptr; png_structp png_ptr; - FILE *fp = fopen(file_name, "wb"); + FILE* fp = fopen(file_name, "wb"); if (fp == NULL) { return false; @@ -153,7 +152,7 @@ bool libmv_saveImage(const FloatImage& image, int x0, int y0) { int x, y; - png_bytep *row_pointers; + png_bytep* row_pointers; assert(image.Depth() == 1); @@ -180,9 +179,8 @@ bool libmv_saveImage(const FloatImage& image, static int image_counter = 0; char file_name[128]; - snprintf(file_name, sizeof(file_name), - "%s_%02d.png", - prefix, ++image_counter); + snprintf( + file_name, sizeof(file_name), "%s_%02d.png", prefix, ++image_counter); bool result = savePNGImage(row_pointers, image.Width(), image.Height(), @@ -191,9 +189,9 @@ bool libmv_saveImage(const FloatImage& image, file_name); for (y = 0; y < image.Height(); y++) { - delete [] row_pointers[y]; + delete[] row_pointers[y]; } - delete [] row_pointers; + delete[] row_pointers; return result; } @@ -211,7 +209,7 @@ void libmv_samplePlanarPatchFloat(const float* image, double* warped_position_x, double* warped_position_y) { FloatImage libmv_image, libmv_patch, libmv_mask; - FloatImage *libmv_mask_for_sample = NULL; + FloatImage* libmv_mask_for_sample = NULL; libmv_floatBufferToFloatImage(image, width, height, channels, &libmv_image); @@ -221,8 +219,10 @@ void libmv_samplePlanarPatchFloat(const float* image, } SamplePlanarPatch(libmv_image, - xs, ys, - num_samples_x, num_samples_y, + xs, + ys, + num_samples_x, + num_samples_y, libmv_mask_for_sample, &libmv_patch, warped_position_x, @@ -232,19 +232,19 @@ void libmv_samplePlanarPatchFloat(const float* image, } void libmv_samplePlanarPatchByte(const unsigned char* image, - int width, - int height, - int channels, - const double* xs, - const double* ys, - int num_samples_x, - int num_samples_y, - const float* mask, - unsigned char* patch, - double* warped_position_x, - double* warped_position_y) { + int width, + int height, + int channels, + const double* xs, + const double* ys, + int num_samples_x, + int num_samples_y, + const float* mask, + unsigned char* patch, + double* warped_position_x, + double* warped_position_y) { libmv::FloatImage libmv_image, libmv_patch, libmv_mask; - libmv::FloatImage *libmv_mask_for_sample = NULL; + libmv::FloatImage* libmv_mask_for_sample = NULL; libmv_byteBufferToFloatImage(image, width, height, channels, &libmv_image); @@ -254,8 +254,10 @@ void libmv_samplePlanarPatchByte(const unsigned char* image, } libmv::SamplePlanarPatch(libmv_image, - xs, ys, - num_samples_x, num_samples_y, + xs, + ys, + num_samples_x, + num_samples_y, libmv_mask_for_sample, &libmv_patch, warped_position_x, diff --git a/intern/libmv/intern/image.h b/intern/libmv/intern/image.h index a1381a4c216..02cef86a127 100644 --- a/intern/libmv/intern/image.h +++ b/intern/libmv/intern/image.h @@ -35,7 +35,7 @@ void libmv_floatBufferToFloatImage(const float* buffer, libmv::FloatImage* image); void libmv_floatImageToFloatBuffer(const libmv::FloatImage& image, - float *buffer); + float* buffer); void libmv_floatImageToByteBuffer(const libmv::FloatImage& image, unsigned char* buffer); @@ -51,13 +51,13 @@ extern "C" { #endif typedef struct libmv_FloatImage { - float *buffer; + float* buffer; int width; int height; int channels; } libmv_FloatImage; -void libmv_floatImageDestroy(libmv_FloatImage *image); +void libmv_floatImageDestroy(libmv_FloatImage* image); void libmv_samplePlanarPatchFloat(const float* image, int width, @@ -72,18 +72,18 @@ void libmv_samplePlanarPatchFloat(const float* image, double* warped_position_x, double* warped_position_y); - void libmv_samplePlanarPatchByte(const unsigned char* image, - int width, - int height, - int channels, - const double* xs, - const double* ys, - int num_samples_x, - int num_samples_y, - const float* mask, - unsigned char* patch, - double* warped_position_x, - double* warped_position_y); +void libmv_samplePlanarPatchByte(const unsigned char* image, + int width, + int height, + int channels, + const double* xs, + const double* ys, + int num_samples_x, + int num_samples_y, + const float* mask, + unsigned char* patch, + double* warped_position_x, + double* warped_position_y); #ifdef __cplusplus } diff --git a/intern/libmv/intern/reconstruction.cc b/intern/libmv/intern/reconstruction.cc index 0f4e890d4ca..430607461da 100644 --- a/intern/libmv/intern/reconstruction.cc +++ b/intern/libmv/intern/reconstruction.cc @@ -24,8 +24,8 @@ #include "libmv/logging/logging.h" #include "libmv/simple_pipeline/bundle.h" -#include "libmv/simple_pipeline/keyframe_selection.h" #include "libmv/simple_pipeline/initialize_reconstruction.h" +#include "libmv/simple_pipeline/keyframe_selection.h" #include "libmv/simple_pipeline/modal_solver.h" #include "libmv/simple_pipeline/pipeline.h" #include "libmv/simple_pipeline/reconstruction_scale.h" @@ -39,19 +39,19 @@ using libmv::EuclideanScaleToUnity; using libmv::Marker; using libmv::ProgressUpdateCallback; -using libmv::PolynomialCameraIntrinsics; -using libmv::Tracks; using libmv::EuclideanBundle; using libmv::EuclideanCompleteReconstruction; using libmv::EuclideanReconstructTwoFrames; using libmv::EuclideanReprojectionError; +using libmv::PolynomialCameraIntrinsics; +using libmv::Tracks; struct libmv_Reconstruction { EuclideanReconstruction reconstruction; /* Used for per-track average error calculation after reconstruction */ Tracks tracks; - CameraIntrinsics *intrinsics; + CameraIntrinsics* intrinsics; double error; bool is_valid; @@ -63,7 +63,7 @@ class ReconstructUpdateCallback : public ProgressUpdateCallback { public: ReconstructUpdateCallback( reconstruct_progress_update_cb progress_update_callback, - void *callback_customdata) { + void* callback_customdata) { progress_update_callback_ = progress_update_callback; callback_customdata_ = callback_customdata; } @@ -73,13 +73,14 @@ class ReconstructUpdateCallback : public ProgressUpdateCallback { progress_update_callback_(callback_customdata_, progress, message); } } + protected: reconstruct_progress_update_cb progress_update_callback_; void* callback_customdata_; }; void libmv_solveRefineIntrinsics( - const Tracks &tracks, + const Tracks& tracks, const int refine_intrinsics, const int bundle_constraints, reconstruct_progress_update_cb progress_update_callback, @@ -96,11 +97,11 @@ void libmv_solveRefineIntrinsics( bundle_intrinsics |= libmv::BUNDLE_PRINCIPAL_POINT; } -#define SET_DISTORTION_FLAG_CHECKED(type, coefficient) \ - do { \ - if (refine_intrinsics & LIBMV_REFINE_ ## type ##_DISTORTION_ ## coefficient) { \ - bundle_intrinsics |= libmv::BUNDLE_ ## type ## _ ## coefficient; \ - } \ +#define SET_DISTORTION_FLAG_CHECKED(type, coefficient) \ + do { \ + if (refine_intrinsics & LIBMV_REFINE_##type##_DISTORTION_##coefficient) { \ + bundle_intrinsics |= libmv::BUNDLE_##type##_##coefficient; \ + } \ } while (0) SET_DISTORTION_FLAG_CHECKED(RADIAL, K1); @@ -123,20 +124,19 @@ void libmv_solveRefineIntrinsics( } void finishReconstruction( - const Tracks &tracks, - const CameraIntrinsics &camera_intrinsics, - libmv_Reconstruction *libmv_reconstruction, + const Tracks& tracks, + const CameraIntrinsics& camera_intrinsics, + libmv_Reconstruction* libmv_reconstruction, reconstruct_progress_update_cb progress_update_callback, - void *callback_customdata) { - EuclideanReconstruction &reconstruction = - libmv_reconstruction->reconstruction; + void* callback_customdata) { + EuclideanReconstruction& reconstruction = + libmv_reconstruction->reconstruction; /* Reprojection error calculation. */ progress_update_callback(callback_customdata, 1.0, "Finishing solution"); libmv_reconstruction->tracks = tracks; - libmv_reconstruction->error = EuclideanReprojectionError(tracks, - reconstruction, - camera_intrinsics); + libmv_reconstruction->error = + EuclideanReprojectionError(tracks, reconstruction, camera_intrinsics); } bool selectTwoKeyframesBasedOnGRICAndVariance( @@ -148,9 +148,8 @@ bool selectTwoKeyframesBasedOnGRICAndVariance( libmv::vector<int> keyframes; /* Get list of all keyframe candidates first. */ - SelectKeyframesBasedOnGRICAndVariance(normalized_tracks, - camera_intrinsics, - keyframes); + SelectKeyframesBasedOnGRICAndVariance( + normalized_tracks, camera_intrinsics, keyframes); if (keyframes.size() < 2) { LG << "Not enough keyframes detected by GRIC"; @@ -175,24 +174,20 @@ bool selectTwoKeyframesBasedOnGRICAndVariance( EuclideanReconstruction reconstruction; int current_keyframe = keyframes[i]; libmv::vector<Marker> keyframe_markers = - normalized_tracks.MarkersForTracksInBothImages(previous_keyframe, - current_keyframe); + normalized_tracks.MarkersForTracksInBothImages(previous_keyframe, + current_keyframe); Tracks keyframe_tracks(keyframe_markers); /* get a solution from two keyframes only */ EuclideanReconstructTwoFrames(keyframe_markers, &reconstruction); EuclideanBundle(keyframe_tracks, &reconstruction); - EuclideanCompleteReconstruction(keyframe_tracks, - &reconstruction, - NULL); + EuclideanCompleteReconstruction(keyframe_tracks, &reconstruction, NULL); - double current_error = EuclideanReprojectionError(tracks, - reconstruction, - camera_intrinsics); + double current_error = + EuclideanReprojectionError(tracks, reconstruction, camera_intrinsics); - LG << "Error between " << previous_keyframe - << " and " << current_keyframe + LG << "Error between " << previous_keyframe << " and " << current_keyframe << ": " << current_error; if (current_error < best_error) { @@ -214,53 +209,49 @@ Marker libmv_projectMarker(const EuclideanPoint& point, projected /= projected(2); libmv::Marker reprojected_marker; - intrinsics.ApplyIntrinsics(projected(0), projected(1), - &reprojected_marker.x, - &reprojected_marker.y); + intrinsics.ApplyIntrinsics( + projected(0), projected(1), &reprojected_marker.x, &reprojected_marker.y); reprojected_marker.image = camera.image; reprojected_marker.track = point.track; return reprojected_marker; } -void libmv_getNormalizedTracks(const Tracks &tracks, - const CameraIntrinsics &camera_intrinsics, - Tracks *normalized_tracks) { +void libmv_getNormalizedTracks(const Tracks& tracks, + const CameraIntrinsics& camera_intrinsics, + Tracks* normalized_tracks) { libmv::vector<Marker> markers = tracks.AllMarkers(); for (int i = 0; i < markers.size(); ++i) { - Marker &marker = markers[i]; - camera_intrinsics.InvertIntrinsics(marker.x, marker.y, - &marker.x, &marker.y); - normalized_tracks->Insert(marker.image, - marker.track, - marker.x, marker.y, - marker.weight); + Marker& marker = markers[i]; + camera_intrinsics.InvertIntrinsics( + marker.x, marker.y, &marker.x, &marker.y); + normalized_tracks->Insert( + marker.image, marker.track, marker.x, marker.y, marker.weight); } } } // namespace -libmv_Reconstruction *libmv_solveReconstruction( +libmv_Reconstruction* libmv_solveReconstruction( const libmv_Tracks* libmv_tracks, const libmv_CameraIntrinsicsOptions* libmv_camera_intrinsics_options, libmv_ReconstructionOptions* libmv_reconstruction_options, reconstruct_progress_update_cb progress_update_callback, void* callback_customdata) { - libmv_Reconstruction *libmv_reconstruction = - LIBMV_OBJECT_NEW(libmv_Reconstruction); + libmv_Reconstruction* libmv_reconstruction = + LIBMV_OBJECT_NEW(libmv_Reconstruction); - Tracks &tracks = *((Tracks *) libmv_tracks); - EuclideanReconstruction &reconstruction = - libmv_reconstruction->reconstruction; + Tracks& tracks = *((Tracks*)libmv_tracks); + EuclideanReconstruction& reconstruction = + libmv_reconstruction->reconstruction; ReconstructUpdateCallback update_callback = - ReconstructUpdateCallback(progress_update_callback, - callback_customdata); + ReconstructUpdateCallback(progress_update_callback, callback_customdata); /* Retrieve reconstruction options from C-API to libmv API. */ - CameraIntrinsics *camera_intrinsics; + CameraIntrinsics* camera_intrinsics; camera_intrinsics = libmv_reconstruction->intrinsics = - libmv_cameraIntrinsicsCreateFromOptions(libmv_camera_intrinsics_options); + libmv_cameraIntrinsicsCreateFromOptions(libmv_camera_intrinsics_options); /* Invert the camera intrinsics/ */ Tracks normalized_tracks; @@ -276,10 +267,10 @@ libmv_Reconstruction *libmv_solveReconstruction( update_callback.invoke(0, "Selecting keyframes"); if (selectTwoKeyframesBasedOnGRICAndVariance(tracks, - normalized_tracks, - *camera_intrinsics, - keyframe1, - keyframe2)) { + normalized_tracks, + *camera_intrinsics, + keyframe1, + keyframe2)) { /* so keyframes in the interface would be updated */ libmv_reconstruction_options->keyframe1 = keyframe1; libmv_reconstruction_options->keyframe2 = keyframe2; @@ -290,7 +281,7 @@ libmv_Reconstruction *libmv_solveReconstruction( LG << "frames to init from: " << keyframe1 << " " << keyframe2; libmv::vector<Marker> keyframe_markers = - normalized_tracks.MarkersForTracksInBothImages(keyframe1, keyframe2); + normalized_tracks.MarkersForTracksInBothImages(keyframe1, keyframe2); LG << "number of markers for init: " << keyframe_markers.size(); @@ -309,14 +300,12 @@ libmv_Reconstruction *libmv_solveReconstruction( } EuclideanBundle(normalized_tracks, &reconstruction); - EuclideanCompleteReconstruction(normalized_tracks, - &reconstruction, - &update_callback); + EuclideanCompleteReconstruction( + normalized_tracks, &reconstruction, &update_callback); /* Refinement. */ if (libmv_reconstruction_options->refine_intrinsics) { - libmv_solveRefineIntrinsics( - tracks, + libmv_solveRefineIntrinsics(tracks, libmv_reconstruction_options->refine_intrinsics, libmv::BUNDLE_NO_CONSTRAINTS, progress_update_callback, @@ -336,31 +325,29 @@ libmv_Reconstruction *libmv_solveReconstruction( callback_customdata); libmv_reconstruction->is_valid = true; - return (libmv_Reconstruction *) libmv_reconstruction; + return (libmv_Reconstruction*)libmv_reconstruction; } -libmv_Reconstruction *libmv_solveModal( - const libmv_Tracks *libmv_tracks, - const libmv_CameraIntrinsicsOptions *libmv_camera_intrinsics_options, - const libmv_ReconstructionOptions *libmv_reconstruction_options, +libmv_Reconstruction* libmv_solveModal( + const libmv_Tracks* libmv_tracks, + const libmv_CameraIntrinsicsOptions* libmv_camera_intrinsics_options, + const libmv_ReconstructionOptions* libmv_reconstruction_options, reconstruct_progress_update_cb progress_update_callback, - void *callback_customdata) { - libmv_Reconstruction *libmv_reconstruction = - LIBMV_OBJECT_NEW(libmv_Reconstruction); + void* callback_customdata) { + libmv_Reconstruction* libmv_reconstruction = + LIBMV_OBJECT_NEW(libmv_Reconstruction); - Tracks &tracks = *((Tracks *) libmv_tracks); - EuclideanReconstruction &reconstruction = - libmv_reconstruction->reconstruction; + Tracks& tracks = *((Tracks*)libmv_tracks); + EuclideanReconstruction& reconstruction = + libmv_reconstruction->reconstruction; ReconstructUpdateCallback update_callback = - ReconstructUpdateCallback(progress_update_callback, - callback_customdata); + ReconstructUpdateCallback(progress_update_callback, callback_customdata); /* Retrieve reconstruction options from C-API to libmv API. */ - CameraIntrinsics *camera_intrinsics; + CameraIntrinsics* camera_intrinsics; camera_intrinsics = libmv_reconstruction->intrinsics = - libmv_cameraIntrinsicsCreateFromOptions( - libmv_camera_intrinsics_options); + libmv_cameraIntrinsicsCreateFromOptions(libmv_camera_intrinsics_options); /* Invert the camera intrinsics. */ Tracks normalized_tracks; @@ -378,11 +365,11 @@ libmv_Reconstruction *libmv_solveModal( /* Refinement. */ if (libmv_reconstruction_options->refine_intrinsics) { - libmv_solveRefineIntrinsics( - tracks, + libmv_solveRefineIntrinsics(tracks, libmv_reconstruction_options->refine_intrinsics, libmv::BUNDLE_NO_TRANSLATION, - progress_update_callback, callback_customdata, + progress_update_callback, + callback_customdata, &reconstruction, camera_intrinsics); } @@ -395,26 +382,25 @@ libmv_Reconstruction *libmv_solveModal( callback_customdata); libmv_reconstruction->is_valid = true; - return (libmv_Reconstruction *) libmv_reconstruction; + return (libmv_Reconstruction*)libmv_reconstruction; } -int libmv_reconstructionIsValid(libmv_Reconstruction *libmv_reconstruction) { +int libmv_reconstructionIsValid(libmv_Reconstruction* libmv_reconstruction) { return libmv_reconstruction->is_valid; } -void libmv_reconstructionDestroy(libmv_Reconstruction *libmv_reconstruction) { +void libmv_reconstructionDestroy(libmv_Reconstruction* libmv_reconstruction) { LIBMV_OBJECT_DELETE(libmv_reconstruction->intrinsics, CameraIntrinsics); LIBMV_OBJECT_DELETE(libmv_reconstruction, libmv_Reconstruction); } int libmv_reprojectionPointForTrack( - const libmv_Reconstruction *libmv_reconstruction, + const libmv_Reconstruction* libmv_reconstruction, int track, double pos[3]) { - const EuclideanReconstruction *reconstruction = - &libmv_reconstruction->reconstruction; - const EuclideanPoint *point = - reconstruction->PointForTrack(track); + const EuclideanReconstruction* reconstruction = + &libmv_reconstruction->reconstruction; + const EuclideanPoint* point = reconstruction->PointForTrack(track); if (point) { pos[0] = point->X[0]; pos[1] = point->X[2]; @@ -425,23 +411,22 @@ int libmv_reprojectionPointForTrack( } double libmv_reprojectionErrorForTrack( - const libmv_Reconstruction *libmv_reconstruction, - int track) { - const EuclideanReconstruction *reconstruction = - &libmv_reconstruction->reconstruction; - const CameraIntrinsics *intrinsics = libmv_reconstruction->intrinsics; + const libmv_Reconstruction* libmv_reconstruction, int track) { + const EuclideanReconstruction* reconstruction = + &libmv_reconstruction->reconstruction; + const CameraIntrinsics* intrinsics = libmv_reconstruction->intrinsics; libmv::vector<Marker> markers = - libmv_reconstruction->tracks.MarkersForTrack(track); + libmv_reconstruction->tracks.MarkersForTrack(track); int num_reprojected = 0; double total_error = 0.0; for (int i = 0; i < markers.size(); ++i) { double weight = markers[i].weight; - const EuclideanCamera *camera = - reconstruction->CameraForImage(markers[i].image); - const EuclideanPoint *point = - reconstruction->PointForTrack(markers[i].track); + const EuclideanCamera* camera = + reconstruction->CameraForImage(markers[i].image); + const EuclideanPoint* point = + reconstruction->PointForTrack(markers[i].track); if (!camera || !point || weight == 0.0) { continue; @@ -450,7 +435,7 @@ double libmv_reprojectionErrorForTrack( num_reprojected++; Marker reprojected_marker = - libmv_projectMarker(*point, *camera, *intrinsics); + libmv_projectMarker(*point, *camera, *intrinsics); double ex = (reprojected_marker.x - markers[i].x) * weight; double ey = (reprojected_marker.y - markers[i].y) * weight; @@ -461,14 +446,13 @@ double libmv_reprojectionErrorForTrack( } double libmv_reprojectionErrorForImage( - const libmv_Reconstruction *libmv_reconstruction, - int image) { - const EuclideanReconstruction *reconstruction = - &libmv_reconstruction->reconstruction; - const CameraIntrinsics *intrinsics = libmv_reconstruction->intrinsics; + const libmv_Reconstruction* libmv_reconstruction, int image) { + const EuclideanReconstruction* reconstruction = + &libmv_reconstruction->reconstruction; + const CameraIntrinsics* intrinsics = libmv_reconstruction->intrinsics; libmv::vector<Marker> markers = - libmv_reconstruction->tracks.MarkersInImage(image); - const EuclideanCamera *camera = reconstruction->CameraForImage(image); + libmv_reconstruction->tracks.MarkersInImage(image); + const EuclideanCamera* camera = reconstruction->CameraForImage(image); int num_reprojected = 0; double total_error = 0.0; @@ -477,8 +461,8 @@ double libmv_reprojectionErrorForImage( } for (int i = 0; i < markers.size(); ++i) { - const EuclideanPoint *point = - reconstruction->PointForTrack(markers[i].track); + const EuclideanPoint* point = + reconstruction->PointForTrack(markers[i].track); if (!point) { continue; @@ -487,7 +471,7 @@ double libmv_reprojectionErrorForImage( num_reprojected++; Marker reprojected_marker = - libmv_projectMarker(*point, *camera, *intrinsics); + libmv_projectMarker(*point, *camera, *intrinsics); double ex = (reprojected_marker.x - markers[i].x) * markers[i].weight; double ey = (reprojected_marker.y - markers[i].y) * markers[i].weight; @@ -498,13 +482,12 @@ double libmv_reprojectionErrorForImage( } int libmv_reprojectionCameraForImage( - const libmv_Reconstruction *libmv_reconstruction, + const libmv_Reconstruction* libmv_reconstruction, int image, double mat[4][4]) { - const EuclideanReconstruction *reconstruction = - &libmv_reconstruction->reconstruction; - const EuclideanCamera *camera = - reconstruction->CameraForImage(image); + const EuclideanReconstruction* reconstruction = + &libmv_reconstruction->reconstruction; + const EuclideanCamera* camera = reconstruction->CameraForImage(image); if (camera) { for (int j = 0; j < 3; ++j) { @@ -541,11 +524,11 @@ int libmv_reprojectionCameraForImage( } double libmv_reprojectionError( - const libmv_Reconstruction *libmv_reconstruction) { + const libmv_Reconstruction* libmv_reconstruction) { return libmv_reconstruction->error; } -libmv_CameraIntrinsics *libmv_reconstructionExtractIntrinsics( - libmv_Reconstruction *libmv_reconstruction) { - return (libmv_CameraIntrinsics *) libmv_reconstruction->intrinsics; +libmv_CameraIntrinsics* libmv_reconstructionExtractIntrinsics( + libmv_Reconstruction* libmv_reconstruction) { + return (libmv_CameraIntrinsics*)libmv_reconstruction->intrinsics; } diff --git a/intern/libmv/intern/reconstruction.h b/intern/libmv/intern/reconstruction.h index 408ac884684..600bc92ccfc 100644 --- a/intern/libmv/intern/reconstruction.h +++ b/intern/libmv/intern/reconstruction.h @@ -31,17 +31,16 @@ struct libmv_CameraIntrinsicsOptions; typedef struct libmv_Reconstruction libmv_Reconstruction; enum { - LIBMV_REFINE_FOCAL_LENGTH = (1 << 0), - LIBMV_REFINE_PRINCIPAL_POINT = (1 << 1), - - LIBMV_REFINE_RADIAL_DISTORTION_K1 = (1 << 2), - LIBMV_REFINE_RADIAL_DISTORTION_K2 = (1 << 3), - LIBMV_REFINE_RADIAL_DISTORTION_K3 = (1 << 4), - LIBMV_REFINE_RADIAL_DISTORTION_K4 = (1 << 5), - LIBMV_REFINE_RADIAL_DISTORTION = (LIBMV_REFINE_RADIAL_DISTORTION_K1 | - LIBMV_REFINE_RADIAL_DISTORTION_K2 | - LIBMV_REFINE_RADIAL_DISTORTION_K3 | - LIBMV_REFINE_RADIAL_DISTORTION_K4), + LIBMV_REFINE_FOCAL_LENGTH = (1 << 0), + LIBMV_REFINE_PRINCIPAL_POINT = (1 << 1), + + LIBMV_REFINE_RADIAL_DISTORTION_K1 = (1 << 2), + LIBMV_REFINE_RADIAL_DISTORTION_K2 = (1 << 3), + LIBMV_REFINE_RADIAL_DISTORTION_K3 = (1 << 4), + LIBMV_REFINE_RADIAL_DISTORTION_K4 = (1 << 5), + LIBMV_REFINE_RADIAL_DISTORTION = + (LIBMV_REFINE_RADIAL_DISTORTION_K1 | LIBMV_REFINE_RADIAL_DISTORTION_K2 | + LIBMV_REFINE_RADIAL_DISTORTION_K3 | LIBMV_REFINE_RADIAL_DISTORTION_K4), LIBMV_REFINE_TANGENTIAL_DISTORTION_P1 = (1 << 6), LIBMV_REFINE_TANGENTIAL_DISTORTION_P2 = (1 << 7), @@ -55,9 +54,9 @@ typedef struct libmv_ReconstructionOptions { int refine_intrinsics; } libmv_ReconstructionOptions; -typedef void (*reconstruct_progress_update_cb) (void* customdata, - double progress, - const char* message); +typedef void (*reconstruct_progress_update_cb)(void* customdata, + double progress, + const char* message); libmv_Reconstruction* libmv_solveReconstruction( const struct libmv_Tracks* libmv_tracks, @@ -73,35 +72,32 @@ libmv_Reconstruction* libmv_solveModal( reconstruct_progress_update_cb progress_update_callback, void* callback_customdata); -int libmv_reconstructionIsValid(libmv_Reconstruction *libmv_reconstruction); +int libmv_reconstructionIsValid(libmv_Reconstruction* libmv_reconstruction); void libmv_reconstructionDestroy(libmv_Reconstruction* libmv_reconstruction); int libmv_reprojectionPointForTrack( - const libmv_Reconstruction* libmv_reconstruction, - int track, - double pos[3]); + const libmv_Reconstruction* libmv_reconstruction, int track, double pos[3]); double libmv_reprojectionErrorForTrack( - const libmv_Reconstruction* libmv_reconstruction, - int track); + const libmv_Reconstruction* libmv_reconstruction, int track); double libmv_reprojectionErrorForImage( - const libmv_Reconstruction* libmv_reconstruction, - int image); + const libmv_Reconstruction* libmv_reconstruction, int image); int libmv_reprojectionCameraForImage( const libmv_Reconstruction* libmv_reconstruction, int image, double mat[4][4]); -double libmv_reprojectionError(const libmv_Reconstruction* libmv_reconstruction); +double libmv_reprojectionError( + const libmv_Reconstruction* libmv_reconstruction); struct libmv_CameraIntrinsics* libmv_reconstructionExtractIntrinsics( - libmv_Reconstruction *libmv_Reconstruction); + libmv_Reconstruction* libmv_Reconstruction); #ifdef __cplusplus } #endif -#endif // LIBMV_C_API_RECONSTRUCTION_H_ +#endif // LIBMV_C_API_RECONSTRUCTION_H_ diff --git a/intern/libmv/intern/stub.cc b/intern/libmv/intern/stub.cc index 47e1896b4cf..1920042b4ec 100644 --- a/intern/libmv/intern/stub.cc +++ b/intern/libmv/intern/stub.cc @@ -24,7 +24,7 @@ /* ************ Logging ************ */ -void libmv_initLogging(const char * /*argv0*/) { +void libmv_initLogging(const char* /*argv0*/) { } void libmv_startDebugLogging(void) { @@ -36,18 +36,18 @@ void libmv_setLoggingVerbosity(int /*verbosity*/) { /* ************ Planar tracker ************ */ /* TrackRegion (new planar tracker) */ -int libmv_trackRegion(const libmv_TrackRegionOptions * /*options*/, - const float * /*image1*/, +int libmv_trackRegion(const libmv_TrackRegionOptions* /*options*/, + const float* /*image1*/, int /*image1_width*/, int /*image1_height*/, - const float * /*image2*/, + const float* /*image2*/, int /*image2_width*/, int /*image2_height*/, - const double *x1, - const double *y1, - libmv_TrackRegionResult *result, - double *x2, - double *y2) { + const double* x1, + const double* y1, + libmv_TrackRegionResult* result, + double* x2, + double* y2) { /* Convert to doubles for the libmv api. The four corners and the center. */ for (int i = 0; i < 5; ++i) { x2[i] = x1[i]; @@ -61,46 +61,46 @@ int libmv_trackRegion(const libmv_TrackRegionOptions * /*options*/, return false; } -void libmv_samplePlanarPatchFloat(const float * /*image*/, +void libmv_samplePlanarPatchFloat(const float* /*image*/, int /*width*/, int /*height*/, int /*channels*/, - const double * /*xs*/, - const double * /*ys*/, + const double* /*xs*/, + const double* /*ys*/, int /*num_samples_x*/, int /*num_samples_y*/, - const float * /*mask*/, - float * /*patch*/, - double * /*warped_position_x*/, - double * /*warped_position_y*/) { + const float* /*mask*/, + float* /*patch*/, + double* /*warped_position_x*/, + double* /*warped_position_y*/) { /* TODO(sergey): implement */ } -void libmv_samplePlanarPatchByte(const unsigned char * /*image*/, +void libmv_samplePlanarPatchByte(const unsigned char* /*image*/, int /*width*/, int /*height*/, int /*channels*/, - const double * /*xs*/, - const double * /*ys*/, - int /*num_samples_x*/, int /*num_samples_y*/, - const float * /*mask*/, - unsigned char * /*patch*/, - double * /*warped_position_x*/, - double * /*warped_position_y*/) { + const double* /*xs*/, + const double* /*ys*/, + int /*num_samples_x*/, + int /*num_samples_y*/, + const float* /*mask*/, + unsigned char* /*patch*/, + double* /*warped_position_x*/, + double* /*warped_position_y*/) { /* TODO(sergey): implement */ } -void libmv_floatImageDestroy(libmv_FloatImage* /*image*/) -{ +void libmv_floatImageDestroy(libmv_FloatImage* /*image*/) { } /* ************ Tracks ************ */ -libmv_Tracks *libmv_tracksNew(void) { +libmv_Tracks* libmv_tracksNew(void) { return NULL; } -void libmv_tracksInsert(libmv_Tracks * /*libmv_tracks*/, +void libmv_tracksInsert(libmv_Tracks* /*libmv_tracks*/, int /*image*/, int /*track*/, double /*x*/, @@ -108,152 +108,152 @@ void libmv_tracksInsert(libmv_Tracks * /*libmv_tracks*/, double /*weight*/) { } -void libmv_tracksDestroy(libmv_Tracks * /*libmv_tracks*/) { +void libmv_tracksDestroy(libmv_Tracks* /*libmv_tracks*/) { } /* ************ Reconstruction solver ************ */ -libmv_Reconstruction *libmv_solveReconstruction( - const libmv_Tracks * /*libmv_tracks*/, - const libmv_CameraIntrinsicsOptions * /*libmv_camera_intrinsics_options*/, - libmv_ReconstructionOptions * /*libmv_reconstruction_options*/, +libmv_Reconstruction* libmv_solveReconstruction( + const libmv_Tracks* /*libmv_tracks*/, + const libmv_CameraIntrinsicsOptions* /*libmv_camera_intrinsics_options*/, + libmv_ReconstructionOptions* /*libmv_reconstruction_options*/, reconstruct_progress_update_cb /*progress_update_callback*/, - void * /*callback_customdata*/) { + void* /*callback_customdata*/) { return NULL; } -libmv_Reconstruction *libmv_solveModal( - const libmv_Tracks * /*libmv_tracks*/, - const libmv_CameraIntrinsicsOptions * /*libmv_camera_intrinsics_options*/, - const libmv_ReconstructionOptions * /*libmv_reconstruction_options*/, +libmv_Reconstruction* libmv_solveModal( + const libmv_Tracks* /*libmv_tracks*/, + const libmv_CameraIntrinsicsOptions* /*libmv_camera_intrinsics_options*/, + const libmv_ReconstructionOptions* /*libmv_reconstruction_options*/, reconstruct_progress_update_cb /*progress_update_callback*/, - void * /*callback_customdata*/) { + void* /*callback_customdata*/) { return NULL; } -int libmv_reconstructionIsValid(libmv_Reconstruction * /*libmv_reconstruction*/) { +int libmv_reconstructionIsValid( + libmv_Reconstruction* /*libmv_reconstruction*/) { return 0; } int libmv_reprojectionPointForTrack( - const libmv_Reconstruction * /*libmv_reconstruction*/, + const libmv_Reconstruction* /*libmv_reconstruction*/, int /*track*/, double /*pos*/[3]) { return 0; } double libmv_reprojectionErrorForTrack( - const libmv_Reconstruction * /*libmv_reconstruction*/, - int /*track*/) { + const libmv_Reconstruction* /*libmv_reconstruction*/, int /*track*/) { return 0.0; } double libmv_reprojectionErrorForImage( - const libmv_Reconstruction * /*libmv_reconstruction*/, - int /*image*/) { + const libmv_Reconstruction* /*libmv_reconstruction*/, int /*image*/) { return 0.0; } int libmv_reprojectionCameraForImage( - const libmv_Reconstruction * /*libmv_reconstruction*/, + const libmv_Reconstruction* /*libmv_reconstruction*/, int /*image*/, double /*mat*/[4][4]) { return 0; } double libmv_reprojectionError( - const libmv_Reconstruction * /*libmv_reconstruction*/) { + const libmv_Reconstruction* /*libmv_reconstruction*/) { return 0.0; } void libmv_reconstructionDestroy( - struct libmv_Reconstruction * /*libmv_reconstruction*/) { + struct libmv_Reconstruction* /*libmv_reconstruction*/) { } /* ************ Feature detector ************ */ -libmv_Features *libmv_detectFeaturesByte(const unsigned char * /*image_buffer*/, +libmv_Features* libmv_detectFeaturesByte(const unsigned char* /*image_buffer*/, int /*width*/, int /*height*/, int /*channels*/, - libmv_DetectOptions * /*options*/) { + libmv_DetectOptions* /*options*/) { return NULL; } -struct libmv_Features *libmv_detectFeaturesFloat( - const float * /*image_buffer*/, +struct libmv_Features* libmv_detectFeaturesFloat( + const float* /*image_buffer*/, int /*width*/, int /*height*/, int /*channels*/, - libmv_DetectOptions * /*options*/) { + libmv_DetectOptions* /*options*/) { return NULL; } -int libmv_countFeatures(const libmv_Features * /*libmv_features*/) { +int libmv_countFeatures(const libmv_Features* /*libmv_features*/) { return 0; } -void libmv_getFeature(const libmv_Features * /*libmv_features*/, +void libmv_getFeature(const libmv_Features* /*libmv_features*/, int /*number*/, - double *x, - double *y, - double *score, - double *size) { + double* x, + double* y, + double* score, + double* size) { *x = 0.0; *y = 0.0; *score = 0.0; *size = 0.0; } -void libmv_featuresDestroy(struct libmv_Features * /*libmv_features*/) { +void libmv_featuresDestroy(struct libmv_Features* /*libmv_features*/) { } /* ************ Camera intrinsics ************ */ -libmv_CameraIntrinsics *libmv_reconstructionExtractIntrinsics( - libmv_Reconstruction * /*libmv_reconstruction*/) { +libmv_CameraIntrinsics* libmv_reconstructionExtractIntrinsics( + libmv_Reconstruction* /*libmv_reconstruction*/) { return NULL; } -libmv_CameraIntrinsics *libmv_cameraIntrinsicsNew( - const libmv_CameraIntrinsicsOptions * /*libmv_camera_intrinsics_options*/) { +libmv_CameraIntrinsics* libmv_cameraIntrinsicsNew( + const libmv_CameraIntrinsicsOptions* /*libmv_camera_intrinsics_options*/) { return NULL; } -libmv_CameraIntrinsics *libmv_cameraIntrinsicsCopy( - const libmv_CameraIntrinsics * /*libmvIntrinsics*/) { +libmv_CameraIntrinsics* libmv_cameraIntrinsicsCopy( + const libmv_CameraIntrinsics* /*libmvIntrinsics*/) { return NULL; } void libmv_cameraIntrinsicsDestroy( - libmv_CameraIntrinsics * /*libmvIntrinsics*/) { + libmv_CameraIntrinsics* /*libmvIntrinsics*/) { } void libmv_cameraIntrinsicsUpdate( - const libmv_CameraIntrinsicsOptions * /*libmv_camera_intrinsics_options*/, - libmv_CameraIntrinsics * /*libmv_intrinsics*/) { + const libmv_CameraIntrinsicsOptions* /*libmv_camera_intrinsics_options*/, + libmv_CameraIntrinsics* /*libmv_intrinsics*/) { } void libmv_cameraIntrinsicsSetThreads( - libmv_CameraIntrinsics * /*libmv_intrinsics*/, - int /*threads*/) { + libmv_CameraIntrinsics* /*libmv_intrinsics*/, int /*threads*/) { } void libmv_cameraIntrinsicsExtractOptions( - const libmv_CameraIntrinsics * /*libmv_intrinsics*/, - libmv_CameraIntrinsicsOptions *camera_intrinsics_options) { + const libmv_CameraIntrinsics* /*libmv_intrinsics*/, + libmv_CameraIntrinsicsOptions* camera_intrinsics_options) { memset(camera_intrinsics_options, 0, sizeof(libmv_CameraIntrinsicsOptions)); camera_intrinsics_options->focal_length = 1.0; } void libmv_cameraIntrinsicsUndistortByte( - const libmv_CameraIntrinsics * /*libmv_intrinsics*/, - const unsigned char *source_image, - int width, int height, + const libmv_CameraIntrinsics* /*libmv_intrinsics*/, + const unsigned char* source_image, + int width, + int height, float /*overscan*/, int channels, - unsigned char *destination_image) { - memcpy(destination_image, source_image, + unsigned char* destination_image) { + memcpy(destination_image, + source_image, channels * width * height * sizeof(unsigned char)); } @@ -265,19 +265,21 @@ void libmv_cameraIntrinsicsUndistortFloat( float /*overscan*/, int channels, float* destination_image) { - memcpy(destination_image, source_image, + memcpy(destination_image, + source_image, channels * width * height * sizeof(float)); } void libmv_cameraIntrinsicsDistortByte( const struct libmv_CameraIntrinsics* /*libmv_intrinsics*/, - const unsigned char *source_image, + const unsigned char* source_image, int width, int height, float /*overscan*/, int channels, - unsigned char *destination_image) { - memcpy(destination_image, source_image, + unsigned char* destination_image) { + memcpy(destination_image, + source_image, channels * width * height * sizeof(unsigned char)); } @@ -289,7 +291,8 @@ void libmv_cameraIntrinsicsDistortFloat( float /*overscan*/, int channels, float* destination_image) { - memcpy(destination_image, source_image, + memcpy(destination_image, + source_image, channels * width * height * sizeof(float)); } @@ -315,8 +318,8 @@ void libmv_cameraIntrinsicsInvert( *y1 = 0.0; } -void libmv_homography2DFromCorrespondencesEuc(/* const */ double (* /*x1*/)[2], - /* const */ double (* /*x2*/)[2], +void libmv_homography2DFromCorrespondencesEuc(/* const */ double (*/*x1*/)[2], + /* const */ double (*/*x2*/)[2], int /*num_points*/, double H[3][3]) { memset(H, 0, sizeof(double[3][3])); @@ -327,45 +330,38 @@ void libmv_homography2DFromCorrespondencesEuc(/* const */ double (* /*x1*/)[2], /* ************ autotrack ************ */ -libmv_AutoTrack* libmv_autoTrackNew(libmv_FrameAccessor* /*frame_accessor*/) -{ +libmv_AutoTrack* libmv_autoTrackNew(libmv_FrameAccessor* /*frame_accessor*/) { return NULL; } -void libmv_autoTrackDestroy(libmv_AutoTrack* /*libmv_autotrack*/) -{ +void libmv_autoTrackDestroy(libmv_AutoTrack* /*libmv_autotrack*/) { } void libmv_autoTrackSetOptions(libmv_AutoTrack* /*libmv_autotrack*/, - const libmv_AutoTrackOptions* /*options*/) -{ + const libmv_AutoTrackOptions* /*options*/) { } int libmv_autoTrackMarker(libmv_AutoTrack* /*libmv_autotrack*/, const libmv_TrackRegionOptions* /*libmv_options*/, - libmv_Marker * /*libmv_tracker_marker*/, - libmv_TrackRegionResult* /*libmv_result*/) -{ + libmv_Marker* /*libmv_tracker_marker*/, + libmv_TrackRegionResult* /*libmv_result*/) { return 0; } void libmv_autoTrackAddMarker(libmv_AutoTrack* /*libmv_autotrack*/, - const libmv_Marker* /*libmv_marker*/) -{ + const libmv_Marker* /*libmv_marker*/) { } void libmv_autoTrackSetMarkers(libmv_AutoTrack* /*libmv_autotrack*/, const libmv_Marker* /*libmv_marker-*/, - size_t /*num_markers*/) -{ + size_t /*num_markers*/) { } int libmv_autoTrackGetMarker(libmv_AutoTrack* /*libmv_autotrack*/, int /*clip*/, int /*frame*/, int /*track*/, - libmv_Marker* /*libmv_marker*/) -{ + libmv_Marker* /*libmv_marker*/) { return 0; } @@ -376,24 +372,20 @@ libmv_FrameAccessor* libmv_FrameAccessorNew( libmv_GetImageCallback /*get_image_callback*/, libmv_ReleaseImageCallback /*release_image_callback*/, libmv_GetMaskForTrackCallback /*get_mask_for_track_callback*/, - libmv_ReleaseMaskCallback /*release_mask_callback*/) -{ + libmv_ReleaseMaskCallback /*release_mask_callback*/) { return NULL; } -void libmv_FrameAccessorDestroy(libmv_FrameAccessor* /*frame_accessor*/) -{ +void libmv_FrameAccessorDestroy(libmv_FrameAccessor* /*frame_accessor*/) { } int64_t libmv_frameAccessorgetTransformKey( - const libmv_FrameTransform * /*transform*/) -{ + const libmv_FrameTransform* /*transform*/) { return 0; } -void libmv_frameAccessorgetTransformRun(const libmv_FrameTransform* /*transform*/, - const libmv_FloatImage* /*input_image*/, - libmv_FloatImage* /*output_image*/) -{ +void libmv_frameAccessorgetTransformRun( + const libmv_FrameTransform* /*transform*/, + const libmv_FloatImage* /*input_image*/, + libmv_FloatImage* /*output_image*/) { } - diff --git a/intern/libmv/intern/track_region.cc b/intern/libmv/intern/track_region.cc index 2a3909c0ced..af88afd7ac2 100644 --- a/intern/libmv/intern/track_region.cc +++ b/intern/libmv/intern/track_region.cc @@ -32,17 +32,17 @@ #undef DUMP_ALWAYS using libmv::FloatImage; +using libmv::TrackRegion; using libmv::TrackRegionOptions; using libmv::TrackRegionResult; -using libmv::TrackRegion; void libmv_configureTrackRegionOptions( const libmv_TrackRegionOptions& options, TrackRegionOptions* track_region_options) { switch (options.motion_model) { -#define LIBMV_CONVERT(the_model) \ - case TrackRegionOptions::the_model: \ - track_region_options->mode = TrackRegionOptions::the_model; \ +#define LIBMV_CONVERT(the_model) \ + case TrackRegionOptions::the_model: \ + track_region_options->mode = TrackRegionOptions::the_model; \ break; LIBMV_CONVERT(TRANSLATION) LIBMV_CONVERT(TRANSLATION_ROTATION) @@ -66,7 +66,8 @@ void libmv_configureTrackRegionOptions( * so disabling for now for until proper prediction model is landed. * * The thing is, currently blender sends input coordinates as the guess to - * region tracker and in case of fast motion such an early out ruins the track. + * region tracker and in case of fast motion such an early out ruins the + * track. */ track_region_options->attempt_refine_before_brute = false; track_region_options->use_normalized_intensities = options.use_normalization; @@ -74,7 +75,7 @@ void libmv_configureTrackRegionOptions( void libmv_regionTrackergetResult(const TrackRegionResult& track_region_result, libmv_TrackRegionResult* result) { - result->termination = (int) track_region_result.termination; + result->termination = (int)track_region_result.termination; result->termination_reason = ""; result->correlation = track_region_result.correlation; } @@ -108,33 +109,27 @@ int libmv_trackRegion(const libmv_TrackRegionOptions* options, libmv_configureTrackRegionOptions(*options, &track_region_options); if (options->image1_mask) { - libmv_floatBufferToFloatImage(options->image1_mask, - image1_width, - image1_height, - 1, - &image1_mask); + libmv_floatBufferToFloatImage( + options->image1_mask, image1_width, image1_height, 1, &image1_mask); track_region_options.image1_mask = &image1_mask; } // Convert from raw float buffers to libmv's FloatImage. FloatImage old_patch, new_patch; - libmv_floatBufferToFloatImage(image1, - image1_width, - image1_height, - 1, - &old_patch); - libmv_floatBufferToFloatImage(image2, - image2_width, - image2_height, - 1, - &new_patch); + libmv_floatBufferToFloatImage( + image1, image1_width, image1_height, 1, &old_patch); + libmv_floatBufferToFloatImage( + image2, image2_width, image2_height, 1, &new_patch); TrackRegionResult track_region_result; - TrackRegion(old_patch, new_patch, - xx1, yy1, + TrackRegion(old_patch, + new_patch, + xx1, + yy1, track_region_options, - xx2, yy2, + xx2, + yy2, &track_region_result); // Convert to floats for the blender api. diff --git a/intern/libmv/intern/track_region.h b/intern/libmv/intern/track_region.h index 48ae97a1c1a..4566fe9bf0f 100644 --- a/intern/libmv/intern/track_region.h +++ b/intern/libmv/intern/track_region.h @@ -31,7 +31,7 @@ typedef struct libmv_TrackRegionOptions { int use_normalization; double minimum_correlation; double sigma; - float *image1_mask; + float* image1_mask; } libmv_TrackRegionOptions; typedef struct libmv_TrackRegionResult { @@ -42,9 +42,9 @@ typedef struct libmv_TrackRegionResult { #ifdef __cplusplus namespace libmv { - struct TrackRegionOptions; - struct TrackRegionResult; -} +struct TrackRegionOptions; +struct TrackRegionResult; +} // namespace libmv void libmv_configureTrackRegionOptions( const libmv_TrackRegionOptions& options, libmv::TrackRegionOptions* track_region_options); diff --git a/intern/libmv/intern/tracks.cc b/intern/libmv/intern/tracks.cc index 0ca5a31796b..146908d6db5 100644 --- a/intern/libmv/intern/tracks.cc +++ b/intern/libmv/intern/tracks.cc @@ -28,18 +28,18 @@ using libmv::Tracks; libmv_Tracks* libmv_tracksNew(void) { Tracks* tracks = LIBMV_OBJECT_NEW(Tracks); - return (libmv_Tracks*) tracks; + return (libmv_Tracks*)tracks; } void libmv_tracksDestroy(libmv_Tracks* libmv_tracks) { LIBMV_OBJECT_DELETE(libmv_tracks, Tracks); } -void libmv_tracksInsert(libmv_Tracks *libmv_tracks, +void libmv_tracksInsert(libmv_Tracks* libmv_tracks, int image, int track, double x, double y, double weight) { - ((Tracks *) libmv_tracks)->Insert(image, track, x, y, weight); + ((Tracks*)libmv_tracks)->Insert(image, track, x, y, weight); } diff --git a/intern/libmv/intern/tracksN.cc b/intern/libmv/intern/tracksN.cc index 1441d8a2066..c7ffb13a386 100644 --- a/intern/libmv/intern/tracksN.cc +++ b/intern/libmv/intern/tracksN.cc @@ -25,8 +25,7 @@ using mv::Marker; using mv::Tracks; -void libmv_apiMarkerToMarker(const libmv_Marker& libmv_marker, - Marker *marker) { +void libmv_apiMarkerToMarker(const libmv_Marker& libmv_marker, Marker* marker) { marker->clip = libmv_marker.clip; marker->frame = libmv_marker.frame; marker->track = libmv_marker.track; @@ -41,17 +40,16 @@ void libmv_apiMarkerToMarker(const libmv_Marker& libmv_marker, marker->search_region.max(0) = libmv_marker.search_region_max[0]; marker->search_region.max(1) = libmv_marker.search_region_max[1]; marker->weight = libmv_marker.weight; - marker->source = (Marker::Source) libmv_marker.source; - marker->status = (Marker::Status) libmv_marker.status; + marker->source = (Marker::Source)libmv_marker.source; + marker->status = (Marker::Status)libmv_marker.status; marker->reference_clip = libmv_marker.reference_clip; marker->reference_frame = libmv_marker.reference_frame; - marker->model_type = (Marker::ModelType) libmv_marker.model_type; + marker->model_type = (Marker::ModelType)libmv_marker.model_type; marker->model_id = libmv_marker.model_id; marker->disabled_channels = libmv_marker.disabled_channels; } -void libmv_markerToApiMarker(const Marker& marker, - libmv_Marker *libmv_marker) { +void libmv_markerToApiMarker(const Marker& marker, libmv_Marker* libmv_marker) { libmv_marker->clip = marker.clip; libmv_marker->frame = marker.frame; libmv_marker->track = marker.track; @@ -66,11 +64,11 @@ void libmv_markerToApiMarker(const Marker& marker, libmv_marker->search_region_max[0] = marker.search_region.max(0); libmv_marker->search_region_max[1] = marker.search_region.max(1); libmv_marker->weight = marker.weight; - libmv_marker->source = (libmv_MarkerSource) marker.source; - libmv_marker->status = (libmv_MarkerStatus) marker.status; + libmv_marker->source = (libmv_MarkerSource)marker.source; + libmv_marker->status = (libmv_MarkerStatus)marker.status; libmv_marker->reference_clip = marker.reference_clip; libmv_marker->reference_frame = marker.reference_frame; - libmv_marker->model_type = (libmv_MarkerModelType) marker.model_type; + libmv_marker->model_type = (libmv_MarkerModelType)marker.model_type; libmv_marker->model_id = marker.model_id; libmv_marker->disabled_channels = marker.disabled_channels; } @@ -78,7 +76,7 @@ void libmv_markerToApiMarker(const Marker& marker, libmv_TracksN* libmv_tracksNewN(void) { Tracks* tracks = LIBMV_OBJECT_NEW(Tracks); - return (libmv_TracksN*) tracks; + return (libmv_TracksN*)tracks; } void libmv_tracksDestroyN(libmv_TracksN* libmv_tracks) { @@ -89,7 +87,7 @@ void libmv_tracksAddMarkerN(libmv_TracksN* libmv_tracks, const libmv_Marker* libmv_marker) { Marker marker; libmv_apiMarkerToMarker(*libmv_marker, &marker); - ((Tracks*) libmv_tracks)->AddMarker(marker); + ((Tracks*)libmv_tracks)->AddMarker(marker); } void libmv_tracksGetMarkerN(libmv_TracksN* libmv_tracks, @@ -98,7 +96,7 @@ void libmv_tracksGetMarkerN(libmv_TracksN* libmv_tracks, int track, libmv_Marker* libmv_marker) { Marker marker; - ((Tracks*) libmv_tracks)->GetMarker(clip, frame, track, &marker); + ((Tracks*)libmv_tracks)->GetMarker(clip, frame, track, &marker); libmv_markerToApiMarker(marker, libmv_marker); } @@ -106,26 +104,25 @@ void libmv_tracksRemoveMarkerN(libmv_TracksN* libmv_tracks, int clip, int frame, int track) { - ((Tracks *) libmv_tracks)->RemoveMarker(clip, frame, track); + ((Tracks*)libmv_tracks)->RemoveMarker(clip, frame, track); } -void libmv_tracksRemoveMarkersForTrack(libmv_TracksN* libmv_tracks, - int track) { - ((Tracks *) libmv_tracks)->RemoveMarkersForTrack(track); +void libmv_tracksRemoveMarkersForTrack(libmv_TracksN* libmv_tracks, int track) { + ((Tracks*)libmv_tracks)->RemoveMarkersForTrack(track); } int libmv_tracksMaxClipN(libmv_TracksN* libmv_tracks) { - return ((Tracks*) libmv_tracks)->MaxClip(); + return ((Tracks*)libmv_tracks)->MaxClip(); } int libmv_tracksMaxFrameN(libmv_TracksN* libmv_tracks, int clip) { - return ((Tracks*) libmv_tracks)->MaxFrame(clip); + return ((Tracks*)libmv_tracks)->MaxFrame(clip); } int libmv_tracksMaxTrackN(libmv_TracksN* libmv_tracks) { - return ((Tracks*) libmv_tracks)->MaxTrack(); + return ((Tracks*)libmv_tracks)->MaxTrack(); } int libmv_tracksNumMarkersN(libmv_TracksN* libmv_tracks) { - return ((Tracks*) libmv_tracks)->NumMarkers(); + return ((Tracks*)libmv_tracks)->NumMarkers(); } diff --git a/intern/libmv/intern/tracksN.h b/intern/libmv/intern/tracksN.h index 9363d34bed7..b5d1f9753e0 100644 --- a/intern/libmv/intern/tracksN.h +++ b/intern/libmv/intern/tracksN.h @@ -79,20 +79,19 @@ typedef struct libmv_Marker { #ifdef __cplusplus namespace mv { - struct Marker; +struct Marker; } void libmv_apiMarkerToMarker(const libmv_Marker& libmv_marker, - mv::Marker *marker); + mv::Marker* marker); void libmv_markerToApiMarker(const mv::Marker& marker, - libmv_Marker *libmv_marker); + libmv_Marker* libmv_marker); #endif libmv_TracksN* libmv_tracksNewN(void); void libmv_tracksDestroyN(libmv_TracksN* libmv_tracks); - void libmv_tracksAddMarkerN(libmv_TracksN* libmv_tracks, const libmv_Marker* libmv_marker); @@ -107,8 +106,7 @@ void libmv_tracksRemoveMarkerN(libmv_TracksN* libmv_tracks, int frame, int track); -void libmv_tracksRemoveMarkersForTrack(libmv_TracksN* libmv_tracks, - int track); +void libmv_tracksRemoveMarkersForTrack(libmv_TracksN* libmv_tracks, int track); int libmv_tracksMaxClipN(libmv_TracksN* libmv_tracks); int libmv_tracksMaxFrameN(libmv_TracksN* libmv_tracks, int clip); diff --git a/intern/libmv/intern/utildefines.h b/intern/libmv/intern/utildefines.h index d76d32f9c4d..052052a1d76 100644 --- a/intern/libmv/intern/utildefines.h +++ b/intern/libmv/intern/utildefines.h @@ -30,27 +30,33 @@ # define LIBMV_OBJECT_NEW OBJECT_GUARDED_NEW # define LIBMV_OBJECT_DELETE OBJECT_GUARDED_DELETE # define LIBMV_OBJECT_DELETE OBJECT_GUARDED_DELETE -# define LIBMV_STRUCT_NEW(type, count) \ - (type*)MEM_mallocN(sizeof(type) * count, __func__) +# define LIBMV_STRUCT_NEW(type, count) \ + (type*)MEM_mallocN(sizeof(type) * count, __func__) # define LIBMV_STRUCT_DELETE(what) MEM_freeN(what) #else // Need this to keep libmv-capi potentially standalone. # if defined __GNUC__ || defined __sun -# define LIBMV_OBJECT_NEW(type, args ...) \ - new(malloc(sizeof(type))) type(args) +# define LIBMV_OBJECT_NEW(type, args...) \ + new (malloc(sizeof(type))) type(args) # else -# define LIBMV_OBJECT_NEW(type, ...) \ - new(malloc(sizeof(type))) type(__VA_ARGS__) -#endif -# define LIBMV_OBJECT_DELETE(what, type) \ - { \ - if (what) { \ - ((type*)(what))->~type(); \ - free(what); \ - } \ - } (void)0 +# define LIBMV_OBJECT_NEW(type, ...) \ + new (malloc(sizeof(type))) type(__VA_ARGS__) +# endif +# define LIBMV_OBJECT_DELETE(what, type) \ + { \ + if (what) { \ + ((type*)(what))->~type(); \ + free(what); \ + } \ + } \ + (void)0 # define LIBMV_STRUCT_NEW(type, count) (type*)malloc(sizeof(type) * count) -# define LIBMV_STRUCT_DELETE(what) { if (what) free(what); } (void)0 +# define LIBMV_STRUCT_DELETE(what) \ + { \ + if (what) \ + free(what); \ + } \ + (void)0 #endif #endif // LIBMV_C_API_UTILDEFINES_H_ diff --git a/intern/libmv/libmv/autotrack/autotrack.cc b/intern/libmv/libmv/autotrack/autotrack.cc index 3b0a762178a..c18567a5f28 100644 --- a/intern/libmv/libmv/autotrack/autotrack.cc +++ b/intern/libmv/libmv/autotrack/autotrack.cc @@ -21,9 +21,9 @@ // Author: mierle@gmail.com (Keir Mierle) #include "libmv/autotrack/autotrack.h" -#include "libmv/autotrack/quad.h" #include "libmv/autotrack/frame_accessor.h" #include "libmv/autotrack/predict_tracks.h" +#include "libmv/autotrack/quad.h" #include "libmv/base/scoped_ptr.h" #include "libmv/logging/logging.h" #include "libmv/numeric/numeric.h" @@ -35,34 +35,30 @@ namespace { class DisableChannelsTransform : public FrameAccessor::Transform { public: DisableChannelsTransform(int disabled_channels) - : disabled_channels_(disabled_channels) { } + : disabled_channels_(disabled_channels) {} - int64_t key() const { - return disabled_channels_; - } + int64_t key() const { return disabled_channels_; } void run(const FloatImage& input, FloatImage* output) const { - bool disable_red = (disabled_channels_ & Marker::CHANNEL_R) != 0, + bool disable_red = (disabled_channels_ & Marker::CHANNEL_R) != 0, disable_green = (disabled_channels_ & Marker::CHANNEL_G) != 0, - disable_blue = (disabled_channels_ & Marker::CHANNEL_B) != 0; + disable_blue = (disabled_channels_ & Marker::CHANNEL_B) != 0; - LG << "Disabling channels: " - << (disable_red ? "R " : "") - << (disable_green ? "G " : "") - << (disable_blue ? "B" : ""); + LG << "Disabling channels: " << (disable_red ? "R " : "") + << (disable_green ? "G " : "") << (disable_blue ? "B" : ""); // It's important to rescale the resultappropriately so that e.g. if only // blue is selected, it's not zeroed out. - float scale = (disable_red ? 0.0f : 0.2126f) + + float scale = (disable_red ? 0.0f : 0.2126f) + (disable_green ? 0.0f : 0.7152f) + - (disable_blue ? 0.0f : 0.0722f); + (disable_blue ? 0.0f : 0.0722f); output->Resize(input.Height(), input.Width(), 1); for (int y = 0; y < input.Height(); y++) { for (int x = 0; x < input.Width(); x++) { - float r = disable_red ? 0.0f : input(y, x, 0); + float r = disable_red ? 0.0f : input(y, x, 0); float g = disable_green ? 0.0f : input(y, x, 1); - float b = disable_blue ? 0.0f : input(y, x, 2); + float b = disable_blue ? 0.0f : input(y, x, 2); (*output)(y, x, 0) = (0.2126f * r + 0.7152f * g + 0.0722f * b) / scale; } } @@ -73,7 +69,7 @@ class DisableChannelsTransform : public FrameAccessor::Transform { int disabled_channels_; }; -template<typename QuadT, typename ArrayT> +template <typename QuadT, typename ArrayT> void QuadToArrays(const QuadT& quad, ArrayT* x, ArrayT* y) { for (int i = 0; i < 4; ++i) { x[i] = quad.coordinates(i, 0); @@ -115,11 +111,8 @@ FrameAccessor::Key GetMaskForMarker(const Marker& marker, FrameAccessor* frame_accessor, FloatImage* mask) { Region region = marker.search_region.Rounded(); - return frame_accessor->GetMaskForTrack(marker.clip, - marker.frame, - marker.track, - ®ion, - mask); + return frame_accessor->GetMaskForTrack( + marker.clip, marker.frame, marker.track, ®ion, mask); } } // namespace @@ -152,23 +145,20 @@ bool AutoTrack::TrackMarker(Marker* tracked_marker, // TODO(keir): Technically this could take a smaller slice from the source // image instead of taking one the size of the search window. FloatImage reference_image; - FrameAccessor::Key reference_key = GetImageForMarker(reference_marker, - frame_accessor_, - &reference_image); + FrameAccessor::Key reference_key = + GetImageForMarker(reference_marker, frame_accessor_, &reference_image); if (!reference_key) { LG << "Couldn't get frame for reference marker: " << reference_marker; return false; } FloatImage reference_mask; - FrameAccessor::Key reference_mask_key = GetMaskForMarker(reference_marker, - frame_accessor_, - &reference_mask); + FrameAccessor::Key reference_mask_key = + GetMaskForMarker(reference_marker, frame_accessor_, &reference_mask); FloatImage tracked_image; - FrameAccessor::Key tracked_key = GetImageForMarker(*tracked_marker, - frame_accessor_, - &tracked_image); + FrameAccessor::Key tracked_key = + GetImageForMarker(*tracked_marker, frame_accessor_, &tracked_image); if (!tracked_key) { frame_accessor_->ReleaseImage(reference_key); LG << "Couldn't get frame for tracked marker: " << tracked_marker; @@ -191,9 +181,11 @@ bool AutoTrack::TrackMarker(Marker* tracked_marker, local_track_region_options.attempt_refine_before_brute = predicted_position; TrackRegion(reference_image, tracked_image, - x1, y1, + x1, + y1, local_track_region_options, - x2, y2, + x2, + y2, result); // Copy results over the tracked marker. @@ -208,7 +200,7 @@ bool AutoTrack::TrackMarker(Marker* tracked_marker, tracked_marker->search_region.Offset(delta); tracked_marker->source = Marker::TRACKED; tracked_marker->status = Marker::UNKNOWN; - tracked_marker->reference_clip = reference_marker.clip; + tracked_marker->reference_clip = reference_marker.clip; tracked_marker->reference_frame = reference_marker.frame; // Release the images and masks from the accessor cache. @@ -230,7 +222,9 @@ void AutoTrack::SetMarkers(vector<Marker>* markers) { tracks_.SetMarkers(markers); } -bool AutoTrack::GetMarker(int clip, int frame, int track, +bool AutoTrack::GetMarker(int clip, + int frame, + int track, Marker* markers) const { return tracks_.GetMarker(clip, frame, track, markers); } @@ -242,7 +236,8 @@ void AutoTrack::DetectAndTrack(const DetectAndTrackOptions& options) { vector<Marker> previous_frame_markers; // Q: How to decide track #s when detecting? // Q: How to match markers from previous frame? set of prev frame tracks? - // Q: How to decide what markers should get tracked and which ones should not? + // Q: How to decide what markers should get tracked and which ones should + // not? for (int frame = 0; frame < num_frames; ++frame) { if (Cancelled()) { LG << "Got cancel message while detecting and tracking..."; @@ -271,8 +266,7 @@ void AutoTrack::DetectAndTrack(const DetectAndTrackOptions& options) { for (int i = 0; i < this_frame_markers.size(); ++i) { tracks_in_this_frame.push_back(this_frame_markers[i].track); } - std::sort(tracks_in_this_frame.begin(), - tracks_in_this_frame.end()); + std::sort(tracks_in_this_frame.begin(), tracks_in_this_frame.end()); // Find tracks in the previous frame that are not in this one. vector<Marker*> previous_frame_markers_to_track; diff --git a/intern/libmv/libmv/autotrack/autotrack.h b/intern/libmv/libmv/autotrack/autotrack.h index 1d7422f54e7..281766f600f 100644 --- a/intern/libmv/libmv/autotrack/autotrack.h +++ b/intern/libmv/libmv/autotrack/autotrack.h @@ -23,8 +23,8 @@ #ifndef LIBMV_AUTOTRACK_AUTOTRACK_H_ #define LIBMV_AUTOTRACK_AUTOTRACK_H_ -#include "libmv/autotrack/tracks.h" #include "libmv/autotrack/region.h" +#include "libmv/autotrack/tracks.h" #include "libmv/tracking/track_region.h" namespace libmv { @@ -74,15 +74,14 @@ class AutoTrack { Region search_region; }; - AutoTrack(FrameAccessor* frame_accessor) - : frame_accessor_(frame_accessor) {} + AutoTrack(FrameAccessor* frame_accessor) : frame_accessor_(frame_accessor) {} // Marker manipulation. // Clip manipulation. // Set the number of clips. These clips will get accessed from the frame // accessor, matches between frames found, and a reconstruction created. - //void SetNumFrames(int clip, int num_frames); + // void SetNumFrames(int clip, int num_frames); // Tracking & Matching @@ -90,7 +89,7 @@ class AutoTrack { // Caller maintains ownership of *result and *tracked_marker. bool TrackMarker(Marker* tracked_marker, TrackRegionResult* result, - const TrackRegionOptions* track_options=NULL); + const TrackRegionOptions* track_options = NULL); // Wrapper around Tracks API; however these may add additional processing. void AddMarker(const Marker& tracked_marker); @@ -99,36 +98,36 @@ class AutoTrack { // TODO(keir): Implement frame matching! This could be very cool for loop // closing and connecting across clips. - //void MatchFrames(int clip1, int frame1, int clip2, int frame2) {} + // void MatchFrames(int clip1, int frame1, int clip2, int frame2) {} // Wrapper around the Reconstruction API. // Returns the new ID. int AddCameraIntrinsics(CameraIntrinsics* intrinsics) { - (void) intrinsics; + (void)intrinsics; return 0; } // XXX int SetClipIntrinsics(int clip, int intrinsics) { - (void) clip; - (void) intrinsics; + (void)clip; + (void)intrinsics; return 0; - } // XXX + } // XXX enum Motion { GENERAL_CAMERA_MOTION, TRIPOD_CAMERA_MOTION, }; int SetClipMotion(int clip, Motion motion) { - (void) clip; - (void) motion; + (void)clip; + (void)motion; return 0; - } // XXX + } // XXX // Decide what to refine for the given intrinsics. bundle_options is from // bundle.h (e.g. BUNDLE_FOCAL_LENGTH | BUNDLE_RADIAL_K1). void SetIntrinsicsRefine(int intrinsics, int bundle_options) { - (void) intrinsics; - (void) bundle_options; - } // XXX + (void)intrinsics; + (void)bundle_options; + } // XXX // Keyframe read/write. struct ClipFrame { @@ -150,20 +149,19 @@ class AutoTrack { }; void DetectAndTrack(const DetectAndTrackOptions& options); - struct DetectFeaturesInFrameOptions { - }; - void DetectFeaturesInFrame(int clip, int frame, - const DetectFeaturesInFrameOptions* options=NULL) { - (void) clip; - (void) frame; - (void) options; - } // XXX + struct DetectFeaturesInFrameOptions {}; + void DetectFeaturesInFrame( + int clip, int frame, const DetectFeaturesInFrameOptions* options = NULL) { + (void)clip; + (void)frame; + (void)options; + } // XXX // Does not take ownership of the given listener, but keeps a reference to it. - void AddListener(OperationListener* listener) {(void) listener;} // XXX + void AddListener(OperationListener* listener) { (void)listener; } // XXX // Create the initial reconstruction, - //void FindInitialReconstruction(); + // void FindInitialReconstruction(); // State machine // @@ -202,17 +200,17 @@ class AutoTrack { bool Cancelled() { return false; } Tracks tracks_; // May be normalized camera coordinates or raw pixels. - //Reconstruction reconstruction_; + // Reconstruction reconstruction_; // TODO(keir): Add the motion models here. - //vector<MotionModel> motion_models_; + // vector<MotionModel> motion_models_; // TODO(keir): Should num_clips and num_frames get moved to FrameAccessor? // TODO(keir): What about masking for clips and frames to prevent various // things like reconstruction or tracking from happening on certain frames? FrameAccessor* frame_accessor_; - //int num_clips_; - //vector<int> num_frames_; // Indexed by clip. + // int num_clips_; + // vector<int> num_frames_; // Indexed by clip. // The intrinsics for each clip, assuming each clip has fixed intrinsics. // TODO(keir): Decide what the semantics should be for varying focal length. diff --git a/intern/libmv/libmv/autotrack/frame_accessor.h b/intern/libmv/libmv/autotrack/frame_accessor.h index cfad9ca71ff..e9308dc400a 100644 --- a/intern/libmv/libmv/autotrack/frame_accessor.h +++ b/intern/libmv/libmv/autotrack/frame_accessor.h @@ -41,7 +41,7 @@ using libmv::FloatImage; // implementations to cache filtered image pieces). struct FrameAccessor { struct Transform { - virtual ~Transform() { } + virtual ~Transform() {} // The key should depend on the transform arguments. Must be non-zero. virtual int64_t key() const = 0; @@ -50,10 +50,7 @@ struct FrameAccessor { virtual void run(const FloatImage& input, FloatImage* output) const = 0; }; - enum InputMode { - MONO, - RGBA - }; + enum InputMode { MONO, RGBA }; typedef void* Key; @@ -100,6 +97,6 @@ struct FrameAccessor { virtual int NumFrames(int clip) = 0; }; -} // namespace libmv +} // namespace mv #endif // LIBMV_AUTOTRACK_FRAME_ACCESSOR_H_ diff --git a/intern/libmv/libmv/autotrack/marker.h b/intern/libmv/libmv/autotrack/marker.h index bb803313af8..29e163c0446 100644 --- a/intern/libmv/libmv/autotrack/marker.h +++ b/intern/libmv/libmv/autotrack/marker.h @@ -57,23 +57,19 @@ struct Marker { float weight; enum Source { - MANUAL, // The user placed this marker manually. - DETECTED, // A keypoint detector found this point. - TRACKED, // The tracking algorithm placed this marker. - MATCHED, // A matching algorithm (e.g. SIFT or SURF or ORB) found this. - PREDICTED, // A motion model predicted this marker. This is needed for - // handling occlusions in some cases where an imaginary marker - // is placed to keep camera motion smooth. + MANUAL, // The user placed this marker manually. + DETECTED, // A keypoint detector found this point. + TRACKED, // The tracking algorithm placed this marker. + MATCHED, // A matching algorithm (e.g. SIFT or SURF or ORB) found this. + PREDICTED, // A motion model predicted this marker. This is needed for + // handling occlusions in some cases where an imaginary marker + // is placed to keep camera motion smooth. }; Source source; // Markers may be inliers or outliers if the tracking fails; this allows // visualizing the markers in the image. - enum Status { - UNKNOWN, - INLIER, - OUTLIER - }; + enum Status { UNKNOWN, INLIER, OUTLIER }; Status status; // When doing correlation tracking, where to search in the current frame for @@ -90,12 +86,7 @@ struct Marker { // another primitive (a rectangular prisim). This captures the information // needed to say that for example a collection of markers belongs to model #2 // (and model #2 is a plane). - enum ModelType { - POINT, - PLANE, - LINE, - CUBE - }; + enum ModelType { POINT, PLANE, LINE, CUBE }; ModelType model_type; // The model ID this track (e.g. the second model, which is a plane). @@ -114,7 +105,7 @@ struct Marker { int disabled_channels; // Offset everything (center, patch, search) by the given delta. - template<typename T> + template <typename T> void Offset(const T& offset) { center += offset.template cast<float>(); patch.coordinates.rowwise() += offset.template cast<int>(); @@ -122,19 +113,15 @@ struct Marker { } // Shift the center to the given new position (and patch, search). - template<typename T> + template <typename T> void SetPosition(const T& new_center) { Offset(new_center - center); } }; inline std::ostream& operator<<(std::ostream& out, const Marker& marker) { - out << "{" - << marker.clip << ", " - << marker.frame << ", " - << marker.track << ", (" - << marker.center.x() << ", " - << marker.center.y() << ")" + out << "{" << marker.clip << ", " << marker.frame << ", " << marker.track + << ", (" << marker.center.x() << ", " << marker.center.y() << ")" << "}"; return out; } diff --git a/intern/libmv/libmv/autotrack/model.h b/intern/libmv/libmv/autotrack/model.h index 1165281cdac..e79d38b742b 100644 --- a/intern/libmv/libmv/autotrack/model.h +++ b/intern/libmv/libmv/autotrack/model.h @@ -23,18 +23,13 @@ #ifndef LIBMV_AUTOTRACK_MODEL_H_ #define LIBMV_AUTOTRACK_MODEL_H_ -#include "libmv/numeric/numeric.h" #include "libmv/autotrack/quad.h" +#include "libmv/numeric/numeric.h" namespace mv { struct Model { - enum ModelType { - POINT, - PLANE, - LINE, - CUBE - }; + enum ModelType { POINT, PLANE, LINE, CUBE }; // ??? }; diff --git a/intern/libmv/libmv/autotrack/predict_tracks.cc b/intern/libmv/libmv/autotrack/predict_tracks.cc index 3786c1b9a3b..d78b5b340f9 100644 --- a/intern/libmv/libmv/autotrack/predict_tracks.cc +++ b/intern/libmv/libmv/autotrack/predict_tracks.cc @@ -20,8 +20,8 @@ // // Author: mierle@gmail.com (Keir Mierle) -#include "libmv/autotrack/marker.h" #include "libmv/autotrack/predict_tracks.h" +#include "libmv/autotrack/marker.h" #include "libmv/autotrack/tracks.h" #include "libmv/base/vector.h" #include "libmv/logging/logging.h" @@ -31,8 +31,8 @@ namespace mv { namespace { -using libmv::vector; using libmv::Vec2; +using libmv::vector; // Implied time delta between steps. Set empirically by tweaking and seeing // what numbers did best at prediction. @@ -57,6 +57,8 @@ const double dt = 3.8; // For a typical system having constant velocity. This gives smooth-appearing // predictions, but they are not always as accurate. +// +// clang-format off const double velocity_state_transition_data[] = { 1, dt, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, @@ -65,10 +67,13 @@ const double velocity_state_transition_data[] = { 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1 }; +// clang-format on #if 0 // This 3rd-order system also models acceleration. This makes for "jerky" // predictions, but that tend to be more accurate. +// +// clang-format off const double acceleration_state_transition_data[] = { 1, dt, dt*dt/2, 0, 0, 0, 0, 1, dt, 0, 0, 0, @@ -77,9 +82,12 @@ const double acceleration_state_transition_data[] = { 0, 0, 0, 0, 1, dt, 0, 0, 0, 0, 0, 1 }; +// clang-format on // This system (attempts) to add an angular velocity component. However, it's // total junk. +// +// clang-format off const double angular_state_transition_data[] = { 1, dt, -dt, 0, 0, 0, // Position x 0, 1, 0, 0, 0, 0, // Velocity x @@ -88,17 +96,22 @@ const double angular_state_transition_data[] = { 0, 0, 0, 0, 1, 0, // Velocity y 0, 0, 0, 0, 0, 1 // Ignored }; +// clang-format on #endif const double* state_transition_data = velocity_state_transition_data; // Observation matrix. +// clang-format off const double observation_data[] = { 1., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0. }; +// clang-format on // Process covariance. +// +// clang-format off const double process_covariance_data[] = { 35, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0, 0, @@ -107,14 +120,19 @@ const double process_covariance_data[] = { 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 5 }; +// clang-format on // Process covariance. const double measurement_covariance_data[] = { - 0.01, 0.00, - 0.00, 0.01, + 0.01, + 0.00, + 0.00, + 0.01, }; // Initial covariance. +// +// clang-format off const double initial_covariance_data[] = { 10, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, @@ -123,6 +141,7 @@ const double initial_covariance_data[] = { 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1 }; +// clang-format on typedef mv::KalmanFilter<double, 6, 2> TrackerKalman; @@ -138,7 +157,7 @@ bool OrderByFrameLessThan(const Marker* a, const Marker* b) { } return a->clip < b->clip; } - return a->frame < b-> frame; + return a->frame < b->frame; } // Predicted must be after the previous markers (in the frame numbering sense). @@ -146,9 +165,9 @@ void RunPrediction(const vector<Marker*> previous_markers, Marker* predicted_marker) { TrackerKalman::State state; state.mean << previous_markers[0]->center.x(), 0, 0, - previous_markers[0]->center.y(), 0, 0; - state.covariance = Eigen::Matrix<double, 6, 6, Eigen::RowMajor>( - initial_covariance_data); + previous_markers[0]->center.y(), 0, 0; + state.covariance = + Eigen::Matrix<double, 6, 6, Eigen::RowMajor>(initial_covariance_data); int current_frame = previous_markers[0]->frame; int target_frame = predicted_marker->frame; @@ -159,19 +178,18 @@ void RunPrediction(const vector<Marker*> previous_markers, for (int i = 1; i < previous_markers.size(); ++i) { // Step forward predicting the state until it is on the current marker. int predictions = 0; - for (; - current_frame != previous_markers[i]->frame; + for (; current_frame != previous_markers[i]->frame; current_frame += frame_delta) { filter.Step(&state); predictions++; - LG << "Predicted point (frame " << current_frame << "): " - << state.mean(0) << ", " << state.mean(3); + LG << "Predicted point (frame " << current_frame << "): " << state.mean(0) + << ", " << state.mean(3); } // Log the error -- not actually used, but interesting. Vec2 error = previous_markers[i]->center.cast<double>() - Vec2(state.mean(0), state.mean(3)); - LG << "Prediction error for " << predictions << " steps: (" - << error.x() << ", " << error.y() << "); norm: " << error.norm(); + LG << "Prediction error for " << predictions << " steps: (" << error.x() + << ", " << error.y() << "); norm: " << error.norm(); // Now that the state is predicted in the current frame, update the state // based on the measurement from the current frame. filter.Update(previous_markers[i]->center.cast<double>(), @@ -184,8 +202,8 @@ void RunPrediction(const vector<Marker*> previous_markers, // predict until the target frame. for (; current_frame != target_frame; current_frame += frame_delta) { filter.Step(&state); - LG << "Final predicted point (frame " << current_frame << "): " - << state.mean(0) << ", " << state.mean(3); + LG << "Final predicted point (frame " << current_frame + << "): " << state.mean(0) << ", " << state.mean(3); } // The x and y positions are at 0 and 3; ignore acceleration and velocity. @@ -253,13 +271,13 @@ bool PredictMarkerPosition(const Tracks& tracks, Marker* marker) { } else if (insert_at != -1) { // Found existing marker; scan before and after it. forward_scan_begin = insert_at + 1; - forward_scan_end = markers.size() - 1;; + forward_scan_end = markers.size() - 1; backward_scan_begin = insert_at - 1; backward_scan_end = 0; } else { // Didn't find existing marker but found an insertion point. forward_scan_begin = insert_before; - forward_scan_end = markers.size() - 1;; + forward_scan_end = markers.size() - 1; backward_scan_begin = insert_before - 1; backward_scan_end = 0; } @@ -301,9 +319,8 @@ bool PredictMarkerPosition(const Tracks& tracks, Marker* marker) { return false; } LG << "Predicting backward"; - int predict_begin = - std::min(forward_scan_begin + max_frames_to_predict_from, - forward_scan_end); + int predict_begin = std::min( + forward_scan_begin + max_frames_to_predict_from, forward_scan_end); int predict_end = forward_scan_begin; vector<Marker*> previous_markers; for (int i = predict_begin; i >= predict_end; --i) { @@ -312,7 +329,6 @@ bool PredictMarkerPosition(const Tracks& tracks, Marker* marker) { RunPrediction(previous_markers, marker); return false; } - } } // namespace mv diff --git a/intern/libmv/libmv/autotrack/predict_tracks_test.cc b/intern/libmv/libmv/autotrack/predict_tracks_test.cc index f7c2c68d750..fea93b91bce 100644 --- a/intern/libmv/libmv/autotrack/predict_tracks_test.cc +++ b/intern/libmv/libmv/autotrack/predict_tracks_test.cc @@ -35,17 +35,15 @@ static void AddMarker(int frame, float x, float y, Tracks* tracks) { marker.frame = frame; marker.center.x() = x; marker.center.y() = y; - marker.patch.coordinates << x - 1, y - 1, - x + 1, y - 1, - x + 1, y + 1, - x - 1, y + 1; + marker.patch.coordinates << x - 1, y - 1, x + 1, y - 1, x + 1, y + 1, x - 1, + y + 1; tracks->AddMarker(marker); } TEST(PredictMarkerPosition, EasyLinearMotion) { Tracks tracks; - AddMarker(0, 1.0, 0.0, &tracks); - AddMarker(1, 2.0, 5.0, &tracks); + AddMarker(0, 1.0, 0.0, &tracks); + AddMarker(1, 2.0, 5.0, &tracks); AddMarker(2, 3.0, 10.0, &tracks); AddMarker(3, 4.0, 15.0, &tracks); AddMarker(4, 5.0, 20.0, &tracks); @@ -66,10 +64,8 @@ TEST(PredictMarkerPosition, EasyLinearMotion) { // Check the patch coordinates as well. double x = 9, y = 40.0; Quad2Df expected_patch; - expected_patch.coordinates << x - 1, y - 1, - x + 1, y - 1, - x + 1, y + 1, - x - 1, y + 1; + expected_patch.coordinates << x - 1, y - 1, x + 1, y - 1, x + 1, y + 1, x - 1, + y + 1; error = (expected_patch.coordinates - predicted.patch.coordinates).norm(); LG << "Patch error: " << error; @@ -78,8 +74,8 @@ TEST(PredictMarkerPosition, EasyLinearMotion) { TEST(PredictMarkerPosition, EasyBackwardLinearMotion) { Tracks tracks; - AddMarker(8, 1.0, 0.0, &tracks); - AddMarker(7, 2.0, 5.0, &tracks); + AddMarker(8, 1.0, 0.0, &tracks); + AddMarker(7, 2.0, 5.0, &tracks); AddMarker(6, 3.0, 10.0, &tracks); AddMarker(5, 4.0, 15.0, &tracks); AddMarker(4, 5.0, 20.0, &tracks); @@ -101,10 +97,8 @@ TEST(PredictMarkerPosition, EasyBackwardLinearMotion) { // Check the patch coordinates as well. double x = 9.0, y = 40.0; Quad2Df expected_patch; - expected_patch.coordinates << x - 1, y - 1, - x + 1, y - 1, - x + 1, y + 1, - x - 1, y + 1; + expected_patch.coordinates << x - 1, y - 1, x + 1, y - 1, x + 1, y + 1, x - 1, + y + 1; error = (expected_patch.coordinates - predicted.patch.coordinates).norm(); LG << "Patch error: " << error; @@ -113,8 +107,8 @@ TEST(PredictMarkerPosition, EasyBackwardLinearMotion) { TEST(PredictMarkerPosition, TwoFrameGap) { Tracks tracks; - AddMarker(0, 1.0, 0.0, &tracks); - AddMarker(1, 2.0, 5.0, &tracks); + AddMarker(0, 1.0, 0.0, &tracks); + AddMarker(1, 2.0, 5.0, &tracks); AddMarker(2, 3.0, 10.0, &tracks); AddMarker(3, 4.0, 15.0, &tracks); AddMarker(4, 5.0, 20.0, &tracks); @@ -135,8 +129,8 @@ TEST(PredictMarkerPosition, TwoFrameGap) { TEST(PredictMarkerPosition, FourFrameGap) { Tracks tracks; - AddMarker(0, 1.0, 0.0, &tracks); - AddMarker(1, 2.0, 5.0, &tracks); + AddMarker(0, 1.0, 0.0, &tracks); + AddMarker(1, 2.0, 5.0, &tracks); AddMarker(2, 3.0, 10.0, &tracks); AddMarker(3, 4.0, 15.0, &tracks); // Missing frames 4, 5, 6, 7. @@ -154,13 +148,13 @@ TEST(PredictMarkerPosition, FourFrameGap) { TEST(PredictMarkerPosition, MultipleGaps) { Tracks tracks; - AddMarker(0, 1.0, 0.0, &tracks); - AddMarker(1, 2.0, 5.0, &tracks); + AddMarker(0, 1.0, 0.0, &tracks); + AddMarker(1, 2.0, 5.0, &tracks); AddMarker(2, 3.0, 10.0, &tracks); // AddMarker(3, 4.0, 15.0, &tracks); // Note the 3-frame gap. // AddMarker(4, 5.0, 20.0, &tracks); // AddMarker(5, 6.0, 25.0, &tracks); - AddMarker(6, 7.0, 30.0, &tracks); // Intermediate measurement. + AddMarker(6, 7.0, 30.0, &tracks); // Intermediate measurement. // AddMarker(7, 8.0, 35.0, &tracks); Marker predicted; @@ -178,14 +172,14 @@ TEST(PredictMarkerPosition, MarkersInRandomOrder) { Tracks tracks; // This is the same as the easy, except that the tracks are randomly ordered. - AddMarker(0, 1.0, 0.0, &tracks); + AddMarker(0, 1.0, 0.0, &tracks); AddMarker(2, 3.0, 10.0, &tracks); AddMarker(7, 8.0, 35.0, &tracks); AddMarker(5, 6.0, 25.0, &tracks); AddMarker(4, 5.0, 20.0, &tracks); AddMarker(3, 4.0, 15.0, &tracks); AddMarker(6, 7.0, 30.0, &tracks); - AddMarker(1, 2.0, 5.0, &tracks); + AddMarker(1, 2.0, 5.0, &tracks); Marker predicted; predicted.clip = 0; diff --git a/intern/libmv/libmv/autotrack/quad.h b/intern/libmv/libmv/autotrack/quad.h index 0c70f9882da..4aeb66f20f7 100644 --- a/intern/libmv/libmv/autotrack/quad.h +++ b/intern/libmv/libmv/autotrack/quad.h @@ -27,7 +27,7 @@ namespace mv { -template<typename T, int D> +template <typename T, int D> struct Quad { // A quad is 4 points; generally in 2D or 3D. // @@ -35,7 +35,7 @@ struct Quad { // |\. // | \. // | z (z goes into screen) - // | + // | // | r0----->r1 // | ^ | // | | . | @@ -44,7 +44,7 @@ struct Quad { // | \. // | \. // v normal goes away (right handed). - // y + // y // // Each row is one of the corners coordinates; either (x, y) or (x, y, z). Eigen::Matrix<T, 4, D> coordinates; diff --git a/intern/libmv/libmv/autotrack/reconstruction.h b/intern/libmv/libmv/autotrack/reconstruction.h index 732e74063f1..f993b39f79e 100644 --- a/intern/libmv/libmv/autotrack/reconstruction.h +++ b/intern/libmv/libmv/autotrack/reconstruction.h @@ -57,17 +57,17 @@ class Reconstruction { public: // All methods copy their input reference or take ownership of the pointer. void AddCameraPose(const CameraPose& pose); - int AddCameraIntrinsics(CameraIntrinsics* intrinsics); - int AddPoint(const Point& point); - int AddModel(Model* model); + int AddCameraIntrinsics(CameraIntrinsics* intrinsics); + int AddPoint(const Point& point); + int AddModel(Model* model); // Returns the corresponding pose or point or NULL if missing. - CameraPose* CameraPoseForFrame(int clip, int frame); + CameraPose* CameraPoseForFrame(int clip, int frame); const CameraPose* CameraPoseForFrame(int clip, int frame) const; - Point* PointForTrack(int track); + Point* PointForTrack(int track); const Point* PointForTrack(int track) const; - const vector<vector<CameraPose> >& camera_poses() const { + const vector<vector<CameraPose>>& camera_poses() const { return camera_poses_; } diff --git a/intern/libmv/libmv/autotrack/region.h b/intern/libmv/libmv/autotrack/region.h index b35d99eb60d..687a217ab2a 100644 --- a/intern/libmv/libmv/autotrack/region.h +++ b/intern/libmv/libmv/autotrack/region.h @@ -46,7 +46,7 @@ struct Region { Vec2f min; Vec2f max; - template<typename T> + template <typename T> void Offset(const T& offset) { min += offset.template cast<float>(); max += offset.template cast<float>(); diff --git a/intern/libmv/libmv/autotrack/tracks.cc b/intern/libmv/libmv/autotrack/tracks.cc index 174f264f3f2..8044bb28bb4 100644 --- a/intern/libmv/libmv/autotrack/tracks.cc +++ b/intern/libmv/libmv/autotrack/tracks.cc @@ -23,8 +23,8 @@ #include "libmv/autotrack/tracks.h" #include <algorithm> -#include <vector> #include <iterator> +#include <vector> #include "libmv/numeric/numeric.h" @@ -34,12 +34,12 @@ Tracks::Tracks(const Tracks& other) { markers_ = other.markers_; } -Tracks::Tracks(const vector<Marker>& markers) : markers_(markers) {} +Tracks::Tracks(const vector<Marker>& markers) : markers_(markers) { +} bool Tracks::GetMarker(int clip, int frame, int track, Marker* marker) const { for (int i = 0; i < markers_.size(); ++i) { - if (markers_[i].clip == clip && - markers_[i].frame == frame && + if (markers_[i].clip == clip && markers_[i].frame == frame && markers_[i].track == track) { *marker = markers_[i]; return true; @@ -60,8 +60,7 @@ void Tracks::GetMarkersForTrackInClip(int clip, int track, vector<Marker>* markers) const { for (int i = 0; i < markers_.size(); ++i) { - if (clip == markers_[i].clip && - track == markers_[i].track) { + if (clip == markers_[i].clip && track == markers_[i].track) { markers->push_back(markers_[i]); } } @@ -71,15 +70,16 @@ void Tracks::GetMarkersInFrame(int clip, int frame, vector<Marker>* markers) const { for (int i = 0; i < markers_.size(); ++i) { - if (markers_[i].clip == clip && - markers_[i].frame == frame) { + if (markers_[i].clip == clip && markers_[i].frame == frame) { markers->push_back(markers_[i]); } } } -void Tracks::GetMarkersForTracksInBothImages(int clip1, int frame1, - int clip2, int frame2, +void Tracks::GetMarkersForTracksInBothImages(int clip1, + int frame1, + int clip2, + int frame2, vector<Marker>* markers) const { std::vector<int> image1_tracks; std::vector<int> image2_tracks; @@ -99,20 +99,19 @@ void Tracks::GetMarkersForTracksInBothImages(int clip1, int frame1, std::sort(image1_tracks.begin(), image1_tracks.end()); std::sort(image2_tracks.begin(), image2_tracks.end()); std::vector<int> intersection; - std::set_intersection(image1_tracks.begin(), image1_tracks.end(), - image2_tracks.begin(), image2_tracks.end(), + std::set_intersection(image1_tracks.begin(), + image1_tracks.end(), + image2_tracks.begin(), + image2_tracks.end(), std::back_inserter(intersection)); // Scan through and get the relevant tracks from the two images. for (int i = 0; i < markers_.size(); ++i) { // Save markers that are in either frame and are in our candidate set. - if (((markers_[i].clip == clip1 && - markers_[i].frame == frame1) || - (markers_[i].clip == clip2 && - markers_[i].frame == frame2)) && - std::binary_search(intersection.begin(), - intersection.end(), - markers_[i].track)) { + if (((markers_[i].clip == clip1 && markers_[i].frame == frame1) || + (markers_[i].clip == clip2 && markers_[i].frame == frame2)) && + std::binary_search( + intersection.begin(), intersection.end(), markers_[i].track)) { markers->push_back(markers_[i]); } } @@ -122,8 +121,7 @@ void Tracks::AddMarker(const Marker& marker) { // TODO(keir): This is quadratic for repeated insertions. Fix this by adding // a smarter data structure like a set<>. for (int i = 0; i < markers_.size(); ++i) { - if (markers_[i].clip == marker.clip && - markers_[i].frame == marker.frame && + if (markers_[i].clip == marker.clip && markers_[i].frame == marker.frame && markers_[i].track == marker.track) { markers_[i] = marker; return; @@ -139,8 +137,7 @@ void Tracks::SetMarkers(vector<Marker>* markers) { bool Tracks::RemoveMarker(int clip, int frame, int track) { int size = markers_.size(); for (int i = 0; i < markers_.size(); ++i) { - if (markers_[i].clip == clip && - markers_[i].frame == frame && + if (markers_[i].clip == clip && markers_[i].frame == frame && markers_[i].track == track) { markers_[i] = markers_[size - 1]; markers_.resize(size - 1); diff --git a/intern/libmv/libmv/autotrack/tracks.h b/intern/libmv/libmv/autotrack/tracks.h index 0b7de91d211..dd11a2d6fbd 100644 --- a/intern/libmv/libmv/autotrack/tracks.h +++ b/intern/libmv/libmv/autotrack/tracks.h @@ -23,8 +23,8 @@ #ifndef LIBMV_AUTOTRACK_TRACKS_H_ #define LIBMV_AUTOTRACK_TRACKS_H_ -#include "libmv/base/vector.h" #include "libmv/autotrack/marker.h" +#include "libmv/base/vector.h" namespace mv { @@ -33,8 +33,8 @@ using libmv::vector; // The Tracks container stores correspondences between frames. class Tracks { public: - Tracks() { } - Tracks(const Tracks &other); + Tracks() {} + Tracks(const Tracks& other); // Create a tracks object with markers already initialized. Copies markers. explicit Tracks(const vector<Marker>& markers); @@ -51,8 +51,10 @@ class Tracks { // // This is not the same as the union of the markers in frame1 and // frame2; each marker is for a track that appears in both images. - void GetMarkersForTracksInBothImages(int clip1, int frame1, - int clip2, int frame2, + void GetMarkersForTracksInBothImages(int clip1, + int frame1, + int clip2, + int frame2, vector<Marker>* markers) const; void AddMarker(const Marker& marker); diff --git a/intern/libmv/libmv/autotrack/tracks_test.cc b/intern/libmv/libmv/autotrack/tracks_test.cc index 028b4a10913..eeefd3714b0 100644 --- a/intern/libmv/libmv/autotrack/tracks_test.cc +++ b/intern/libmv/libmv/autotrack/tracks_test.cc @@ -22,8 +22,8 @@ #include "libmv/autotrack/tracks.h" -#include "testing/testing.h" #include "libmv/logging/logging.h" +#include "testing/testing.h" namespace mv { diff --git a/intern/libmv/libmv/base/aligned_malloc.cc b/intern/libmv/libmv/base/aligned_malloc.cc index 5d3e05e9df9..6e327acf928 100644 --- a/intern/libmv/libmv/base/aligned_malloc.cc +++ b/intern/libmv/libmv/base/aligned_malloc.cc @@ -41,11 +41,11 @@ namespace libmv { -void *aligned_malloc(int size, int alignment) { +void* aligned_malloc(int size, int alignment) { #ifdef _WIN32 return _aligned_malloc(size, alignment); #elif defined(__FreeBSD__) || defined(__NetBSD__) || defined(__APPLE__) - void *result; + void* result; if (posix_memalign(&result, alignment, size)) { // non-zero means allocation error @@ -58,7 +58,7 @@ void *aligned_malloc(int size, int alignment) { #endif } -void aligned_free(void *ptr) { +void aligned_free(void* ptr) { #ifdef _WIN32 _aligned_free(ptr); #else diff --git a/intern/libmv/libmv/base/aligned_malloc.h b/intern/libmv/libmv/base/aligned_malloc.h index 096ff6e2d7c..25583bb6be4 100644 --- a/intern/libmv/libmv/base/aligned_malloc.h +++ b/intern/libmv/libmv/base/aligned_malloc.h @@ -24,10 +24,10 @@ namespace libmv { // Allocate block of size bytes at least aligned to a given value. -void *aligned_malloc(int size, int alignment); +void* aligned_malloc(int size, int alignment); // Free memory allocated by aligned_malloc. -void aligned_free(void *ptr); +void aligned_free(void* ptr); } // namespace libmv diff --git a/intern/libmv/libmv/base/id_generator.h b/intern/libmv/libmv/base/id_generator.h index bf1eafd218e..535c9bd7b38 100644 --- a/intern/libmv/libmv/base/id_generator.h +++ b/intern/libmv/libmv/base/id_generator.h @@ -28,6 +28,7 @@ class IdGenerator { public: IdGenerator() : next_(0) {} ID Generate() { return next_++; } + private: ID next_; }; diff --git a/intern/libmv/libmv/base/map.h b/intern/libmv/libmv/base/map.h index 88b720f17fe..a91e3561791 100644 --- a/intern/libmv/libmv/base/map.h +++ b/intern/libmv/libmv/base/map.h @@ -26,8 +26,8 @@ namespace libmv { -using std::map; using std::make_pair; +using std::map; } // namespace libmv diff --git a/intern/libmv/libmv/base/scoped_ptr.h b/intern/libmv/libmv/base/scoped_ptr.h index b9cd4854213..9bfcfe1d615 100644 --- a/intern/libmv/libmv/base/scoped_ptr.h +++ b/intern/libmv/libmv/base/scoped_ptr.h @@ -30,44 +30,44 @@ namespace libmv { * A handle for a heap-allocated resource that should be freed when it goes out * of scope. This looks similar to the one found in TR1. */ -template<typename T> +template <typename T> class scoped_ptr { public: - scoped_ptr(T *resource) : resource_(resource) {} + scoped_ptr(T* resource) : resource_(resource) {} ~scoped_ptr() { reset(0); } - T *get() const { return resource_; } - T *operator->() const { return resource_; } - T &operator*() const { return *resource_; } + T* get() const { return resource_; } + T* operator->() const { return resource_; } + T& operator*() const { return *resource_; } - void reset(T *new_resource) { + void reset(T* new_resource) { if (sizeof(T)) { delete resource_; } resource_ = new_resource; } - T *release() { - T *released_resource = resource_; + T* release() { + T* released_resource = resource_; resource_ = 0; return released_resource; } private: // No copying allowed. - T *resource_; + T* resource_; }; // Same as scoped_ptr but caller must allocate the data // with new[] and the destructor will free the memory // using delete[]. -template<typename T> +template <typename T> class scoped_array { public: - scoped_array(T *array) : array_(array) {} + scoped_array(T* array) : array_(array) {} ~scoped_array() { reset(NULL); } - T *get() const { return array_; } + T* get() const { return array_; } T& operator[](std::ptrdiff_t i) const { assert(i >= 0); @@ -75,25 +75,27 @@ class scoped_array { return array_[i]; } - void reset(T *new_array) { + void reset(T* new_array) { if (sizeof(T)) { delete array_; } array_ = new_array; } - T *release() { - T *released_array = array_; + T* release() { + T* released_array = array_; array_ = NULL; return released_array; } private: - T *array_; + T* array_; // Forbid comparison of different scoped_array types. - template <typename T2> bool operator==(scoped_array<T2> const& p2) const; - template <typename T2> bool operator!=(scoped_array<T2> const& p2) const; + template <typename T2> + bool operator==(scoped_array<T2> const& p2) const; + template <typename T2> + bool operator!=(scoped_array<T2> const& p2) const; // Disallow evil constructors scoped_array(const scoped_array&); diff --git a/intern/libmv/libmv/base/scoped_ptr_test.cc b/intern/libmv/libmv/base/scoped_ptr_test.cc index ce1d56b500a..e86af6d4516 100644 --- a/intern/libmv/libmv/base/scoped_ptr_test.cc +++ b/intern/libmv/libmv/base/scoped_ptr_test.cc @@ -25,9 +25,9 @@ namespace libmv { namespace { struct FreeMe { - FreeMe(int *freed) : freed(freed) {} + FreeMe(int* freed) : freed(freed) {} ~FreeMe() { (*freed)++; } - int *freed; + int* freed; }; TEST(ScopedPtr, NullDoesNothing) { @@ -61,8 +61,8 @@ TEST(ScopedPtr, Reset) { TEST(ScopedPtr, ReleaseAndGet) { int frees = 0; - FreeMe *allocated = new FreeMe(&frees); - FreeMe *released = NULL; + FreeMe* allocated = new FreeMe(&frees); + FreeMe* released = NULL; { scoped_ptr<FreeMe> scoped(allocated); EXPECT_EQ(0, frees); diff --git a/intern/libmv/libmv/base/vector_test.cc b/intern/libmv/libmv/base/vector_test.cc index f171e3a18b5..d31bee751cd 100644 --- a/intern/libmv/libmv/base/vector_test.cc +++ b/intern/libmv/libmv/base/vector_test.cc @@ -19,9 +19,9 @@ // IN THE SOFTWARE. #include "libmv/base/vector.h" +#include <algorithm> #include "libmv/numeric/numeric.h" #include "testing/testing.h" -#include <algorithm> namespace { using namespace libmv; @@ -62,7 +62,7 @@ int foo_destruct_calls = 0; struct Foo { public: Foo() : value(5) { foo_construct_calls++; } - ~Foo() { foo_destruct_calls++; } + ~Foo() { foo_destruct_calls++; } int value; }; @@ -150,7 +150,7 @@ TEST_F(VectorTest, CopyConstructor) { a.push_back(3); vector<int> b(a); - EXPECT_EQ(a.size(), b.size()); + EXPECT_EQ(a.size(), b.size()); for (int i = 0; i < a.size(); ++i) { EXPECT_EQ(a[i], b[i]); } @@ -164,7 +164,7 @@ TEST_F(VectorTest, OperatorEquals) { b = a; - EXPECT_EQ(a.size(), b.size()); + EXPECT_EQ(a.size(), b.size()); for (int i = 0; i < a.size(); ++i) { EXPECT_EQ(a[i], b[i]); } diff --git a/intern/libmv/libmv/base/vector_utils.h b/intern/libmv/libmv/base/vector_utils.h index c71e1bea951..5f69c03d937 100644 --- a/intern/libmv/libmv/base/vector_utils.h +++ b/intern/libmv/libmv/base/vector_utils.h @@ -18,14 +18,13 @@ // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS // IN THE SOFTWARE. - #ifndef LIBMV_BASE_VECTOR_UTILS_H_ #define LIBMV_BASE_VECTOR_UTILS_H_ /// Delete the contents of a container. template <class Array> -void DeleteElements(Array *array) { - for (int i = 0; i < array->size(); ++i) { +void DeleteElements(Array* array) { + for (int i = 0; i < array->size(); ++i) { delete (*array)[i]; } array->clear(); diff --git a/intern/libmv/libmv/image/array_nd.cc b/intern/libmv/libmv/image/array_nd.cc index 469a19aabf1..07feda33e66 100644 --- a/intern/libmv/libmv/image/array_nd.cc +++ b/intern/libmv/libmv/image/array_nd.cc @@ -18,18 +18,17 @@ // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS // IN THE SOFTWARE. -#include "libmv/image/image.h" -#include <iostream> #include <cmath> +#include <iostream> +#include "libmv/image/image.h" namespace libmv { -void FloatArrayToScaledByteArray(const Array3Df &float_array, - Array3Du *byte_array, - bool automatic_range_detection - ) { +void FloatArrayToScaledByteArray(const Array3Df& float_array, + Array3Du* byte_array, + bool automatic_range_detection) { byte_array->ResizeLike(float_array); - float minval = HUGE_VAL; + float minval = HUGE_VAL; float maxval = -HUGE_VAL; if (automatic_range_detection) { for (int i = 0; i < float_array.Height(); ++i) { @@ -54,8 +53,8 @@ void FloatArrayToScaledByteArray(const Array3Df &float_array, } } -void ByteArrayToScaledFloatArray(const Array3Du &byte_array, - Array3Df *float_array) { +void ByteArrayToScaledFloatArray(const Array3Du& byte_array, + Array3Df* float_array) { float_array->ResizeLike(byte_array); for (int i = 0; i < byte_array.Height(); ++i) { for (int j = 0; j < byte_array.Width(); ++j) { @@ -66,10 +65,10 @@ void ByteArrayToScaledFloatArray(const Array3Du &byte_array, } } -void SplitChannels(const Array3Df &input, - Array3Df *channel0, - Array3Df *channel1, - Array3Df *channel2) { +void SplitChannels(const Array3Df& input, + Array3Df* channel0, + Array3Df* channel1, + Array3Df* channel2) { assert(input.Depth() >= 3); channel0->Resize(input.Height(), input.Width()); channel1->Resize(input.Height(), input.Width()); @@ -83,7 +82,7 @@ void SplitChannels(const Array3Df &input, } } -void PrintArray(const Array3Df &array) { +void PrintArray(const Array3Df& array) { using namespace std; printf("[\n"); diff --git a/intern/libmv/libmv/image/array_nd.h b/intern/libmv/libmv/image/array_nd.h index e95e66aa2b3..1a3c39d0461 100644 --- a/intern/libmv/libmv/image/array_nd.h +++ b/intern/libmv/libmv/image/array_nd.h @@ -44,13 +44,13 @@ class ArrayND : public BaseArray { ArrayND() : data_(NULL), own_data_(true) { Resize(Index(0)); } /// Create an array with the specified shape. - ArrayND(const Index &shape) : data_(NULL), own_data_(true) { Resize(shape); } + ArrayND(const Index& shape) : data_(NULL), own_data_(true) { Resize(shape); } /// Create an array with the specified shape. - ArrayND(int *shape) : data_(NULL), own_data_(true) { Resize(shape); } + ArrayND(int* shape) : data_(NULL), own_data_(true) { Resize(shape); } /// Copy constructor. - ArrayND(const ArrayND<T, N> &b) : data_(NULL), own_data_(true) { + ArrayND(const ArrayND<T, N>& b) : data_(NULL), own_data_(true) { ResizeLike(b); std::memcpy(Data(), b.Data(), sizeof(T) * Size()); } @@ -58,7 +58,7 @@ class ArrayND : public BaseArray { ArrayND(int s0) : data_(NULL), own_data_(true) { Resize(s0); } ArrayND(int s0, int s1) : data_(NULL), own_data_(true) { Resize(s0, s1); } ArrayND(int s0, int s1, int s2) : data_(NULL), own_data_(true) { - Resize(s0, s1, s2); + Resize(s0, s1, s2); } ArrayND(T* data, int s0, int s1, int s2) @@ -69,28 +69,24 @@ class ArrayND : public BaseArray { /// Destructor deletes pixel data. ~ArrayND() { if (own_data_) { - delete [] data_; + delete[] data_; } } /// Assignation copies pixel data. - ArrayND &operator=(const ArrayND<T, N> &b) { + ArrayND& operator=(const ArrayND<T, N>& b) { assert(this != &b); ResizeLike(b); std::memcpy(Data(), b.Data(), sizeof(T) * Size()); return *this; } - const Index &Shapes() const { - return shape_; - } + const Index& Shapes() const { return shape_; } - const Index &Strides() const { - return strides_; - } + const Index& Strides() const { return strides_; } /// Create an array of shape s. - void Resize(const Index &new_shape) { + void Resize(const Index& new_shape) { if (data_ != NULL && shape_ == new_shape) { // Don't bother realloacting if the shapes match. return; @@ -101,7 +97,7 @@ class ArrayND : public BaseArray { strides_(i - 1) = strides_(i) * shape_(i); } if (own_data_) { - delete [] data_; + delete[] data_; data_ = NULL; if (Size() > 0) { data_ = new T[Size()]; @@ -109,15 +105,13 @@ class ArrayND : public BaseArray { } } - template<typename D> - void ResizeLike(const ArrayND<D, N> &other) { + template <typename D> + void ResizeLike(const ArrayND<D, N>& other) { Resize(other.Shape()); } /// Resizes the array to shape s. All data is lost. - void Resize(const int *new_shape_array) { - Resize(Index(new_shape_array)); - } + void Resize(const int* new_shape_array) { Resize(Index(new_shape_array)); } /// Resize a 1D array to length s0. void Resize(int s0) { @@ -136,9 +130,7 @@ class ArrayND : public BaseArray { } // Match Eigen2's API. - void resize(int rows, int cols) { - Resize(rows, cols); - } + void resize(int rows, int cols) { Resize(rows, cols); } /// Resize a 3D array to shape (s0,s1,s2). void Resize(int s0, int s1, int s2) { @@ -147,11 +139,11 @@ class ArrayND : public BaseArray { Resize(shape); } - template<typename D> - void CopyFrom(const ArrayND<D, N> &other) { + template <typename D> + void CopyFrom(const ArrayND<D, N>& other) { ResizeLike(other); - T *data = Data(); - const D *other_data = other.Data(); + T* data = Data(); + const D* other_data = other.Data(); for (int i = 0; i < Size(); ++i) { data[i] = T(other_data[i]); } @@ -171,19 +163,13 @@ class ArrayND : public BaseArray { } /// Return a tuple containing the length of each axis. - const Index &Shape() const { - return shape_; - } + const Index& Shape() const { return shape_; } /// Return the length of an axis. - int Shape(int axis) const { - return shape_(axis); - } + int Shape(int axis) const { return shape_(axis); } /// Return the distance between neighboring elements along axis. - int Stride(int axis) const { - return strides_(axis); - } + int Stride(int axis) const { return strides_(axis); } /// Return the number of elements of the array. int Size() const { @@ -194,18 +180,16 @@ class ArrayND : public BaseArray { } /// Return the total amount of memory used by the array. - int MemorySizeInBytes() const { - return sizeof(*this) + Size() * sizeof(T); - } + int MemorySizeInBytes() const { return sizeof(*this) + Size() * sizeof(T); } /// Pointer to the first element of the array. - T *Data() { return data_; } + T* Data() { return data_; } /// Constant pointer to the first element of the array. - const T *Data() const { return data_; } + const T* Data() const { return data_; } /// Distance between the first element and the element at position index. - int Offset(const Index &index) const { + int Offset(const Index& index) const { int offset = 0; for (int i = 0; i < N; ++i) offset += index(i) * Stride(i); @@ -231,25 +215,23 @@ class ArrayND : public BaseArray { } /// Return a reference to the element at position index. - T &operator()(const Index &index) { + T& operator()(const Index& index) { // TODO(pau) Boundary checking in debug mode. - return *( Data() + Offset(index) ); + return *(Data() + Offset(index)); } /// 1D specialization. - T &operator()(int i0) { - return *( Data() + Offset(i0) ); - } + T& operator()(int i0) { return *(Data() + Offset(i0)); } /// 2D specialization. - T &operator()(int i0, int i1) { + T& operator()(int i0, int i1) { assert(0 <= i0 && i0 < Shape(0)); assert(0 <= i1 && i1 < Shape(1)); return *(Data() + Offset(i0, i1)); } /// 3D specialization. - T &operator()(int i0, int i1, int i2) { + T& operator()(int i0, int i1, int i2) { assert(0 <= i0 && i0 < Shape(0)); assert(0 <= i1 && i1 < Shape(1)); assert(0 <= i2 && i2 < Shape(2)); @@ -257,29 +239,27 @@ class ArrayND : public BaseArray { } /// Return a constant reference to the element at position index. - const T &operator()(const Index &index) const { + const T& operator()(const Index& index) const { return *(Data() + Offset(index)); } /// 1D specialization. - const T &operator()(int i0) const { - return *(Data() + Offset(i0)); - } + const T& operator()(int i0) const { return *(Data() + Offset(i0)); } /// 2D specialization. - const T &operator()(int i0, int i1) const { + const T& operator()(int i0, int i1) const { assert(0 <= i0 && i0 < Shape(0)); assert(0 <= i1 && i1 < Shape(1)); return *(Data() + Offset(i0, i1)); } /// 3D specialization. - const T &operator()(int i0, int i1, int i2) const { + const T& operator()(int i0, int i1, int i2) const { return *(Data() + Offset(i0, i1, i2)); } /// True if index is inside array. - bool Contains(const Index &index) const { + bool Contains(const Index& index) const { for (int i = 0; i < N; ++i) if (index(i) < 0 || index(i) >= Shape(i)) return false; @@ -287,26 +267,24 @@ class ArrayND : public BaseArray { } /// 1D specialization. - bool Contains(int i0) const { - return 0 <= i0 && i0 < Shape(0); - } + bool Contains(int i0) const { return 0 <= i0 && i0 < Shape(0); } /// 2D specialization. bool Contains(int i0, int i1) const { - return 0 <= i0 && i0 < Shape(0) - && 0 <= i1 && i1 < Shape(1); + return 0 <= i0 && i0 < Shape(0) && 0 <= i1 && i1 < Shape(1); } /// 3D specialization. bool Contains(int i0, int i1, int i2) const { - return 0 <= i0 && i0 < Shape(0) - && 0 <= i1 && i1 < Shape(1) - && 0 <= i2 && i2 < Shape(2); + return 0 <= i0 && i0 < Shape(0) && 0 <= i1 && i1 < Shape(1) && 0 <= i2 && + i2 < Shape(2); } - bool operator==(const ArrayND<T, N> &other) const { - if (shape_ != other.shape_) return false; - if (strides_ != other.strides_) return false; + bool operator==(const ArrayND<T, N>& other) const { + if (shape_ != other.shape_) + return false; + if (strides_ != other.strides_) + return false; for (int i = 0; i < Size(); ++i) { if (this->Data()[i] != other.Data()[i]) return false; @@ -314,11 +292,11 @@ class ArrayND : public BaseArray { return true; } - bool operator!=(const ArrayND<T, N> &other) const { + bool operator!=(const ArrayND<T, N>& other) const { return !(*this == other); } - ArrayND<T, N> operator*(const ArrayND<T, N> &other) const { + ArrayND<T, N> operator*(const ArrayND<T, N>& other) const { assert(Shape() = other.Shape()); ArrayND<T, N> res; res.ResizeLike(*this); @@ -336,7 +314,7 @@ class ArrayND : public BaseArray { Index strides_; /// Pointer to the first element of the array. - T *data_; + T* data_; /// Flag if this Array either own or reference the data bool own_data_; @@ -346,30 +324,20 @@ class ArrayND : public BaseArray { template <typename T> class Array3D : public ArrayND<T, 3> { typedef ArrayND<T, 3> Base; + public: - Array3D() - : Base() { - } - Array3D(int height, int width, int depth = 1) - : Base(height, width, depth) { - } + Array3D() : Base() {} + Array3D(int height, int width, int depth = 1) : Base(height, width, depth) {} Array3D(T* data, int height, int width, int depth = 1) - : Base(data, height, width, depth) { - } + : Base(data, height, width, depth) {} void Resize(int height, int width, int depth = 1) { Base::Resize(height, width, depth); } - int Height() const { - return Base::Shape(0); - } - int Width() const { - return Base::Shape(1); - } - int Depth() const { - return Base::Shape(2); - } + int Height() const { return Base::Shape(0); } + int Width() const { return Base::Shape(1); } + int Depth() const { return Base::Shape(2); } // Match Eigen2's API so that Array3D's and Mat*'s can work together via // template magic. @@ -377,15 +345,15 @@ class Array3D : public ArrayND<T, 3> { int cols() const { return Width(); } int depth() const { return Depth(); } - int Get_Step() const { return Width()*Depth(); } + int Get_Step() const { return Width() * Depth(); } /// Enable accessing with 2 indices for grayscale images. - T &operator()(int i0, int i1, int i2 = 0) { + T& operator()(int i0, int i1, int i2 = 0) { assert(0 <= i0 && i0 < Height()); assert(0 <= i1 && i1 < Width()); return Base::operator()(i0, i1, i2); } - const T &operator()(int i0, int i1, int i2 = 0) const { + const T& operator()(int i0, int i1, int i2 = 0) const { assert(0 <= i0 && i0 < Height()); assert(0 <= i1 && i1 < Width()); return Base::operator()(i0, i1, i2); @@ -398,31 +366,29 @@ typedef Array3D<int> Array3Di; typedef Array3D<float> Array3Df; typedef Array3D<short> Array3Ds; -void SplitChannels(const Array3Df &input, - Array3Df *channel0, - Array3Df *channel1, - Array3Df *channel2); +void SplitChannels(const Array3Df& input, + Array3Df* channel0, + Array3Df* channel1, + Array3Df* channel2); -void PrintArray(const Array3Df &array); +void PrintArray(const Array3Df& array); /** Convert a float array into a byte array by scaling values by 255* (max-min). - * where max and min are automatically detected + * where max and min are automatically detected * (if automatic_range_detection = true) * \note and TODO this automatic detection only works when the image contains * at least one pixel of both bounds. **/ -void FloatArrayToScaledByteArray(const Array3Df &float_array, - Array3Du *byte_array, +void FloatArrayToScaledByteArray(const Array3Df& float_array, + Array3Du* byte_array, bool automatic_range_detection = false); //! Convert a byte array into a float array by dividing values by 255. -void ByteArrayToScaledFloatArray(const Array3Du &byte_array, - Array3Df *float_array); +void ByteArrayToScaledFloatArray(const Array3Du& byte_array, + Array3Df* float_array); template <typename AArrayType, typename BArrayType, typename CArrayType> -void MultiplyElements(const AArrayType &a, - const BArrayType &b, - CArrayType *c) { +void MultiplyElements(const AArrayType& a, const BArrayType& b, CArrayType* c) { // This function does an element-wise multiply between // the two Arrays A and B, and stores the result in C. // A and B must have the same dimensions. @@ -435,7 +401,7 @@ void MultiplyElements(const AArrayType &a, // The index starts at the maximum value for each dimension const typename CArrayType::Index& cShape = c->Shape(); - for ( int i = 0; i < CArrayType::Index::SIZE; ++i ) + for (int i = 0; i < CArrayType::Index::SIZE; ++i) index(i) = cShape(i) - 1; // After each multiplication, the highest-dimensional index is reduced. @@ -443,12 +409,12 @@ void MultiplyElements(const AArrayType &a, // and decrements the index of the next lower dimension. // This ripple-action continues until the entire new array has been // calculated, indicated by dimension zero having a negative index. - while ( index(0) >= 0 ) { + while (index(0) >= 0) { (*c)(index) = a(index) * b(index); int dimension = CArrayType::Index::SIZE - 1; index(dimension) = index(dimension) - 1; - while ( dimension > 0 && index(dimension) < 0 ) { + while (dimension > 0 && index(dimension) < 0) { index(dimension) = cShape(dimension) - 1; index(dimension - 1) = index(dimension - 1) - 1; --dimension; @@ -457,9 +423,9 @@ void MultiplyElements(const AArrayType &a, } template <typename TA, typename TB, typename TC> -void MultiplyElements(const ArrayND<TA, 3> &a, - const ArrayND<TB, 3> &b, - ArrayND<TC, 3> *c) { +void MultiplyElements(const ArrayND<TA, 3>& a, + const ArrayND<TB, 3>& b, + ArrayND<TC, 3>* c) { // Specialization for N==3 c->ResizeLike(a); assert(a.Shape(0) == b.Shape(0)); @@ -475,9 +441,9 @@ void MultiplyElements(const ArrayND<TA, 3> &a, } template <typename TA, typename TB, typename TC> -void MultiplyElements(const Array3D<TA> &a, - const Array3D<TB> &b, - Array3D<TC> *c) { +void MultiplyElements(const Array3D<TA>& a, + const Array3D<TB>& b, + Array3D<TC>* c) { // Specialization for N==3 c->ResizeLike(a); assert(a.Shape(0) == b.Shape(0)); diff --git a/intern/libmv/libmv/image/array_nd_test.cc b/intern/libmv/libmv/image/array_nd_test.cc index dc7cfacf90d..67838d34051 100644 --- a/intern/libmv/libmv/image/array_nd_test.cc +++ b/intern/libmv/libmv/image/array_nd_test.cc @@ -21,9 +21,9 @@ #include "libmv/image/array_nd.h" #include "testing/testing.h" -using libmv::ArrayND; using libmv::Array3D; using libmv::Array3Df; +using libmv::ArrayND; namespace { @@ -100,7 +100,7 @@ TEST(ArrayND, Size) { int l[] = {0, 1, 2}; ArrayND<int, 3>::Index last(l); - EXPECT_EQ(a.Size(), a.Offset(last)+1); + EXPECT_EQ(a.Size(), a.Offset(last) + 1); EXPECT_TRUE(a.Contains(last)); EXPECT_FALSE(a.Contains(shape)); } @@ -120,8 +120,8 @@ TEST(ArrayND, Parenthesis) { int s[] = {3, 3}; ArrayND<int, 2> a(s); - *(a.Data()+0) = 0; - *(a.Data()+5) = 5; + *(a.Data() + 0) = 0; + *(a.Data() + 5) = 5; int i1[] = {0, 0}; EXPECT_EQ(0, a(Index(i1))); @@ -210,7 +210,7 @@ TEST(ArrayND, MultiplyElements) { b(1, 1, 0) = 3; ArrayND<int, 3> c; MultiplyElements(a, b, &c); - EXPECT_FLOAT_EQ(6, c(0, 0, 0)); + EXPECT_FLOAT_EQ(6, c(0, 0, 0)); EXPECT_FLOAT_EQ(10, c(0, 1, 0)); EXPECT_FLOAT_EQ(12, c(1, 0, 0)); EXPECT_FLOAT_EQ(12, c(1, 1, 0)); diff --git a/intern/libmv/libmv/image/convolve.cc b/intern/libmv/libmv/image/convolve.cc index 464043581d2..478e320377d 100644 --- a/intern/libmv/libmv/image/convolve.cc +++ b/intern/libmv/libmv/image/convolve.cc @@ -29,7 +29,7 @@ namespace libmv { // Compute a Gaussian kernel and derivative, such that you can take the // derivative of an image by convolving with the kernel horizontally then the // derivative vertically to get (eg) the y derivative. -void ComputeGaussianKernel(double sigma, Vec *kernel, Vec *derivative) { +void ComputeGaussianKernel(double sigma, Vec* kernel, Vec* derivative) { assert(sigma >= 0.0); // 0.004 implies a 3 pixel kernel with 1 pixel sigma. @@ -37,7 +37,7 @@ void ComputeGaussianKernel(double sigma, Vec *kernel, Vec *derivative) { // Calculate the kernel size based on sigma such that it is odd. float precisehalfwidth = GaussianInversePositive(truncation_factor, sigma); - int width = lround(2*precisehalfwidth); + int width = lround(2 * precisehalfwidth); if (width % 2 == 0) { width++; } @@ -47,7 +47,7 @@ void ComputeGaussianKernel(double sigma, Vec *kernel, Vec *derivative) { kernel->setZero(); derivative->setZero(); int halfwidth = width / 2; - for (int i = -halfwidth; i <= halfwidth; ++i) { + for (int i = -halfwidth; i <= halfwidth; ++i) { (*kernel)(i + halfwidth) = Gaussian(i, sigma); (*derivative)(i + halfwidth) = GaussianDerivative(i, sigma); } @@ -57,16 +57,21 @@ void ComputeGaussianKernel(double sigma, Vec *kernel, Vec *derivative) { // Normalize the derivative differently. See // www.cs.duke.edu/courses/spring03/cps296.1/handouts/Image%20Processing.pdf double factor = 0.; - for (int i = -halfwidth; i <= halfwidth; ++i) { - factor -= i*(*derivative)(i+halfwidth); + for (int i = -halfwidth; i <= halfwidth; ++i) { + factor -= i * (*derivative)(i + halfwidth); } *derivative /= factor; } template <int size, bool vertical> -void FastConvolve(const Vec &kernel, int width, int height, - const float* src, int src_stride, int src_line_stride, - float* dst, int dst_stride) { +void FastConvolve(const Vec& kernel, + int width, + int height, + const float* src, + int src_stride, + int src_line_stride, + float* dst, + int dst_stride) { double coefficients[2 * size + 1]; for (int k = 0; k < 2 * size + 1; ++k) { coefficients[k] = kernel(2 * size - k); @@ -93,14 +98,14 @@ void FastConvolve(const Vec &kernel, int width, int height, } } -template<bool vertical> -void Convolve(const Array3Df &in, - const Vec &kernel, - Array3Df *out_pointer, +template <bool vertical> +void Convolve(const Array3Df& in, + const Vec& kernel, + Array3Df* out_pointer, int plane) { int width = in.Width(); int height = in.Height(); - Array3Df &out = *out_pointer; + Array3Df& out = *out_pointer; if (plane == -1) { out.ResizeLike(in); plane = 0; @@ -119,61 +124,62 @@ void Convolve(const Array3Df &in, // fast path. int half_width = kernel.size() / 2; switch (half_width) { -#define static_convolution(size) case size: \ - FastConvolve<size, vertical>(kernel, width, height, src, src_stride, \ - src_line_stride, dst, dst_stride); break; - static_convolution(1) - static_convolution(2) - static_convolution(3) - static_convolution(4) - static_convolution(5) - static_convolution(6) - static_convolution(7) +#define static_convolution(size) \ + case size: \ + FastConvolve<size, vertical>(kernel, \ + width, \ + height, \ + src, \ + src_stride, \ + src_line_stride, \ + dst, \ + dst_stride); \ + break; + static_convolution(1) static_convolution(2) static_convolution(3) + static_convolution(4) static_convolution(5) static_convolution(6) + static_convolution(7) #undef static_convolution - default: - int dynamic_size = kernel.size() / 2; - for (int y = 0; y < height; ++y) { - for (int x = 0; x < width; ++x) { - double sum = 0; - // Slow path: this loop cannot be unrolled. - for (int k = -dynamic_size; k <= dynamic_size; ++k) { - if (vertical) { - if (y + k >= 0 && y + k < height) { - sum += src[k * src_line_stride] * - kernel(2 * dynamic_size - (k + dynamic_size)); - } - } else { - if (x + k >= 0 && x + k < width) { - sum += src[k * src_stride] * - kernel(2 * dynamic_size - (k + dynamic_size)); - } + default : int dynamic_size = kernel.size() / 2; + for (int y = 0; y < height; ++y) { + for (int x = 0; x < width; ++x) { + double sum = 0; + // Slow path: this loop cannot be unrolled. + for (int k = -dynamic_size; k <= dynamic_size; ++k) { + if (vertical) { + if (y + k >= 0 && y + k < height) { + sum += src[k * src_line_stride] * + kernel(2 * dynamic_size - (k + dynamic_size)); + } + } else { + if (x + k >= 0 && x + k < width) { + sum += src[k * src_stride] * + kernel(2 * dynamic_size - (k + dynamic_size)); } } - dst[0] = static_cast<float>(sum); - src += src_stride; - dst += dst_stride; } + dst[0] = static_cast<float>(sum); + src += src_stride; + dst += dst_stride; } + } } } -void ConvolveHorizontal(const Array3Df &in, - const Vec &kernel, - Array3Df *out_pointer, +void ConvolveHorizontal(const Array3Df& in, + const Vec& kernel, + Array3Df* out_pointer, int plane) { Convolve<false>(in, kernel, out_pointer, plane); } -void ConvolveVertical(const Array3Df &in, - const Vec &kernel, - Array3Df *out_pointer, +void ConvolveVertical(const Array3Df& in, + const Vec& kernel, + Array3Df* out_pointer, int plane) { Convolve<true>(in, kernel, out_pointer, plane); } -void ConvolveGaussian(const Array3Df &in, - double sigma, - Array3Df *out_pointer) { +void ConvolveGaussian(const Array3Df& in, double sigma, Array3Df* out_pointer) { Vec kernel, derivative; ComputeGaussianKernel(sigma, &kernel, &derivative); @@ -182,10 +188,10 @@ void ConvolveGaussian(const Array3Df &in, ConvolveHorizontal(tmp, kernel, out_pointer); } -void ImageDerivatives(const Array3Df &in, +void ImageDerivatives(const Array3Df& in, double sigma, - Array3Df *gradient_x, - Array3Df *gradient_y) { + Array3Df* gradient_x, + Array3Df* gradient_y) { Vec kernel, derivative; ComputeGaussianKernel(sigma, &kernel, &derivative); Array3Df tmp; @@ -199,11 +205,11 @@ void ImageDerivatives(const Array3Df &in, ConvolveVertical(tmp, derivative, gradient_y); } -void BlurredImageAndDerivatives(const Array3Df &in, +void BlurredImageAndDerivatives(const Array3Df& in, double sigma, - Array3Df *blurred_image, - Array3Df *gradient_x, - Array3Df *gradient_y) { + Array3Df* blurred_image, + Array3Df* gradient_x, + Array3Df* gradient_y) { Vec kernel, derivative; ComputeGaussianKernel(sigma, &kernel, &derivative); Array3Df tmp; @@ -224,9 +230,9 @@ void BlurredImageAndDerivatives(const Array3Df &in, // image, and store the results in three channels. Since the blurred value and // gradients are closer in memory, this leads to better performance if all // three values are needed at the same time. -void BlurredImageAndDerivativesChannels(const Array3Df &in, +void BlurredImageAndDerivativesChannels(const Array3Df& in, double sigma, - Array3Df *blurred_and_gradxy) { + Array3Df* blurred_and_gradxy) { assert(in.Depth() == 1); Vec kernel, derivative; @@ -246,10 +252,10 @@ void BlurredImageAndDerivativesChannels(const Array3Df &in, ConvolveVertical(tmp, derivative, blurred_and_gradxy, 2); } -void BoxFilterHorizontal(const Array3Df &in, +void BoxFilterHorizontal(const Array3Df& in, int window_size, - Array3Df *out_pointer) { - Array3Df &out = *out_pointer; + Array3Df* out_pointer) { + Array3Df& out = *out_pointer; out.ResizeLike(in); int half_width = (window_size - 1) / 2; @@ -266,7 +272,7 @@ void BoxFilterHorizontal(const Array3Df &in, out(i, j, k) = sum; } // Fill interior. - for (int j = half_width + 1; j < in.Width()-half_width; ++j) { + for (int j = half_width + 1; j < in.Width() - half_width; ++j) { sum -= in(i, j - half_width - 1, k); sum += in(i, j + half_width, k); out(i, j, k) = sum; @@ -280,10 +286,10 @@ void BoxFilterHorizontal(const Array3Df &in, } } -void BoxFilterVertical(const Array3Df &in, +void BoxFilterVertical(const Array3Df& in, int window_size, - Array3Df *out_pointer) { - Array3Df &out = *out_pointer; + Array3Df* out_pointer) { + Array3Df& out = *out_pointer; out.ResizeLike(in); int half_width = (window_size - 1) / 2; @@ -300,7 +306,7 @@ void BoxFilterVertical(const Array3Df &in, out(i, j, k) = sum; } // Fill interior. - for (int i = half_width + 1; i < in.Height()-half_width; ++i) { + for (int i = half_width + 1; i < in.Height() - half_width; ++i) { sum -= in(i - half_width - 1, j, k); sum += in(i + half_width, j, k); out(i, j, k) = sum; @@ -314,9 +320,7 @@ void BoxFilterVertical(const Array3Df &in, } } -void BoxFilter(const Array3Df &in, - int box_width, - Array3Df *out) { +void BoxFilter(const Array3Df& in, int box_width, Array3Df* out) { Array3Df tmp; BoxFilterHorizontal(in, box_width, &tmp); BoxFilterVertical(tmp, box_width, out); @@ -327,17 +331,17 @@ void LaplaceFilter(unsigned char* src, int width, int height, int strength) { - for (int y = 1; y < height-1; y++) - for (int x = 1; x < width-1; x++) { - const unsigned char* s = &src[y*width+x]; - int l = 128 + - s[-width-1] + s[-width] + s[-width+1] + - s[1] - 8*s[0] + s[1] + - s[ width-1] + s[ width] + s[ width+1]; - int d = ((256-strength)*s[0] + strength*l) / 256; - if (d < 0) d=0; - if (d > 255) d=255; - dst[y*width+x] = d; + for (int y = 1; y < height - 1; y++) + for (int x = 1; x < width - 1; x++) { + const unsigned char* s = &src[y * width + x]; + int l = 128 + s[-width - 1] + s[-width] + s[-width + 1] + s[1] - + 8 * s[0] + s[1] + s[width - 1] + s[width] + s[width + 1]; + int d = ((256 - strength) * s[0] + strength * l) / 256; + if (d < 0) + d = 0; + if (d > 255) + d = 255; + dst[y * width + x] = d; } } diff --git a/intern/libmv/libmv/image/convolve.h b/intern/libmv/libmv/image/convolve.h index d3b6da9794b..3794550eb73 100644 --- a/intern/libmv/libmv/image/convolve.h +++ b/intern/libmv/libmv/image/convolve.h @@ -30,70 +30,71 @@ namespace libmv { // Zero mean Gaussian. inline double Gaussian(double x, double sigma) { - return 1/sqrt(2*M_PI*sigma*sigma) * exp(-(x*x/2/sigma/sigma)); + return 1 / sqrt(2 * M_PI * sigma * sigma) * exp(-(x * x / 2 / sigma / sigma)); } // 2D gaussian (zero mean) // (9) in http://mathworld.wolfram.com/GaussianFunction.html inline double Gaussian2D(double x, double y, double sigma) { - return 1.0/(2.0*M_PI*sigma*sigma) * exp( -(x*x+y*y)/(2.0*sigma*sigma)); + return 1.0 / (2.0 * M_PI * sigma * sigma) * + exp(-(x * x + y * y) / (2.0 * sigma * sigma)); } inline double GaussianDerivative(double x, double sigma) { return -x / sigma / sigma * Gaussian(x, sigma); } // Solve the inverse of the Gaussian for positive x. inline double GaussianInversePositive(double y, double sigma) { - return sqrt(-2 * sigma * sigma * log(y * sigma * sqrt(2*M_PI))); + return sqrt(-2 * sigma * sigma * log(y * sigma * sqrt(2 * M_PI))); } -void ComputeGaussianKernel(double sigma, Vec *kernel, Vec *derivative); -void ConvolveHorizontal(const FloatImage &in, - const Vec &kernel, - FloatImage *out_pointer, +void ComputeGaussianKernel(double sigma, Vec* kernel, Vec* derivative); +void ConvolveHorizontal(const FloatImage& in, + const Vec& kernel, + FloatImage* out_pointer, int plane = -1); -void ConvolveVertical(const FloatImage &in, - const Vec &kernel, - FloatImage *out_pointer, +void ConvolveVertical(const FloatImage& in, + const Vec& kernel, + FloatImage* out_pointer, int plane = -1); -void ConvolveGaussian(const FloatImage &in, +void ConvolveGaussian(const FloatImage& in, double sigma, - FloatImage *out_pointer); + FloatImage* out_pointer); -void ImageDerivatives(const FloatImage &in, +void ImageDerivatives(const FloatImage& in, double sigma, - FloatImage *gradient_x, - FloatImage *gradient_y); + FloatImage* gradient_x, + FloatImage* gradient_y); -void BlurredImageAndDerivatives(const FloatImage &in, +void BlurredImageAndDerivatives(const FloatImage& in, double sigma, - FloatImage *blurred_image, - FloatImage *gradient_x, - FloatImage *gradient_y); + FloatImage* blurred_image, + FloatImage* gradient_x, + FloatImage* gradient_y); // Blur and take the gradients of an image, storing the results inside the // three channels of blurred_and_gradxy. -void BlurredImageAndDerivativesChannels(const FloatImage &in, +void BlurredImageAndDerivativesChannels(const FloatImage& in, double sigma, - FloatImage *blurred_and_gradxy); + FloatImage* blurred_and_gradxy); -void BoxFilterHorizontal(const FloatImage &in, +void BoxFilterHorizontal(const FloatImage& in, int window_size, - FloatImage *out_pointer); + FloatImage* out_pointer); -void BoxFilterVertical(const FloatImage &in, +void BoxFilterVertical(const FloatImage& in, int window_size, - FloatImage *out_pointer); + FloatImage* out_pointer); -void BoxFilter(const FloatImage &in, - int box_width, - FloatImage *out); +void BoxFilter(const FloatImage& in, int box_width, FloatImage* out); /*! Convolve \a src into \a dst with the discrete laplacian operator. \a src and \a dst should be \a width x \a height images. - \a strength is an interpolation coefficient (0-256) between original image and the laplacian. + \a strength is an interpolation coefficient (0-256) between original image + and the laplacian. - \note Make sure the search region is filtered with the same strength as the pattern. + \note Make sure the search region is filtered with the same strength as the + pattern. */ void LaplaceFilter(unsigned char* src, unsigned char* dst, @@ -104,4 +105,3 @@ void LaplaceFilter(unsigned char* src, } // namespace libmv #endif // LIBMV_IMAGE_CONVOLVE_H_ - diff --git a/intern/libmv/libmv/image/convolve_test.cc b/intern/libmv/libmv/image/convolve_test.cc index 0cdef8e1e72..1ad4cb9a40e 100644 --- a/intern/libmv/libmv/image/convolve_test.cc +++ b/intern/libmv/libmv/image/convolve_test.cc @@ -85,26 +85,26 @@ TEST(Convolve, BlurredImageAndDerivativesChannelsHorizontalSlope) { FloatImage image(10, 10), blurred_and_derivatives; for (int j = 0; j < 10; ++j) { for (int i = 0; i < 10; ++i) { - image(j, i) = 2*i; + image(j, i) = 2 * i; } } BlurredImageAndDerivativesChannels(image, 0.9, &blurred_and_derivatives); EXPECT_NEAR(blurred_and_derivatives(5, 5, 0), 10.0, 1e-7); - EXPECT_NEAR(blurred_and_derivatives(5, 5, 1), 2.0, 1e-7); - EXPECT_NEAR(blurred_and_derivatives(5, 5, 2), 0.0, 1e-7); + EXPECT_NEAR(blurred_and_derivatives(5, 5, 1), 2.0, 1e-7); + EXPECT_NEAR(blurred_and_derivatives(5, 5, 2), 0.0, 1e-7); } TEST(Convolve, BlurredImageAndDerivativesChannelsVerticalSlope) { FloatImage image(10, 10), blurred_and_derivatives; for (int j = 0; j < 10; ++j) { for (int i = 0; i < 10; ++i) { - image(j, i) = 2*j; + image(j, i) = 2 * j; } } BlurredImageAndDerivativesChannels(image, 0.9, &blurred_and_derivatives); EXPECT_NEAR(blurred_and_derivatives(5, 5, 0), 10.0, 1e-7); - EXPECT_NEAR(blurred_and_derivatives(5, 5, 1), 0.0, 1e-7); - EXPECT_NEAR(blurred_and_derivatives(5, 5, 2), 2.0, 1e-7); + EXPECT_NEAR(blurred_and_derivatives(5, 5, 1), 0.0, 1e-7); + EXPECT_NEAR(blurred_and_derivatives(5, 5, 2), 2.0, 1e-7); } } // namespace diff --git a/intern/libmv/libmv/image/correlation.h b/intern/libmv/libmv/image/correlation.h index c354f7e891e..25123efe8d0 100644 --- a/intern/libmv/libmv/image/correlation.h +++ b/intern/libmv/libmv/image/correlation.h @@ -21,14 +21,14 @@ #ifndef LIBMV_IMAGE_CORRELATION_H #define LIBMV_IMAGE_CORRELATION_H -#include "libmv/logging/logging.h" #include "libmv/image/image.h" +#include "libmv/logging/logging.h" namespace libmv { inline double PearsonProductMomentCorrelation( - const FloatImage &image_and_gradient1_sampled, - const FloatImage &image_and_gradient2_sampled) { + const FloatImage& image_and_gradient1_sampled, + const FloatImage& image_and_gradient2_sampled) { assert(image_and_gradient1_sampled.Width() == image_and_gradient2_sampled.Width()); assert(image_and_gradient1_sampled.Height() == @@ -63,9 +63,8 @@ inline double PearsonProductMomentCorrelation( double covariance_xy = sXY - sX * sY; double correlation = covariance_xy / sqrt(var_x * var_y); - LG << "Covariance xy: " << covariance_xy - << ", var 1: " << var_x << ", var 2: " << var_y - << ", correlation: " << correlation; + LG << "Covariance xy: " << covariance_xy << ", var 1: " << var_x + << ", var 2: " << var_y << ", correlation: " << correlation; return correlation; } diff --git a/intern/libmv/libmv/image/image.h b/intern/libmv/libmv/image/image.h index e0f200a4c93..40d6aa6f70a 100644 --- a/intern/libmv/libmv/image/image.h +++ b/intern/libmv/libmv/image/image.h @@ -39,14 +39,11 @@ typedef Array3Ds ShortImage; // is the best solution after all. class Image { public: - // Create an image from an array. The image takes ownership of the array. - Image(Array3Du *array) : array_type_(BYTE), array_(array) {} - Image(Array3Df *array) : array_type_(FLOAT), array_(array) {} + Image(Array3Du* array) : array_type_(BYTE), array_(array) {} + Image(Array3Df* array) : array_type_(FLOAT), array_(array) {} - Image(const Image &img): array_type_(NONE), array_(NULL) { - *this = img; - } + Image(const Image& img) : array_type_(NONE), array_(NULL) { *this = img; } // Underlying data type. enum DataType { @@ -62,20 +59,18 @@ class Image { int size; switch (array_type_) { case BYTE: - size = reinterpret_cast<Array3Du *>(array_)->MemorySizeInBytes(); - break; + size = reinterpret_cast<Array3Du*>(array_)->MemorySizeInBytes(); + break; case FLOAT: - size = reinterpret_cast<Array3Df *>(array_)->MemorySizeInBytes(); - break; + size = reinterpret_cast<Array3Df*>(array_)->MemorySizeInBytes(); + break; case INT: - size = reinterpret_cast<Array3Di *>(array_)->MemorySizeInBytes(); - break; + size = reinterpret_cast<Array3Di*>(array_)->MemorySizeInBytes(); + break; case SHORT: - size = reinterpret_cast<Array3Ds *>(array_)->MemorySizeInBytes(); - break; - default : - size = 0; - assert(0); + size = reinterpret_cast<Array3Ds*>(array_)->MemorySizeInBytes(); + break; + default: size = 0; assert(0); } size += sizeof(*this); return size; @@ -83,71 +78,57 @@ class Image { ~Image() { switch (array_type_) { - case BYTE: - delete reinterpret_cast<Array3Du *>(array_); - - break; - case FLOAT: - delete reinterpret_cast<Array3Df *>(array_); - - break; - case INT: - delete reinterpret_cast<Array3Di *>(array_); - - break; - case SHORT: - delete reinterpret_cast<Array3Ds *>(array_); - - break; - default: - assert(0); - } + case BYTE: delete reinterpret_cast<Array3Du*>(array_); break; + case FLOAT: delete reinterpret_cast<Array3Df*>(array_); break; + case INT: delete reinterpret_cast<Array3Di*>(array_); break; + case SHORT: delete reinterpret_cast<Array3Ds*>(array_); break; + default: assert(0); + } } - Image& operator= (const Image& f) { + Image& operator=(const Image& f) { if (this != &f) { array_type_ = f.array_type_; switch (array_type_) { case BYTE: - delete reinterpret_cast<Array3Du *>(array_); - array_ = new Array3Du(*(Array3Du *)f.array_); - break; + delete reinterpret_cast<Array3Du*>(array_); + array_ = new Array3Du(*(Array3Du*)f.array_); + break; case FLOAT: - delete reinterpret_cast<Array3Df *>(array_); - array_ = new Array3Df(*(Array3Df *)f.array_); - break; + delete reinterpret_cast<Array3Df*>(array_); + array_ = new Array3Df(*(Array3Df*)f.array_); + break; case INT: - delete reinterpret_cast<Array3Di *>(array_); - array_ = new Array3Di(*(Array3Di *)f.array_); - break; + delete reinterpret_cast<Array3Di*>(array_); + array_ = new Array3Di(*(Array3Di*)f.array_); + break; case SHORT: - delete reinterpret_cast<Array3Ds *>(array_); - array_ = new Array3Ds(*(Array3Ds *)f.array_); - break; - default: - assert(0); + delete reinterpret_cast<Array3Ds*>(array_); + array_ = new Array3Ds(*(Array3Ds*)f.array_); + break; + default: assert(0); } } return *this; } - Array3Du *AsArray3Du() const { + Array3Du* AsArray3Du() const { if (array_type_ == BYTE) { - return reinterpret_cast<Array3Du *>(array_); + return reinterpret_cast<Array3Du*>(array_); } return NULL; } - Array3Df *AsArray3Df() const { + Array3Df* AsArray3Df() const { if (array_type_ == FLOAT) { - return reinterpret_cast<Array3Df *>(array_); + return reinterpret_cast<Array3Df*>(array_); } return NULL; } private: DataType array_type_; - BaseArray *array_; + BaseArray* array_; }; } // namespace libmv diff --git a/intern/libmv/libmv/image/image_converter.h b/intern/libmv/libmv/image/image_converter.h index b3a3fa2bf8c..41d53be6722 100644 --- a/intern/libmv/libmv/image/image_converter.h +++ b/intern/libmv/libmv/image/image_converter.h @@ -28,7 +28,7 @@ namespace libmv { // The factor comes from http://www.easyrgb.com/ // RGB to XYZ : Y is the luminance channel // var_R * 0.2126 + var_G * 0.7152 + var_B * 0.0722 -template<typename T> +template <typename T> inline T RGB2GRAY(const T r, const T g, const T b) { return static_cast<T>(r * 0.2126 + g * 0.7152 + b * 0.0722); } @@ -42,8 +42,8 @@ inline unsigned char RGB2GRAY<unsigned char>(const unsigned char r, return (unsigned char)(r * 0.2126 + g * 0.7152 + b * 0.0722 +0.5); }*/ -template<class ImageIn, class ImageOut> -void Rgb2Gray(const ImageIn &imaIn, ImageOut *imaOut) { +template <class ImageIn, class ImageOut> +void Rgb2Gray(const ImageIn& imaIn, ImageOut* imaOut) { // It is all fine to cnvert RGBA image here as well, // all the additional channels will be nicely ignored. assert(imaIn.Depth() >= 3); @@ -52,21 +52,22 @@ void Rgb2Gray(const ImageIn &imaIn, ImageOut *imaOut) { // Convert each RGB pixel into Gray value (luminance) for (int j = 0; j < imaIn.Height(); ++j) { - for (int i = 0; i < imaIn.Width(); ++i) { - (*imaOut)(j, i) = RGB2GRAY(imaIn(j, i, 0) , imaIn(j, i, 1), imaIn(j, i, 2)); + for (int i = 0; i < imaIn.Width(); ++i) { + (*imaOut)(j, i) = + RGB2GRAY(imaIn(j, i, 0), imaIn(j, i, 1), imaIn(j, i, 2)); } } } // Convert given float image to an unsigned char array of pixels. -template<class Image> -unsigned char *FloatImageToUCharArray(const Image &image) { - unsigned char *buffer = +template <class Image> +unsigned char* FloatImageToUCharArray(const Image& image) { + unsigned char* buffer = new unsigned char[image.Width() * image.Height() * image.Depth()]; for (int y = 0; y < image.Height(); y++) { - for (int x = 0; x < image.Width(); x++) { - for (int d = 0; d < image.Depth(); d++) { + for (int x = 0; x < image.Width(); x++) { + for (int d = 0; d < image.Depth(); d++) { int index = (y * image.Width() + x) * image.Depth() + d; buffer[index] = 255.0 * image(y, x, d); } diff --git a/intern/libmv/libmv/image/image_drawing.h b/intern/libmv/libmv/image/image_drawing.h index f50e48b75a3..dd6a94dd7d4 100644 --- a/intern/libmv/libmv/image/image_drawing.h +++ b/intern/libmv/libmv/image/image_drawing.h @@ -34,9 +34,9 @@ namespace libmv { /// Put the pixel in the image to the given color only if the point (xc,yc) /// is inside the image. template <class Image, class Color> -inline void safePutPixel(int yc, int xc, const Color & col, Image *pim) { +inline void safePutPixel(int yc, int xc, const Color& col, Image* pim) { if (!pim) - return; + return; if (pim->Contains(yc, xc)) { (*pim)(yc, xc) = col; } @@ -45,9 +45,9 @@ inline void safePutPixel(int yc, int xc, const Color & col, Image *pim) { /// is inside the image. This function support multi-channel color /// \note The color pointer col must have size as the image depth template <class Image, class Color> -inline void safePutPixel(int yc, int xc, const Color *col, Image *pim) { +inline void safePutPixel(int yc, int xc, const Color* col, Image* pim) { if (!pim) - return; + return; if (pim->Contains(yc, xc)) { for (int i = 0; i < pim->Depth(); ++i) (*pim)(yc, xc, i) = *(col + i); @@ -59,19 +59,23 @@ inline void safePutPixel(int yc, int xc, const Color *col, Image *pim) { // Add the rotation of the ellipse. // As the algo. use symmetry we must use 4 rotations. template <class Image, class Color> -void DrawEllipse(int xc, int yc, int radiusA, int radiusB, - const Color &col, Image *pim, double angle = 0.0) { +void DrawEllipse(int xc, + int yc, + int radiusA, + int radiusB, + const Color& col, + Image* pim, + double angle = 0.0) { int a = radiusA; int b = radiusB; // Counter Clockwise rotation matrix. - double matXY[4] = { cos(angle), sin(angle), - -sin(angle), cos(angle)}; + double matXY[4] = {cos(angle), sin(angle), -sin(angle), cos(angle)}; int x, y; double d1, d2; x = 0; y = b; - d1 = b*b - a*a*b + a*a/4; + d1 = b * b - a * a * b + a * a / 4; float rotX = (matXY[0] * x + matXY[1] * y); float rotY = (matXY[2] * x + matXY[3] * y); @@ -86,12 +90,12 @@ void DrawEllipse(int xc, int yc, int radiusA, int radiusB, rotY = (-matXY[2] * x + matXY[3] * y); safePutPixel(yc + rotY, xc + rotX, col, pim); - while (a*a*(y-.5) > b*b*(x+1)) { + while (a * a * (y - .5) > b * b * (x + 1)) { if (d1 < 0) { - d1 += b*b*(2*x+3); + d1 += b * b * (2 * x + 3); ++x; } else { - d1 += b*b*(2*x+3) + a*a*(-2*y+2); + d1 += b * b * (2 * x + 3) + a * a * (-2 * y + 2); ++x; --y; } @@ -108,14 +112,14 @@ void DrawEllipse(int xc, int yc, int radiusA, int radiusB, rotY = (-matXY[2] * x + matXY[3] * y); safePutPixel(yc + rotY, xc + rotX, col, pim); } - d2 = b*b*(x+.5)*(x+.5) + a*a*(y-1)*(y-1) - a*a*b*b; + d2 = b * b * (x + .5) * (x + .5) + a * a * (y - 1) * (y - 1) - a * a * b * b; while (y > 0) { if (d2 < 0) { - d2 += b*b*(2*x+2) + a*a*(-2*y+3); + d2 += b * b * (2 * x + 2) + a * a * (-2 * y + 3); --y; ++x; } else { - d2 += a*a*(-2*y+3); + d2 += a * a * (-2 * y + 3); --y; } rotX = (matXY[0] * x + matXY[1] * y); @@ -137,23 +141,23 @@ void DrawEllipse(int xc, int yc, int radiusA, int radiusB, // So it's better the use the Andres method. // http://fr.wikipedia.org/wiki/Algorithme_de_tracé_de_cercle_d'Andres. template <class Image, class Color> -void DrawCircle(int x, int y, int radius, const Color &col, Image *pim) { - Image &im = *pim; - if ( im.Contains(y + radius, x + radius) - || im.Contains(y + radius, x - radius) - || im.Contains(y - radius, x + radius) - || im.Contains(y - radius, x - radius)) { +void DrawCircle(int x, int y, int radius, const Color& col, Image* pim) { + Image& im = *pim; + if (im.Contains(y + radius, x + radius) || + im.Contains(y + radius, x - radius) || + im.Contains(y - radius, x + radius) || + im.Contains(y - radius, x - radius)) { int x1 = 0; int y1 = radius; int d = radius - 1; while (y1 >= x1) { // Draw the point for each octant. - safePutPixel( y1 + y, x1 + x, col, pim); - safePutPixel( x1 + y, y1 + x, col, pim); - safePutPixel( y1 + y, -x1 + x, col, pim); - safePutPixel( x1 + y, -y1 + x, col, pim); - safePutPixel(-y1 + y, x1 + x, col, pim); - safePutPixel(-x1 + y, y1 + x, col, pim); + safePutPixel(y1 + y, x1 + x, col, pim); + safePutPixel(x1 + y, y1 + x, col, pim); + safePutPixel(y1 + y, -x1 + x, col, pim); + safePutPixel(x1 + y, -y1 + x, col, pim); + safePutPixel(-y1 + y, x1 + x, col, pim); + safePutPixel(-x1 + y, y1 + x, col, pim); safePutPixel(-y1 + y, -x1 + x, col, pim); safePutPixel(-x1 + y, -y1 + x, col, pim); if (d >= 2 * x1) { @@ -163,7 +167,7 @@ void DrawCircle(int x, int y, int radius, const Color &col, Image *pim) { if (d <= 2 * (radius - y1)) { d = d + 2 * y1 - 1; y1 -= 1; - } else { + } else { d = d + 2 * (y1 - x1 - 1); y1 -= 1; x1 += 1; @@ -175,8 +179,8 @@ void DrawCircle(int x, int y, int radius, const Color &col, Image *pim) { // Bresenham algorithm template <class Image, class Color> -void DrawLine(int xa, int ya, int xb, int yb, const Color &col, Image *pim) { - Image &im = *pim; +void DrawLine(int xa, int ya, int xb, int yb, const Color& col, Image* pim) { + Image& im = *pim; // If one point is outside the image // Replace the outside point by the intersection of the line and @@ -185,35 +189,37 @@ void DrawLine(int xa, int ya, int xb, int yb, const Color &col, Image *pim) { int width = pim->Width(); int height = pim->Height(); const bool xdir = xa < xb, ydir = ya < yb; - float nx0 = xa, nx1 = xb, ny0 = ya, ny1 = yb, - &xleft = xdir?nx0:nx1, &yleft = xdir?ny0:ny1, - &xright = xdir?nx1:nx0, &yright = xdir?ny1:ny0, - &xup = ydir?nx0:nx1, &yup = ydir?ny0:ny1, - &xdown = ydir?nx1:nx0, &ydown = ydir?ny1:ny0; + float nx0 = xa, nx1 = xb, ny0 = ya, ny1 = yb, &xleft = xdir ? nx0 : nx1, + &yleft = xdir ? ny0 : ny1, &xright = xdir ? nx1 : nx0, + &yright = xdir ? ny1 : ny0, &xup = ydir ? nx0 : nx1, + &yup = ydir ? ny0 : ny1, &xdown = ydir ? nx1 : nx0, + &ydown = ydir ? ny1 : ny0; - if (xright < 0 || xleft >= width) return; + if (xright < 0 || xleft >= width) + return; if (xleft < 0) { - yleft -= xleft*(yright - yleft)/(xright - xleft); - xleft = 0; + yleft -= xleft * (yright - yleft) / (xright - xleft); + xleft = 0; } if (xright >= width) { - yright -= (xright - width)*(yright - yleft)/(xright - xleft); - xright = width - 1; + yright -= (xright - width) * (yright - yleft) / (xright - xleft); + xright = width - 1; } - if (ydown < 0 || yup >= height) return; + if (ydown < 0 || yup >= height) + return; if (yup < 0) { - xup -= yup*(xdown - xup)/(ydown - yup); - yup = 0; + xup -= yup * (xdown - xup) / (ydown - yup); + yup = 0; } if (ydown >= height) { - xdown -= (ydown - height)*(xdown - xup)/(ydown - yup); - ydown = height - 1; + xdown -= (ydown - height) * (xdown - xup) / (ydown - yup); + ydown = height - 1; } - xa = (int) xleft; - xb = (int) xright; - ya = (int) yleft; - yb = (int) yright; + xa = (int)xleft; + xb = (int)xright; + ya = (int)yleft; + yb = (int)yright; } int xbas, xhaut, ybas, yhaut; @@ -241,7 +247,7 @@ void DrawLine(int xa, int ya, int xb, int yb, const Color &col, Image *pim) { } if (dy > 0) { // Positive slope will increment X. incrmY = 1; - } else { // Negative slope. + } else { // Negative slope. incrmY = -1; } if (dx >= dy) { @@ -255,9 +261,9 @@ void DrawLine(int xa, int ya, int xb, int yb, const Color &col, Image *pim) { x += incrmX; if (dp <= 0) { // Go in direction of the South Pixel. dp += S; - } else { // Go to the North. + } else { // Go to the North. dp += N; - y+=incrmY; + y += incrmY; } } } else { @@ -271,7 +277,7 @@ void DrawLine(int xa, int ya, int xb, int yb, const Color &col, Image *pim) { y += incrmY; if (dp <= 0) { // Go in direction of the South Pixel. dp += S; - } else { // Go to the North. + } else { // Go to the North. dp += N; x += incrmX; } diff --git a/intern/libmv/libmv/image/image_test.cc b/intern/libmv/libmv/image/image_test.cc index 241f49f2244..a1730a9a55e 100644 --- a/intern/libmv/libmv/image/image_test.cc +++ b/intern/libmv/libmv/image/image_test.cc @@ -23,20 +23,20 @@ #include "libmv/image/image.h" #include "testing/testing.h" -using libmv::Image; using libmv::Array3Df; +using libmv::Image; namespace { TEST(Image, SimpleImageAccessors) { - Array3Df *array = new Array3Df(2, 3); + Array3Df* array = new Array3Df(2, 3); Image image(array); EXPECT_EQ(array, image.AsArray3Df()); EXPECT_TRUE(NULL == image.AsArray3Du()); } TEST(Image, MemorySizeInBytes) { - Array3Df *array = new Array3Df(2, 3); + Array3Df* array = new Array3Df(2, 3); Image image(array); int size = sizeof(image) + array->MemorySizeInBytes(); EXPECT_EQ(size, image.MemorySizeInBytes()); diff --git a/intern/libmv/libmv/image/sample.h b/intern/libmv/libmv/image/sample.h index 24eb9ccd57d..2b57baf27b9 100644 --- a/intern/libmv/libmv/image/sample.h +++ b/intern/libmv/libmv/image/sample.h @@ -26,17 +26,14 @@ namespace libmv { /// Nearest neighbor interpolation. -template<typename T> -inline T SampleNearest(const Array3D<T> &image, - float y, float x, int v = 0) { +template <typename T> +inline T SampleNearest(const Array3D<T>& image, float y, float x, int v = 0) { const int i = int(round(y)); const int j = int(round(x)); return image(i, j, v); } -inline void LinearInitAxis(float x, int size, - int *x1, int *x2, - float *dx) { +inline void LinearInitAxis(float x, int size, int* x1, int* x2, float* dx) { const int ix = static_cast<int>(x); if (ix < 0) { *x1 = 0; @@ -54,32 +51,32 @@ inline void LinearInitAxis(float x, int size, } /// Linear interpolation. -template<typename T> -inline T SampleLinear(const Array3D<T> &image, float y, float x, int v = 0) { +template <typename T> +inline T SampleLinear(const Array3D<T>& image, float y, float x, int v = 0) { int x1, y1, x2, y2; float dx, dy; LinearInitAxis(y, image.Height(), &y1, &y2, &dy); - LinearInitAxis(x, image.Width(), &x1, &x2, &dx); + LinearInitAxis(x, image.Width(), &x1, &x2, &dx); const T im11 = image(y1, x1, v); const T im12 = image(y1, x2, v); const T im21 = image(y2, x1, v); const T im22 = image(y2, x2, v); - return T( dy * (dx * im11 + (1.0 - dx) * im12) + + return T(dy * (dx * im11 + (1.0 - dx) * im12) + (1 - dy) * (dx * im21 + (1.0 - dx) * im22)); } /// Linear interpolation, of all channels. The sample is assumed to have the /// same size as the number of channels in image. -template<typename T> -inline void SampleLinear(const Array3D<T> &image, float y, float x, T *sample) { +template <typename T> +inline void SampleLinear(const Array3D<T>& image, float y, float x, T* sample) { int x1, y1, x2, y2; float dx, dy; LinearInitAxis(y, image.Height(), &y1, &y2, &dy); - LinearInitAxis(x, image.Width(), &x1, &x2, &dx); + LinearInitAxis(x, image.Width(), &x1, &x2, &dx); for (int i = 0; i < image.Depth(); ++i) { const T im11 = image(y1, x1, i); @@ -87,7 +84,7 @@ inline void SampleLinear(const Array3D<T> &image, float y, float x, T *sample) { const T im21 = image(y2, x1, i); const T im22 = image(y2, x2, i); - sample[i] = T( dy * (dx * im11 + (1.0 - dx) * im12) + + sample[i] = T(dy * (dx * im11 + (1.0 - dx) * im12) + (1 - dy) * (dx * im21 + (1.0 - dx) * im22)); } } @@ -95,7 +92,7 @@ inline void SampleLinear(const Array3D<T> &image, float y, float x, T *sample) { // Downsample all channels by 2. If the image has odd width or height, the last // row or column is ignored. // FIXME(MatthiasF): this implementation shouldn't be in an interface file -inline void DownsampleChannelsBy2(const Array3Df &in, Array3Df *out) { +inline void DownsampleChannelsBy2(const Array3Df& in, Array3Df* out) { int height = in.Height() / 2; int width = in.Width() / 2; int depth = in.Depth(); @@ -106,10 +103,12 @@ inline void DownsampleChannelsBy2(const Array3Df &in, Array3Df *out) { for (int r = 0; r < height; ++r) { for (int c = 0; c < width; ++c) { for (int k = 0; k < depth; ++k) { + // clang-format off (*out)(r, c, k) = (in(2 * r, 2 * c, k) + in(2 * r + 1, 2 * c, k) + in(2 * r, 2 * c + 1, k) + in(2 * r + 1, 2 * c + 1, k)) / 4.0f; + // clang-format on } } } @@ -117,11 +116,12 @@ inline void DownsampleChannelsBy2(const Array3Df &in, Array3Df *out) { // Sample a region centered at x,y in image with size extending by half_width // from x,y. Channels specifies the number of channels to sample from. -inline void SamplePattern(const FloatImage &image, - double x, double y, - int half_width, - int channels, - FloatImage *sampled) { +inline void SamplePattern(const FloatImage& image, + double x, + double y, + int half_width, + int channels, + FloatImage* sampled) { sampled->Resize(2 * half_width + 1, 2 * half_width + 1, channels); for (int r = -half_width; r <= half_width; ++r) { for (int c = -half_width; c <= half_width; ++c) { diff --git a/intern/libmv/libmv/image/sample_test.cc b/intern/libmv/libmv/image/sample_test.cc index c8a0ce470c2..f1fb4c42c67 100644 --- a/intern/libmv/libmv/image/sample_test.cc +++ b/intern/libmv/libmv/image/sample_test.cc @@ -32,9 +32,9 @@ TEST(Image, Nearest) { image(1, 0) = 2; image(1, 1) = 3; EXPECT_EQ(0, SampleNearest(image, -0.4f, -0.4f)); - EXPECT_EQ(0, SampleNearest(image, 0.4f, 0.4f)); - EXPECT_EQ(3, SampleNearest(image, 0.6f, 0.6f)); - EXPECT_EQ(3, SampleNearest(image, 1.4f, 1.4f)); + EXPECT_EQ(0, SampleNearest(image, 0.4f, 0.4f)); + EXPECT_EQ(3, SampleNearest(image, 0.6f, 0.6f)); + EXPECT_EQ(3, SampleNearest(image, 1.4f, 1.4f)); } TEST(Image, Linear) { @@ -57,7 +57,7 @@ TEST(Image, DownsampleBy2) { ASSERT_EQ(1, resampled_image.Height()); ASSERT_EQ(1, resampled_image.Width()); ASSERT_EQ(1, resampled_image.Depth()); - EXPECT_FLOAT_EQ(6./4., resampled_image(0, 0)); + EXPECT_FLOAT_EQ(6. / 4., resampled_image(0, 0)); } TEST(Image, DownsampleBy2MultiChannel) { @@ -82,8 +82,8 @@ TEST(Image, DownsampleBy2MultiChannel) { ASSERT_EQ(1, resampled_image.Height()); ASSERT_EQ(1, resampled_image.Width()); ASSERT_EQ(3, resampled_image.Depth()); - EXPECT_FLOAT_EQ((0+1+2+3)/4., resampled_image(0, 0, 0)); - EXPECT_FLOAT_EQ((5+6+7+8)/4., resampled_image(0, 0, 1)); - EXPECT_FLOAT_EQ((9+10+11+12)/4., resampled_image(0, 0, 2)); + EXPECT_FLOAT_EQ((0 + 1 + 2 + 3) / 4., resampled_image(0, 0, 0)); + EXPECT_FLOAT_EQ((5 + 6 + 7 + 8) / 4., resampled_image(0, 0, 1)); + EXPECT_FLOAT_EQ((9 + 10 + 11 + 12) / 4., resampled_image(0, 0, 2)); } } // namespace diff --git a/intern/libmv/libmv/image/tuple.h b/intern/libmv/libmv/image/tuple.h index c8dc36f2e18..447bf0cc81c 100644 --- a/intern/libmv/libmv/image/tuple.h +++ b/intern/libmv/libmv/image/tuple.h @@ -34,10 +34,14 @@ class Tuple { Tuple(T initial_value) { Reset(initial_value); } template <typename D> - Tuple(D *values) { Reset(values); } + Tuple(D* values) { + Reset(values); + } template <typename D> - Tuple(const Tuple<D, N> &b) { Reset(b); } + Tuple(const Tuple<D, N>& b) { + Reset(b); + } template <typename D> Tuple& operator=(const Tuple<D, N>& b) { @@ -46,30 +50,32 @@ class Tuple { } template <typename D> - void Reset(const Tuple<D, N>& b) { Reset(b.Data()); } + void Reset(const Tuple<D, N>& b) { + Reset(b.Data()); + } template <typename D> - void Reset(D *values) { - for (int i = 0;i < N; i++) { + void Reset(D* values) { + for (int i = 0; i < N; i++) { data_[i] = T(values[i]); } } // Set all tuple values to the same thing. void Reset(T value) { - for (int i = 0;i < N; i++) { + for (int i = 0; i < N; i++) { data_[i] = value; } } // Pointer to the first element. - T *Data() { return &data_[0]; } - const T *Data() const { return &data_[0]; } + T* Data() { return &data_[0]; } + const T* Data() const { return &data_[0]; } - T &operator()(int i) { return data_[i]; } - const T &operator()(int i) const { return data_[i]; } + T& operator()(int i) { return data_[i]; } + const T& operator()(int i) const { return data_[i]; } - bool operator==(const Tuple<T, N> &other) const { + bool operator==(const Tuple<T, N>& other) const { for (int i = 0; i < N; ++i) { if ((*this)(i) != other(i)) { return false; @@ -77,9 +83,7 @@ class Tuple { } return true; } - bool operator!=(const Tuple<T, N> &other) const { - return !(*this == other); - } + bool operator!=(const Tuple<T, N>& other) const { return !(*this == other); } private: T data_[N]; diff --git a/intern/libmv/libmv/multiview/conditioning.cc b/intern/libmv/libmv/multiview/conditioning.cc index 0afbf119ea3..2f4bf653ca0 100644 --- a/intern/libmv/libmv/multiview/conditioning.cc +++ b/intern/libmv/libmv/multiview/conditioning.cc @@ -24,7 +24,7 @@ namespace libmv { // HZ 4.4.4 pag.109: Point conditioning (non isotropic) -void PreconditionerFromPoints(const Mat &points, Mat3 *T) { +void PreconditionerFromPoints(const Mat& points, Mat3* T) { Vec mean, variance; MeanAndVarianceAlongRows(points, &mean, &variance); @@ -38,12 +38,14 @@ void PreconditionerFromPoints(const Mat &points, Mat3 *T) { if (variance(1) < 1e-8) yfactor = mean(1) = 1.0; + // clang-format off *T << xfactor, 0, -xfactor * mean(0), 0, yfactor, -yfactor * mean(1), 0, 0, 1; + // clang-format on } // HZ 4.4.4 pag.107: Point conditioning (isotropic) -void IsotropicPreconditionerFromPoints(const Mat &points, Mat3 *T) { +void IsotropicPreconditionerFromPoints(const Mat& points, Mat3* T) { Vec mean, variance; MeanAndVarianceAlongRows(points, &mean, &variance); @@ -57,14 +59,16 @@ void IsotropicPreconditionerFromPoints(const Mat &points, Mat3 *T) { mean.setOnes(); } + // clang-format off *T << factor, 0, -factor * mean(0), 0, factor, -factor * mean(1), 0, 0, 1; + // clang-format on } -void ApplyTransformationToPoints(const Mat &points, - const Mat3 &T, - Mat *transformed_points) { +void ApplyTransformationToPoints(const Mat& points, + const Mat3& T, + Mat* transformed_points) { int n = points.cols(); transformed_points->resize(2, n); Mat3X p(3, n); @@ -73,26 +77,24 @@ void ApplyTransformationToPoints(const Mat &points, HomogeneousToEuclidean(p, transformed_points); } -void NormalizePoints(const Mat &points, - Mat *normalized_points, - Mat3 *T) { +void NormalizePoints(const Mat& points, Mat* normalized_points, Mat3* T) { PreconditionerFromPoints(points, T); ApplyTransformationToPoints(points, *T, normalized_points); } -void NormalizeIsotropicPoints(const Mat &points, - Mat *normalized_points, - Mat3 *T) { +void NormalizeIsotropicPoints(const Mat& points, + Mat* normalized_points, + Mat3* T) { IsotropicPreconditionerFromPoints(points, T); ApplyTransformationToPoints(points, *T, normalized_points); } // Denormalize the results. See HZ page 109. -void UnnormalizerT::Unnormalize(const Mat3 &T1, const Mat3 &T2, Mat3 *H) { +void UnnormalizerT::Unnormalize(const Mat3& T1, const Mat3& T2, Mat3* H) { *H = T2.transpose() * (*H) * T1; } -void UnnormalizerI::Unnormalize(const Mat3 &T1, const Mat3 &T2, Mat3 *H) { +void UnnormalizerI::Unnormalize(const Mat3& T1, const Mat3& T2, Mat3* H) { *H = T2.inverse() * (*H) * T1; } diff --git a/intern/libmv/libmv/multiview/conditioning.h b/intern/libmv/libmv/multiview/conditioning.h index 8f3e3a76070..876c5af48e6 100644 --- a/intern/libmv/libmv/multiview/conditioning.h +++ b/intern/libmv/libmv/multiview/conditioning.h @@ -26,32 +26,30 @@ namespace libmv { // Point conditioning (non isotropic) -void PreconditionerFromPoints(const Mat &points, Mat3 *T); +void PreconditionerFromPoints(const Mat& points, Mat3* T); // Point conditioning (isotropic) -void IsotropicPreconditionerFromPoints(const Mat &points, Mat3 *T); +void IsotropicPreconditionerFromPoints(const Mat& points, Mat3* T); -void ApplyTransformationToPoints(const Mat &points, - const Mat3 &T, - Mat *transformed_points); +void ApplyTransformationToPoints(const Mat& points, + const Mat3& T, + Mat* transformed_points); -void NormalizePoints(const Mat &points, - Mat *normalized_points, - Mat3 *T); +void NormalizePoints(const Mat& points, Mat* normalized_points, Mat3* T); -void NormalizeIsotropicPoints(const Mat &points, - Mat *normalized_points, - Mat3 *T); +void NormalizeIsotropicPoints(const Mat& points, + Mat* normalized_points, + Mat3* T); /// Use inverse for unnormalize struct UnnormalizerI { // Denormalize the results. See HZ page 109. - static void Unnormalize(const Mat3 &T1, const Mat3 &T2, Mat3 *H); + static void Unnormalize(const Mat3& T1, const Mat3& T2, Mat3* H); }; /// Use transpose for unnormalize struct UnnormalizerT { // Denormalize the results. See HZ page 109. - static void Unnormalize(const Mat3 &T1, const Mat3 &T2, Mat3 *H); + static void Unnormalize(const Mat3& T1, const Mat3& T2, Mat3* H); }; } // namespace libmv diff --git a/intern/libmv/libmv/multiview/euclidean_resection.cc b/intern/libmv/libmv/multiview/euclidean_resection.cc index 16a1a0caafa..249d7ebef3d 100644 --- a/intern/libmv/libmv/multiview/euclidean_resection.cc +++ b/intern/libmv/libmv/multiview/euclidean_resection.cc @@ -23,8 +23,8 @@ #include <cmath> #include <limits> -#include <Eigen/SVD> #include <Eigen/Geometry> +#include <Eigen/SVD> #include "libmv/base/vector.h" #include "libmv/logging/logging.h" @@ -35,9 +35,10 @@ namespace euclidean_resection { typedef unsigned int uint; -bool EuclideanResection(const Mat2X &x_camera, - const Mat3X &X_world, - Mat3 *R, Vec3 *t, +bool EuclideanResection(const Mat2X& x_camera, + const Mat3X& X_world, + Mat3* R, + Vec3* t, ResectionMethod method) { switch (method) { case RESECTION_ANSAR_DANIILIDIS: @@ -49,20 +50,20 @@ bool EuclideanResection(const Mat2X &x_camera, case RESECTION_PPNP: return EuclideanResectionPPnP(x_camera, X_world, R, t); break; - default: - LOG(FATAL) << "Unknown resection method."; + default: LOG(FATAL) << "Unknown resection method."; } return false; } -bool EuclideanResection(const Mat &x_image, - const Mat3X &X_world, - const Mat3 &K, - Mat3 *R, Vec3 *t, +bool EuclideanResection(const Mat& x_image, + const Mat3X& X_world, + const Mat3& K, + Mat3* R, + Vec3* t, ResectionMethod method) { CHECK(x_image.rows() == 2 || x_image.rows() == 3) - << "Invalid size for x_image: " - << x_image.rows() << "x" << x_image.cols(); + << "Invalid size for x_image: " << x_image.rows() << "x" + << x_image.cols(); Mat2X x_camera; if (x_image.rows() == 2) { @@ -73,18 +74,15 @@ bool EuclideanResection(const Mat &x_image, return EuclideanResection(x_camera, X_world, R, t, method); } -void AbsoluteOrientation(const Mat3X &X, - const Mat3X &Xp, - Mat3 *R, - Vec3 *t) { +void AbsoluteOrientation(const Mat3X& X, const Mat3X& Xp, Mat3* R, Vec3* t) { int num_points = X.cols(); - Vec3 C = X.rowwise().sum() / num_points; // Centroid of X. + Vec3 C = X.rowwise().sum() / num_points; // Centroid of X. Vec3 Cp = Xp.rowwise().sum() / num_points; // Centroid of Xp. // Normalize the two point sets. Mat3X Xn(3, num_points), Xpn(3, num_points); for (int i = 0; i < num_points; ++i) { - Xn.col(i) = X.col(i) - C; + Xn.col(i) = X.col(i) - C; Xpn.col(i) = Xp.col(i) - Cp; } @@ -100,10 +98,12 @@ void AbsoluteOrientation(const Mat3X &X, double Szy = Xn.row(2).dot(Xpn.row(1)); Mat4 N; + // clang-format off N << Sxx + Syy + Szz, Syz - Szy, Szx - Sxz, Sxy - Syx, Syz - Szy, Sxx - Syy - Szz, Sxy + Syx, Szx + Sxz, Szx - Sxz, Sxy + Syx, -Sxx + Syy - Szz, Syz + Szy, Sxy - Syx, Szx + Sxz, Syz + Szy, -Sxx - Syy + Szz; + // clang-format on // Find the unit quaternion q that maximizes qNq. It is the eigenvector // corresponding to the lagest eigenvalue. @@ -118,6 +118,7 @@ void AbsoluteOrientation(const Mat3X &X, double q1q3 = q(1) * q(3); double q2q3 = q(2) * q(3); + // clang-format off (*R) << qq(0) + qq(1) - qq(2) - qq(3), 2 * (q1q2 - q0q3), 2 * (q1q3 + q0q2), @@ -127,6 +128,7 @@ void AbsoluteOrientation(const Mat3X &X, 2 * (q1q3 - q0q2), 2 * (q2q3 + q0q1), qq(0) - qq(1) - qq(2) + qq(3); + // clang-format on // Fix the handedness of the R matrix. if (R->determinant() < 0) { @@ -176,9 +178,7 @@ static int Sign(double value) { // Lambda to create the constraints in equation (5) in "Linear Pose Estimation // from Points or Lines", by Ansar, A. and Daniilidis, PAMI 2003. vol. 25, no. // 5. -static Vec MatrixToConstraint(const Mat &A, - int num_k_columns, - int num_lambda) { +static Vec MatrixToConstraint(const Mat& A, int num_k_columns, int num_lambda) { Vec C(num_k_columns); C.setZero(); int idx = 0; @@ -195,17 +195,17 @@ static Vec MatrixToConstraint(const Mat &A, } // Normalizes the columns of vectors. -static void NormalizeColumnVectors(Mat3X *vectors) { +static void NormalizeColumnVectors(Mat3X* vectors) { int num_columns = vectors->cols(); for (int i = 0; i < num_columns; ++i) { vectors->col(i).normalize(); } } -void EuclideanResectionAnsarDaniilidis(const Mat2X &x_camera, - const Mat3X &X_world, - Mat3 *R, - Vec3 *t) { +void EuclideanResectionAnsarDaniilidis(const Mat2X& x_camera, + const Mat3X& X_world, + Mat3* R, + Vec3* t) { CHECK(x_camera.cols() == X_world.cols()); CHECK(x_camera.cols() > 3); @@ -229,14 +229,14 @@ void EuclideanResectionAnsarDaniilidis(const Mat2X &x_camera, // them into the M matrix (8). Also store the initial (i, j) indices. int row = 0; for (int i = 0; i < num_points; ++i) { - for (int j = i+1; j < num_points; ++j) { + for (int j = i + 1; j < num_points; ++j) { M(row, row) = -2 * x_camera_unit.col(i).dot(x_camera_unit.col(j)); M(row, num_m_rows + i) = x_camera_unit.col(i).dot(x_camera_unit.col(i)); M(row, num_m_rows + j) = x_camera_unit.col(j).dot(x_camera_unit.col(j)); Vec3 Xdiff = X_world.col(i) - X_world.col(j); double center_to_point_distance = Xdiff.norm(); M(row, num_m_columns - 1) = - - center_to_point_distance * center_to_point_distance; + -center_to_point_distance * center_to_point_distance; ij_index(row, 0) = i; ij_index(row, 1) = j; ++row; @@ -246,17 +246,17 @@ void EuclideanResectionAnsarDaniilidis(const Mat2X &x_camera, } int num_lambda = num_points + 1; // Dimension of the null space of M. - Mat V = M.jacobiSvd(Eigen::ComputeFullV).matrixV().block(0, - num_m_rows, - num_m_columns, - num_lambda); + Mat V = M.jacobiSvd(Eigen::ComputeFullV) + .matrixV() + .block(0, num_m_rows, num_m_columns, num_lambda); // TODO(vess): The number of constraint equations in K (num_k_rows) must be // (num_points + 1) * (num_points + 2)/2. This creates a performance issue // for more than 4 points. It is fine for 4 points at the moment with 18 // instead of 15 equations. - int num_k_rows = num_m_rows + num_points * - (num_points*(num_points-1)/2 - num_points+1); + int num_k_rows = + num_m_rows + + num_points * (num_points * (num_points - 1) / 2 - num_points + 1); int num_k_columns = num_lambda * (num_lambda + 1) / 2; Mat K(num_k_rows, num_k_columns); K.setZero(); @@ -275,8 +275,8 @@ void EuclideanResectionAnsarDaniilidis(const Mat2X &x_camera, int idx4 = IJToPointIndex(i, k, num_points); K.row(counter_k_row) = - MatrixToConstraint(V.row(idx1).transpose() * V.row(idx2)- - V.row(idx3).transpose() * V.row(idx4), + MatrixToConstraint(V.row(idx1).transpose() * V.row(idx2) - + V.row(idx3).transpose() * V.row(idx4), num_k_columns, num_lambda); ++counter_k_row; @@ -296,8 +296,8 @@ void EuclideanResectionAnsarDaniilidis(const Mat2X &x_camera, int idx4 = IJToPointIndex(i, k, num_points); K.row(counter_k_row) = - MatrixToConstraint(V.row(idx1).transpose() * V.row(idx2)- - V.row(idx3).transpose() * V.row(idx4), + MatrixToConstraint(V.row(idx1).transpose() * V.row(idx2) - + V.row(idx3).transpose() * V.row(idx4), num_k_columns, num_lambda); ++counter_k_row; @@ -317,14 +317,12 @@ void EuclideanResectionAnsarDaniilidis(const Mat2X &x_camera, } } // Ensure positiveness of the largest value corresponding to lambda_ii. - L_sq = L_sq * Sign(L_sq(IJToIndex(max_L_sq_index, - max_L_sq_index, - num_lambda))); + L_sq = + L_sq * Sign(L_sq(IJToIndex(max_L_sq_index, max_L_sq_index, num_lambda))); Vec L(num_lambda); - L(max_L_sq_index) = sqrt(L_sq(IJToIndex(max_L_sq_index, - max_L_sq_index, - num_lambda))); + L(max_L_sq_index) = + sqrt(L_sq(IJToIndex(max_L_sq_index, max_L_sq_index, num_lambda))); for (int i = 0; i < num_lambda; ++i) { if (i != max_L_sq_index) { @@ -353,9 +351,9 @@ void EuclideanResectionAnsarDaniilidis(const Mat2X &x_camera, } // Selects 4 virtual control points using mean and PCA. -static void SelectControlPoints(const Mat3X &X_world, - Mat *X_centered, - Mat34 *X_control_points) { +static void SelectControlPoints(const Mat3X& X_world, + Mat* X_centered, + Mat34* X_control_points) { size_t num_points = X_world.cols(); // The first virtual control point, C0, is the centroid. @@ -379,13 +377,13 @@ static void SelectControlPoints(const Mat3X &X_world, } // Computes the barycentric coordinates for all real points -static void ComputeBarycentricCoordinates(const Mat3X &X_world_centered, - const Mat34 &X_control_points, - Mat4X *alphas) { +static void ComputeBarycentricCoordinates(const Mat3X& X_world_centered, + const Mat34& X_control_points, + Mat4X* alphas) { size_t num_points = X_world_centered.cols(); Mat3 C2; for (size_t c = 1; c < 4; c++) { - C2.col(c-1) = X_control_points.col(c) - X_control_points.col(0); + C2.col(c - 1) = X_control_points.col(c) - X_control_points.col(0); } Mat3 C2inv = C2.inverse(); @@ -401,14 +399,15 @@ static void ComputeBarycentricCoordinates(const Mat3X &X_world_centered, // Estimates the coordinates of all real points in the camera coordinate frame static void ComputePointsCoordinatesInCameraFrame( - const Mat4X &alphas, - const Vec4 &betas, - const Eigen::Matrix<double, 12, 12> &U, - Mat3X *X_camera) { + const Mat4X& alphas, + const Vec4& betas, + const Eigen::Matrix<double, 12, 12>& U, + Mat3X* X_camera) { size_t num_points = alphas.cols(); // Estimates the control points in the camera reference frame. - Mat34 C2b; C2b.setZero(); + Mat34 C2b; + C2b.setZero(); for (size_t cu = 0; cu < 4; cu++) { for (size_t c = 0; c < 4; c++) { C2b.col(c) += betas(cu) * U.block(11 - cu, c * 3, 1, 3).transpose(); @@ -436,9 +435,10 @@ static void ComputePointsCoordinatesInCameraFrame( } } -bool EuclideanResectionEPnP(const Mat2X &x_camera, - const Mat3X &X_world, - Mat3 *R, Vec3 *t) { +bool EuclideanResectionEPnP(const Mat2X& x_camera, + const Mat3X& X_world, + Mat3* R, + Vec3* t) { CHECK(x_camera.cols() == X_world.cols()); CHECK(x_camera.cols() > 3); size_t num_points = X_world.cols(); @@ -462,6 +462,7 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera, double a3 = alphas(3, c); double ui = x_camera(0, c); double vi = x_camera(1, c); + // clang-format off M.block(2*c, 0, 2, 12) << a0, 0, a0*(-ui), a1, 0, a1*(-ui), a2, 0, @@ -471,10 +472,11 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera, a1, a1*(-vi), 0, a2, a2*(-vi), 0, a3, a3*(-vi); + // clang-format on } // TODO(julien): Avoid the transpose by rewriting the u2.block() calls. - Eigen::JacobiSVD<Mat> MtMsvd(M.transpose()*M, Eigen::ComputeFullU); + Eigen::JacobiSVD<Mat> MtMsvd(M.transpose() * M, Eigen::ComputeFullU); Eigen::Matrix<double, 12, 12> u2 = MtMsvd.matrixU().transpose(); // Estimate the L matrix. @@ -495,21 +497,22 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera, dv2.row(3) = u2.block(10, 3, 1, 3) - u2.block(10, 6, 1, 3); dv2.row(4) = u2.block(10, 3, 1, 3) - u2.block(10, 9, 1, 3); dv2.row(5) = u2.block(10, 6, 1, 3) - u2.block(10, 9, 1, 3); - dv3.row(0) = u2.block(9, 0, 1, 3) - u2.block(9, 3, 1, 3); - dv3.row(1) = u2.block(9, 0, 1, 3) - u2.block(9, 6, 1, 3); - dv3.row(2) = u2.block(9, 0, 1, 3) - u2.block(9, 9, 1, 3); - dv3.row(3) = u2.block(9, 3, 1, 3) - u2.block(9, 6, 1, 3); - dv3.row(4) = u2.block(9, 3, 1, 3) - u2.block(9, 9, 1, 3); - dv3.row(5) = u2.block(9, 6, 1, 3) - u2.block(9, 9, 1, 3); - dv4.row(0) = u2.block(8, 0, 1, 3) - u2.block(8, 3, 1, 3); - dv4.row(1) = u2.block(8, 0, 1, 3) - u2.block(8, 6, 1, 3); - dv4.row(2) = u2.block(8, 0, 1, 3) - u2.block(8, 9, 1, 3); - dv4.row(3) = u2.block(8, 3, 1, 3) - u2.block(8, 6, 1, 3); - dv4.row(4) = u2.block(8, 3, 1, 3) - u2.block(8, 9, 1, 3); - dv4.row(5) = u2.block(8, 6, 1, 3) - u2.block(8, 9, 1, 3); + dv3.row(0) = u2.block(9, 0, 1, 3) - u2.block(9, 3, 1, 3); + dv3.row(1) = u2.block(9, 0, 1, 3) - u2.block(9, 6, 1, 3); + dv3.row(2) = u2.block(9, 0, 1, 3) - u2.block(9, 9, 1, 3); + dv3.row(3) = u2.block(9, 3, 1, 3) - u2.block(9, 6, 1, 3); + dv3.row(4) = u2.block(9, 3, 1, 3) - u2.block(9, 9, 1, 3); + dv3.row(5) = u2.block(9, 6, 1, 3) - u2.block(9, 9, 1, 3); + dv4.row(0) = u2.block(8, 0, 1, 3) - u2.block(8, 3, 1, 3); + dv4.row(1) = u2.block(8, 0, 1, 3) - u2.block(8, 6, 1, 3); + dv4.row(2) = u2.block(8, 0, 1, 3) - u2.block(8, 9, 1, 3); + dv4.row(3) = u2.block(8, 3, 1, 3) - u2.block(8, 6, 1, 3); + dv4.row(4) = u2.block(8, 3, 1, 3) - u2.block(8, 9, 1, 3); + dv4.row(5) = u2.block(8, 6, 1, 3) - u2.block(8, 9, 1, 3); Eigen::Matrix<double, 6, 10> L; for (size_t r = 0; r < 6; r++) { + // clang-format off L.row(r) << dv1.row(r).dot(dv1.row(r)), 2.0 * dv1.row(r).dot(dv2.row(r)), dv2.row(r).dot(dv2.row(r)), @@ -520,19 +523,23 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera, 2.0 * dv2.row(r).dot(dv4.row(r)), 2.0 * dv3.row(r).dot(dv4.row(r)), dv4.row(r).dot(dv4.row(r)); + // clang-format on } Vec6 rho; + // clang-format off rho << (X_control_points.col(0) - X_control_points.col(1)).squaredNorm(), (X_control_points.col(0) - X_control_points.col(2)).squaredNorm(), (X_control_points.col(0) - X_control_points.col(3)).squaredNorm(), (X_control_points.col(1) - X_control_points.col(2)).squaredNorm(), (X_control_points.col(1) - X_control_points.col(3)).squaredNorm(), (X_control_points.col(2) - X_control_points.col(3)).squaredNorm(); + // clang-format on // There are three possible solutions based on the three approximations of L // (betas). Below, each one is solved for then the best one is chosen. Mat3X X_camera; - Mat3 K; K.setIdentity(); + Mat3 K; + K.setIdentity(); vector<Mat3> Rs(3); vector<Vec3> ts(3); Vec rmse(3); @@ -546,7 +553,7 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera, // // TODO(keir): Decide if setting this to infinity, effectively disabling the // check, is the right approach. So far this seems the case. - double kSuccessThreshold = std::numeric_limits<double>::max(); + double kSuccessThreshold = std::numeric_limits<double>::max(); // Find the first possible solution for R, t corresponding to: // Betas = [b00 b01 b11 b02 b12 b22 b03 b13 b23 b33] @@ -563,7 +570,7 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera, if (b4(0) < 0) { b4 = -b4; } - b4(0) = std::sqrt(b4(0)); + b4(0) = std::sqrt(b4(0)); betas << b4(0), b4(1) / b4(0), b4(2) / b4(0), b4(3) / b4(0); ComputePointsCoordinatesInCameraFrame(alphas, betas, u2, &X_camera); AbsoluteOrientation(X_world, X_camera, &Rs[0], &ts[0]); @@ -669,12 +676,12 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera, // TODO(julien): Improve the solutions with non-linear refinement. return true; } - + /* - + Straight from the paper: http://www.diegm.uniud.it/fusiello/papers/3dimpvt12-b.pdf - + function [R T] = ppnp(P,S,tol) % input % P : matrix (nx3) image coordinates in camera reference [u v 1] @@ -708,33 +715,34 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera, end T = -R*c; end - + */ // TODO(keir): Re-do all the variable names and add comments matching the paper. // This implementation has too much of the terseness of the original. On the // other hand, it did work on the first try. -bool EuclideanResectionPPnP(const Mat2X &x_camera, - const Mat3X &X_world, - Mat3 *R, Vec3 *t) { +bool EuclideanResectionPPnP(const Mat2X& x_camera, + const Mat3X& X_world, + Mat3* R, + Vec3* t) { int n = x_camera.cols(); Mat Z = Mat::Zero(n, n); Vec e = Vec::Ones(n); Mat A = Mat::Identity(n, n) - (e * e.transpose() / n); Vec II = e / n; - + Mat P(n, 3); P.col(0) = x_camera.row(0); P.col(1) = x_camera.row(1); P.col(2).setConstant(1.0); - + Mat S = X_world.transpose(); - + double error = std::numeric_limits<double>::infinity(); Mat E_old = 1000 * Mat::Ones(n, 3); - + Vec3 c; Mat E(n, 3); - + int iteration = 0; double tolerance = 1e-5; // TODO(keir): The limit of 100 can probably be reduced, but this will require @@ -748,20 +756,21 @@ bool EuclideanResectionPPnP(const Mat2X &x_camera, s << 1, 1, (U * VT).determinant(); *R = U * s.asDiagonal() * VT; Mat PR = P * *R; // n x 3 - c = (S - Z*PR).transpose() * II; - Mat Y = S - e*c.transpose(); // n x 3 - Vec Zmindiag = (PR * Y.transpose()).diagonal() - .cwiseQuotient(P.rowwise().squaredNorm()); + c = (S - Z * PR).transpose() * II; + Mat Y = S - e * c.transpose(); // n x 3 + Vec Zmindiag = (PR * Y.transpose()) + .diagonal() + .cwiseQuotient(P.rowwise().squaredNorm()); for (int i = 0; i < n; ++i) { Zmindiag[i] = std::max(Zmindiag[i], 0.0); } Z = Zmindiag.asDiagonal(); - E = Y - Z*PR; + E = Y - Z * PR; error = (E - E_old).norm(); LG << "PPnP error(" << (iteration++) << "): " << error; E_old = E; } - *t = -*R*c; + *t = -*R * c; // TODO(keir): Figure out what the failure cases are. Is it too many // iterations? Spend some time going through the math figuring out if there @@ -769,6 +778,5 @@ bool EuclideanResectionPPnP(const Mat2X &x_camera, return true; } - -} // namespace resection +} // namespace euclidean_resection } // namespace libmv diff --git a/intern/libmv/libmv/multiview/euclidean_resection.h b/intern/libmv/libmv/multiview/euclidean_resection.h index 28eae92611c..3c4c3979ff6 100644 --- a/intern/libmv/libmv/multiview/euclidean_resection.h +++ b/intern/libmv/libmv/multiview/euclidean_resection.h @@ -21,8 +21,8 @@ #ifndef LIBMV_MULTIVIEW_EUCLIDEAN_RESECTION_H_ #define LIBMV_MULTIVIEW_EUCLIDEAN_RESECTION_H_ -#include "libmv/numeric/numeric.h" #include "libmv/multiview/projection.h" +#include "libmv/numeric/numeric.h" namespace libmv { namespace euclidean_resection { @@ -33,7 +33,7 @@ enum ResectionMethod { // The "EPnP" algorithm by Lepetit et al. // http://cvlab.epfl.ch/~lepetit/papers/lepetit_ijcv08.pdf RESECTION_EPNP, - + // The Procrustes PNP algorithm ("PPnP") // http://www.diegm.uniud.it/fusiello/papers/3dimpvt12-b.pdf RESECTION_PPNP @@ -50,9 +50,10 @@ enum ResectionMethod { * \param t Solution for the camera translation vector * \param method The resection method to use. */ -bool EuclideanResection(const Mat2X &x_camera, - const Mat3X &X_world, - Mat3 *R, Vec3 *t, +bool EuclideanResection(const Mat2X& x_camera, + const Mat3X& X_world, + Mat3* R, + Vec3* t, ResectionMethod method = RESECTION_EPNP); /** @@ -68,10 +69,11 @@ bool EuclideanResection(const Mat2X &x_camera, * \param t Solution for the camera translation vector * \param method Resection method */ -bool EuclideanResection(const Mat &x_image, - const Mat3X &X_world, - const Mat3 &K, - Mat3 *R, Vec3 *t, +bool EuclideanResection(const Mat& x_image, + const Mat3X& X_world, + const Mat3& K, + Mat3* R, + Vec3* t, ResectionMethod method = RESECTION_EPNP); /** @@ -84,10 +86,7 @@ bool EuclideanResection(const Mat &x_image, * Horn, Hilden, "Closed-form solution of absolute orientation using * orthonormal matrices" */ -void AbsoluteOrientation(const Mat3X &X, - const Mat3X &Xp, - Mat3 *R, - Vec3 *t); +void AbsoluteOrientation(const Mat3X& X, const Mat3X& Xp, Mat3* R, Vec3* t); /** * Computes the extrinsic parameters, R and t for a calibrated camera from 4 or @@ -102,9 +101,10 @@ void AbsoluteOrientation(const Mat3X &X, * This is the algorithm described in: "Linear Pose Estimation from Points or * Lines", by Ansar, A. and Daniilidis, PAMI 2003. vol. 25, no. 5. */ -void EuclideanResectionAnsarDaniilidis(const Mat2X &x_camera, - const Mat3X &X_world, - Mat3 *R, Vec3 *t); +void EuclideanResectionAnsarDaniilidis(const Mat2X& x_camera, + const Mat3X& X_world, + Mat3* R, + Vec3* t); /** * Computes the extrinsic parameters, R and t for a calibrated camera from 4 or * more 3D points and their images. @@ -120,9 +120,10 @@ void EuclideanResectionAnsarDaniilidis(const Mat2X &x_camera, * and F. Moreno-Noguer and P. Fua, IJCV 2009. vol. 81, no. 2 * \note: the non-linear optimization is not implemented here. */ -bool EuclideanResectionEPnP(const Mat2X &x_camera, - const Mat3X &X_world, - Mat3 *R, Vec3 *t); +bool EuclideanResectionEPnP(const Mat2X& x_camera, + const Mat3X& X_world, + Mat3* R, + Vec3* t); /** * Computes the extrinsic parameters, R and t for a calibrated camera from 4 or @@ -137,12 +138,12 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera, * Straight from the paper: * http://www.diegm.uniud.it/fusiello/papers/3dimpvt12-b.pdf */ -bool EuclideanResectionPPnP(const Mat2X &x_camera, - const Mat3X &X_world, - Mat3 *R, Vec3 *t); +bool EuclideanResectionPPnP(const Mat2X& x_camera, + const Mat3X& X_world, + Mat3* R, + Vec3* t); } // namespace euclidean_resection } // namespace libmv - #endif /* LIBMV_MULTIVIEW_EUCLIDEAN_RESECTION_H_ */ diff --git a/intern/libmv/libmv/multiview/euclidean_resection_test.cc b/intern/libmv/libmv/multiview/euclidean_resection_test.cc index 378837d3d2d..3bb8e6e1710 100644 --- a/intern/libmv/libmv/multiview/euclidean_resection_test.cc +++ b/intern/libmv/libmv/multiview/euclidean_resection_test.cc @@ -19,9 +19,9 @@ // IN THE SOFTWARE. #include "libmv/multiview/euclidean_resection.h" -#include "libmv/numeric/numeric.h" #include "libmv/logging/logging.h" #include "libmv/multiview/projection.h" +#include "libmv/numeric/numeric.h" #include "testing/testing.h" using namespace libmv::euclidean_resection; @@ -33,10 +33,10 @@ static void CreateCameraSystem(const Mat3& KK, const Vec& X_distances, const Mat3& R_input, const Vec3& T_input, - Mat2X *x_camera, - Mat3X *X_world, - Mat3 *R_expected, - Vec3 *T_expected) { + Mat2X* x_camera, + Mat3X* X_world, + Mat3* R_expected, + Vec3* T_expected) { int num_points = x_image.cols(); Mat3X x_unit_cam(3, num_points); @@ -76,9 +76,9 @@ TEST(AbsoluteOrientation, QuaternionSolution) { // Create a random translation and rotation. Mat3 R_input; - R_input = Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitZ()) - * Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitY()) - * Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitZ()); + R_input = Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitZ()) * + Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitY()) * + Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitZ()); Vec3 t_input; t_input.setRandom(); @@ -109,26 +109,29 @@ TEST(EuclideanResection, Points4KnownImagePointsRandomTranslationRotation) { image_dimensions << 1600, 1200; Mat3 KK; + // clang-format off KK << 2796, 0, 804, 0 , 2796, 641, 0, 0, 1; + // clang-format on // The real image points. int num_points = 4; Mat3X x_image(3, num_points); + // clang-format off x_image << 1164.06, 734.948, 749.599, 430.727, 681.386, 844.59, 496.315, 580.775, 1, 1, 1, 1; - + // clang-format on // A vector of the 4 distances to the 3D points. Vec X_distances = 100 * Vec::Random(num_points).array().abs(); // Create the random camera motion R and t that resection should recover. Mat3 R_input; - R_input = Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitZ()) - * Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitY()) - * Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitZ()); + R_input = Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitZ()) * + Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitY()) * + Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitZ()); Vec3 T_input; T_input.setRandom(); @@ -140,15 +143,21 @@ TEST(EuclideanResection, Points4KnownImagePointsRandomTranslationRotation) { Vec3 T_expected; Mat3X X_world; Mat2X x_camera; - CreateCameraSystem(KK, x_image, X_distances, R_input, T_input, - &x_camera, &X_world, &R_expected, &T_expected); + CreateCameraSystem(KK, + x_image, + X_distances, + R_input, + T_input, + &x_camera, + &X_world, + &R_expected, + &T_expected); // Finally, run the code under test. Mat3 R_output; Vec3 T_output; - EuclideanResection(x_camera, X_world, - &R_output, &T_output, - RESECTION_ANSAR_DANIILIDIS); + EuclideanResection( + x_camera, X_world, &R_output, &T_output, RESECTION_ANSAR_DANIILIDIS); EXPECT_MATRIX_NEAR(T_output, T_expected, 1e-5); EXPECT_MATRIX_NEAR(R_output, R_expected, 1e-7); @@ -173,9 +182,11 @@ TEST(EuclideanResection, Points4KnownImagePointsRandomTranslationRotation) { // TODO(jmichot): Reduce the code duplication here with the code above. TEST(EuclideanResection, Points6AllRandomInput) { Mat3 KK; + // clang-format off KK << 2796, 0, 804, 0 , 2796, 641, 0, 0, 1; + // clang-format on // Create random image points for a 1600x1200 image. int w = 1600; @@ -192,9 +203,9 @@ TEST(EuclideanResection, Points6AllRandomInput) { // Create the random camera motion R and t that resection should recover. Mat3 R_input; - R_input = Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitZ()) - * Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitY()) - * Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitZ()); + R_input = Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitZ()) * + Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitY()) * + Eigen::AngleAxisd(rand(), Eigen::Vector3d::UnitZ()); Vec3 T_input; T_input.setRandom(); @@ -204,33 +215,36 @@ TEST(EuclideanResection, Points6AllRandomInput) { Mat3 R_expected; Vec3 T_expected; Mat3X X_world; - CreateCameraSystem(KK, x_image, X_distances, R_input, T_input, - &x_camera, &X_world, &R_expected, &T_expected); + CreateCameraSystem(KK, + x_image, + X_distances, + R_input, + T_input, + &x_camera, + &X_world, + &R_expected, + &T_expected); // Test each of the resection methods. { Mat3 R_output; Vec3 T_output; - EuclideanResection(x_camera, X_world, - &R_output, &T_output, - RESECTION_ANSAR_DANIILIDIS); + EuclideanResection( + x_camera, X_world, &R_output, &T_output, RESECTION_ANSAR_DANIILIDIS); EXPECT_MATRIX_NEAR(T_output, T_expected, 1e-5); EXPECT_MATRIX_NEAR(R_output, R_expected, 1e-7); } { Mat3 R_output; Vec3 T_output; - EuclideanResection(x_camera, X_world, - &R_output, &T_output, - RESECTION_EPNP); + EuclideanResection(x_camera, X_world, &R_output, &T_output, RESECTION_EPNP); EXPECT_MATRIX_NEAR(T_output, T_expected, 1e-5); EXPECT_MATRIX_NEAR(R_output, R_expected, 1e-7); } { Mat3 R_output; Vec3 T_output; - EuclideanResection(x_image, X_world, KK, - &R_output, &T_output); + EuclideanResection(x_image, X_world, KK, &R_output, &T_output); EXPECT_MATRIX_NEAR(T_output, T_expected, 1e-5); EXPECT_MATRIX_NEAR(R_output, R_expected, 1e-7); } diff --git a/intern/libmv/libmv/multiview/fundamental.cc b/intern/libmv/libmv/multiview/fundamental.cc index ea8594c8cc0..c8c94ecd7bb 100644 --- a/intern/libmv/libmv/multiview/fundamental.cc +++ b/intern/libmv/libmv/multiview/fundamental.cc @@ -22,15 +22,15 @@ #include "ceres/ceres.h" #include "libmv/logging/logging.h" -#include "libmv/numeric/numeric.h" -#include "libmv/numeric/poly.h" #include "libmv/multiview/conditioning.h" #include "libmv/multiview/projection.h" #include "libmv/multiview/triangulation.h" +#include "libmv/numeric/numeric.h" +#include "libmv/numeric/poly.h" namespace libmv { -static void EliminateRow(const Mat34 &P, int row, Mat *X) { +static void EliminateRow(const Mat34& P, int row, Mat* X) { X->resize(2, 4); int first_row = (row + 1) % 3; @@ -42,7 +42,7 @@ static void EliminateRow(const Mat34 &P, int row, Mat *X) { } } -void ProjectionsFromFundamental(const Mat3 &F, Mat34 *P1, Mat34 *P2) { +void ProjectionsFromFundamental(const Mat3& F, Mat34* P1, Mat34* P2) { *P1 << Mat3::Identity(), Vec3::Zero(); Vec3 e2; Mat3 Ft = F.transpose(); @@ -51,7 +51,7 @@ void ProjectionsFromFundamental(const Mat3 &F, Mat34 *P1, Mat34 *P2) { } // Addapted from vgg_F_from_P. -void FundamentalFromProjections(const Mat34 &P1, const Mat34 &P2, Mat3 *F) { +void FundamentalFromProjections(const Mat34& P1, const Mat34& P2, Mat3* F) { Mat X[3]; Mat Y[3]; Mat XY; @@ -71,7 +71,7 @@ void FundamentalFromProjections(const Mat34 &P1, const Mat34 &P2, Mat3 *F) { // HZ 11.1 pag.279 (x1 = x, x2 = x') // http://www.cs.unc.edu/~marc/tutorial/node54.html -static double EightPointSolver(const Mat &x1, const Mat &x2, Mat3 *F) { +static double EightPointSolver(const Mat& x1, const Mat& x2, Mat3* F) { DCHECK_EQ(x1.rows(), 2); DCHECK_GE(x1.cols(), 8); DCHECK_EQ(x1.rows(), x2.rows()); @@ -98,7 +98,7 @@ static double EightPointSolver(const Mat &x1, const Mat &x2, Mat3 *F) { } // HZ 11.1.1 pag.280 -void EnforceFundamentalRank2Constraint(Mat3 *F) { +void EnforceFundamentalRank2Constraint(Mat3* F) { Eigen::JacobiSVD<Mat3> USV(*F, Eigen::ComputeFullU | Eigen::ComputeFullV); Vec3 d = USV.singularValues(); d(2) = 0.0; @@ -106,9 +106,7 @@ void EnforceFundamentalRank2Constraint(Mat3 *F) { } // HZ 11.2 pag.281 (x1 = x, x2 = x') -double NormalizedEightPointSolver(const Mat &x1, - const Mat &x2, - Mat3 *F) { +double NormalizedEightPointSolver(const Mat& x1, const Mat& x2, Mat3* F) { DCHECK_EQ(x1.rows(), 2); DCHECK_GE(x1.cols(), 8); DCHECK_EQ(x1.rows(), x2.rows()); @@ -135,9 +133,9 @@ double NormalizedEightPointSolver(const Mat &x1, // Seven-point algorithm. // http://www.cs.unc.edu/~marc/tutorial/node55.html -double FundamentalFrom7CorrespondencesLinear(const Mat &x1, - const Mat &x2, - std::vector<Mat3> *F) { +double FundamentalFrom7CorrespondencesLinear(const Mat& x1, + const Mat& x2, + std::vector<Mat3>* F) { DCHECK_EQ(x1.rows(), 2); DCHECK_EQ(x1.cols(), 7); DCHECK_EQ(x1.rows(), x2.rows()); @@ -169,25 +167,29 @@ double FundamentalFrom7CorrespondencesLinear(const Mat &x1, // Then, use the condition det(F) = 0 to determine F. In other words, solve // det(F1 + a*F2) = 0 for a. - double a = F1(0, 0), j = F2(0, 0), - b = F1(0, 1), k = F2(0, 1), - c = F1(0, 2), l = F2(0, 2), - d = F1(1, 0), m = F2(1, 0), - e = F1(1, 1), n = F2(1, 1), - f = F1(1, 2), o = F2(1, 2), - g = F1(2, 0), p = F2(2, 0), - h = F1(2, 1), q = F2(2, 1), - i = F1(2, 2), r = F2(2, 2); + double a = F1(0, 0), j = F2(0, 0); + double b = F1(0, 1), k = F2(0, 1); + double c = F1(0, 2), l = F2(0, 2); + double d = F1(1, 0), m = F2(1, 0); + double e = F1(1, 1), n = F2(1, 1); + double f = F1(1, 2), o = F2(1, 2); + double g = F1(2, 0), p = F2(2, 0); + double h = F1(2, 1), q = F2(2, 1); + double i = F1(2, 2), r = F2(2, 2); // Run fundamental_7point_coeffs.py to get the below coefficients. // The coefficients are in ascending powers of alpha, i.e. P[N]*x^N. double P[4] = { - a*e*i + b*f*g + c*d*h - a*f*h - b*d*i - c*e*g, - a*e*r + a*i*n + b*f*p + b*g*o + c*d*q + c*h*m + d*h*l + e*i*j + f*g*k - - a*f*q - a*h*o - b*d*r - b*i*m - c*e*p - c*g*n - d*i*k - e*g*l - f*h*j, - a*n*r + b*o*p + c*m*q + d*l*q + e*j*r + f*k*p + g*k*o + h*l*m + i*j*n - - a*o*q - b*m*r - c*n*p - d*k*r - e*l*p - f*j*q - g*l*n - h*j*o - i*k*m, - j*n*r + k*o*p + l*m*q - j*o*q - k*m*r - l*n*p, + a * e * i + b * f * g + c * d * h - a * f * h - b * d * i - c * e * g, + a * e * r + a * i * n + b * f * p + b * g * o + c * d * q + c * h * m + + d * h * l + e * i * j + f * g * k - a * f * q - a * h * o - + b * d * r - b * i * m - c * e * p - c * g * n - d * i * k - + e * g * l - f * h * j, + a * n * r + b * o * p + c * m * q + d * l * q + e * j * r + f * k * p + + g * k * o + h * l * m + i * j * n - a * o * q - b * m * r - + c * n * p - d * k * r - e * l * p - f * j * q - g * l * n - + h * j * o - i * k * m, + j * n * r + k * o * p + l * m * q - j * o * q - k * m * r - l * n * p, }; // Solve for the roots of P[3]*x^3 + P[2]*x^2 + P[1]*x + P[0] = 0. @@ -195,15 +197,15 @@ double FundamentalFrom7CorrespondencesLinear(const Mat &x1, int num_roots = SolveCubicPolynomial(P, roots); // Build the fundamental matrix for each solution. - for (int kk = 0; kk < num_roots; ++kk) { + for (int kk = 0; kk < num_roots; ++kk) { F->push_back(F1 + roots[kk] * F2); } return s; } -double FundamentalFromCorrespondences7Point(const Mat &x1, - const Mat &x2, - std::vector<Mat3> *F) { +double FundamentalFromCorrespondences7Point(const Mat& x1, + const Mat& x2, + std::vector<Mat3>* F) { DCHECK_EQ(x1.rows(), 2); DCHECK_GE(x1.cols(), 7); DCHECK_EQ(x1.rows(), x2.rows()); @@ -218,25 +220,25 @@ double FundamentalFromCorrespondences7Point(const Mat &x1, ApplyTransformationToPoints(x2, T2, &x2_normalized); // Estimate the fundamental matrix. - double smaller_singular_value = - FundamentalFrom7CorrespondencesLinear(x1_normalized, x2_normalized, &(*F)); + double smaller_singular_value = FundamentalFrom7CorrespondencesLinear( + x1_normalized, x2_normalized, &(*F)); for (int k = 0; k < F->size(); ++k) { - Mat3 & Fmat = (*F)[k]; + Mat3& Fmat = (*F)[k]; // Denormalize the fundamental matrix. Fmat = T2.transpose() * Fmat * T1; } return smaller_singular_value; } -void NormalizeFundamental(const Mat3 &F, Mat3 *F_normalized) { +void NormalizeFundamental(const Mat3& F, Mat3* F_normalized) { *F_normalized = F / FrobeniusNorm(F); if ((*F_normalized)(2, 2) < 0) { *F_normalized *= -1; } } -double SampsonDistance(const Mat &F, const Vec2 &x1, const Vec2 &x2) { +double SampsonDistance(const Mat& F, const Vec2& x1, const Vec2& x2) { Vec3 x(x1(0), x1(1), 1.0); Vec3 y(x2(0), x2(1), 1.0); @@ -244,11 +246,11 @@ double SampsonDistance(const Mat &F, const Vec2 &x1, const Vec2 &x2) { Vec3 Ft_y = F.transpose() * y; double y_F_x = y.dot(F_x); - return Square(y_F_x) / ( F_x.head<2>().squaredNorm() - + Ft_y.head<2>().squaredNorm()); + return Square(y_F_x) / + (F_x.head<2>().squaredNorm() + Ft_y.head<2>().squaredNorm()); } -double SymmetricEpipolarDistance(const Mat &F, const Vec2 &x1, const Vec2 &x2) { +double SymmetricEpipolarDistance(const Mat& F, const Vec2& x1, const Vec2& x2) { Vec3 x(x1(0), x1(1), 1.0); Vec3 y(x2(0), x2(1), 1.0); @@ -256,43 +258,40 @@ double SymmetricEpipolarDistance(const Mat &F, const Vec2 &x1, const Vec2 &x2) { Vec3 Ft_y = F.transpose() * y; double y_F_x = y.dot(F_x); - return Square(y_F_x) * ( 1 / F_x.head<2>().squaredNorm() - + 1 / Ft_y.head<2>().squaredNorm()); + return Square(y_F_x) * + (1 / F_x.head<2>().squaredNorm() + 1 / Ft_y.head<2>().squaredNorm()); } // HZ 9.6 pag 257 (formula 9.12) -void EssentialFromFundamental(const Mat3 &F, - const Mat3 &K1, - const Mat3 &K2, - Mat3 *E) { +void EssentialFromFundamental(const Mat3& F, + const Mat3& K1, + const Mat3& K2, + Mat3* E) { *E = K2.transpose() * F * K1; } // HZ 9.6 pag 257 (formula 9.12) // Or http://ai.stanford.edu/~birch/projective/node20.html -void FundamentalFromEssential(const Mat3 &E, - const Mat3 &K1, - const Mat3 &K2, - Mat3 *F) { +void FundamentalFromEssential(const Mat3& E, + const Mat3& K1, + const Mat3& K2, + Mat3* F) { *F = K2.inverse().transpose() * E * K1.inverse(); } -void RelativeCameraMotion(const Mat3 &R1, - const Vec3 &t1, - const Mat3 &R2, - const Vec3 &t2, - Mat3 *R, - Vec3 *t) { +void RelativeCameraMotion(const Mat3& R1, + const Vec3& t1, + const Mat3& R2, + const Vec3& t2, + Mat3* R, + Vec3* t) { *R = R2 * R1.transpose(); *t = t2 - (*R) * t1; } // HZ 9.6 pag 257 -void EssentialFromRt(const Mat3 &R1, - const Vec3 &t1, - const Mat3 &R2, - const Vec3 &t2, - Mat3 *E) { +void EssentialFromRt( + const Mat3& R1, const Vec3& t1, const Mat3& R2, const Vec3& t2, Mat3* E) { Mat3 R; Vec3 t; RelativeCameraMotion(R1, t1, R2, t2, &R, &t); @@ -301,11 +300,11 @@ void EssentialFromRt(const Mat3 &R1, } // HZ 9.6 pag 259 (Result 9.19) -void MotionFromEssential(const Mat3 &E, - std::vector<Mat3> *Rs, - std::vector<Vec3> *ts) { +void MotionFromEssential(const Mat3& E, + std::vector<Mat3>* Rs, + std::vector<Vec3>* ts) { Eigen::JacobiSVD<Mat3> USV(E, Eigen::ComputeFullU | Eigen::ComputeFullV); - Mat3 U = USV.matrixU(); + Mat3 U = USV.matrixU(); Mat3 Vt = USV.matrixV().transpose(); // Last column of U is undetermined since d = (a a 0). @@ -318,9 +317,11 @@ void MotionFromEssential(const Mat3 &E, } Mat3 W; + // clang-format off W << 0, -1, 0, 1, 0, 0, 0, 0, 1; + // clang-format on Mat3 U_W_Vt = U * W * Vt; Mat3 U_Wt_Vt = U * W.transpose() * Vt; @@ -332,18 +333,18 @@ void MotionFromEssential(const Mat3 &E, (*Rs)[3] = U_Wt_Vt; ts->resize(4); - (*ts)[0] = U.col(2); + (*ts)[0] = U.col(2); (*ts)[1] = -U.col(2); - (*ts)[2] = U.col(2); + (*ts)[2] = U.col(2); (*ts)[3] = -U.col(2); } -int MotionFromEssentialChooseSolution(const std::vector<Mat3> &Rs, - const std::vector<Vec3> &ts, - const Mat3 &K1, - const Vec2 &x1, - const Mat3 &K2, - const Vec2 &x2) { +int MotionFromEssentialChooseSolution(const std::vector<Mat3>& Rs, + const std::vector<Vec3>& ts, + const Mat3& K1, + const Vec2& x1, + const Mat3& K2, + const Vec2& x2) { DCHECK_EQ(4, Rs.size()); DCHECK_EQ(4, ts.size()); @@ -354,8 +355,8 @@ int MotionFromEssentialChooseSolution(const std::vector<Mat3> &Rs, t1.setZero(); P_From_KRt(K1, R1, t1, &P1); for (int i = 0; i < 4; ++i) { - const Mat3 &R2 = Rs[i]; - const Vec3 &t2 = ts[i]; + const Mat3& R2 = Rs[i]; + const Vec3& t2 = ts[i]; P_From_KRt(K2, R2, t2, &P2); Vec3 X; TriangulateDLT(P1, x1, P2, x2, &X); @@ -369,13 +370,13 @@ int MotionFromEssentialChooseSolution(const std::vector<Mat3> &Rs, return -1; } -bool MotionFromEssentialAndCorrespondence(const Mat3 &E, - const Mat3 &K1, - const Vec2 &x1, - const Mat3 &K2, - const Vec2 &x2, - Mat3 *R, - Vec3 *t) { +bool MotionFromEssentialAndCorrespondence(const Mat3& E, + const Mat3& K1, + const Vec2& x1, + const Mat3& K2, + const Vec2& x2, + Mat3* R, + Vec3* t) { std::vector<Mat3> Rs; std::vector<Vec3> ts; MotionFromEssential(E, &Rs, &ts); @@ -389,7 +390,7 @@ bool MotionFromEssentialAndCorrespondence(const Mat3 &E, } } -void FundamentalToEssential(const Mat3 &F, Mat3 *E) { +void FundamentalToEssential(const Mat3& F, Mat3* E) { Eigen::JacobiSVD<Mat3> svd(F, Eigen::ComputeFullU | Eigen::ComputeFullV); // See Hartley & Zisserman page 294, result 11.1, which shows how to get the @@ -399,8 +400,8 @@ void FundamentalToEssential(const Mat3 &F, Mat3 *E) { double s = (a + b) / 2.0; LG << "Initial reconstruction's rotation is non-euclidean by " - << (((a - b) / std::max(a, b)) * 100) << "%; singular values:" - << svd.singularValues().transpose(); + << (((a - b) / std::max(a, b)) * 100) + << "%; singular values:" << svd.singularValues().transpose(); Vec3 diag; diag << s, s, 0; @@ -410,9 +411,8 @@ void FundamentalToEssential(const Mat3 &F, Mat3 *E) { // Default settings for fundamental estimation which should be suitable // for a wide range of use cases. -EstimateFundamentalOptions::EstimateFundamentalOptions(void) : - max_num_iterations(50), - expected_average_symmetric_distance(1e-16) { +EstimateFundamentalOptions::EstimateFundamentalOptions(void) + : max_num_iterations(50), expected_average_symmetric_distance(1e-16) { } namespace { @@ -420,12 +420,11 @@ namespace { // used for fundamental matrix refinement. class FundamentalSymmetricEpipolarCostFunctor { public: - FundamentalSymmetricEpipolarCostFunctor(const Vec2 &x, - const Vec2 &y) - : x_(x), y_(y) {} + FundamentalSymmetricEpipolarCostFunctor(const Vec2& x, const Vec2& y) + : x_(x), y_(y) {} - template<typename T> - bool operator()(const T *fundamental_parameters, T *residuals) const { + template <typename T> + bool operator()(const T* fundamental_parameters, T* residuals) const { typedef Eigen::Matrix<T, 3, 3> Mat3; typedef Eigen::Matrix<T, 3, 1> Vec3; @@ -454,9 +453,10 @@ class FundamentalSymmetricEpipolarCostFunctor { // average value. class TerminationCheckingCallback : public ceres::IterationCallback { public: - TerminationCheckingCallback(const Mat &x1, const Mat &x2, - const EstimateFundamentalOptions &options, - Mat3 *F) + TerminationCheckingCallback(const Mat& x1, + const Mat& x2, + const EstimateFundamentalOptions& options, + Mat3* F) : options_(options), x1_(x1), x2_(x2), F_(F) {} virtual ceres::CallbackReturnType operator()( @@ -469,9 +469,7 @@ class TerminationCheckingCallback : public ceres::IterationCallback { // Calculate average of symmetric epipolar distance. double average_distance = 0.0; for (int i = 0; i < x1_.cols(); i++) { - average_distance = SymmetricEpipolarDistance(*F_, - x1_.col(i), - x2_.col(i)); + average_distance = SymmetricEpipolarDistance(*F_, x1_.col(i), x2_.col(i)); } average_distance /= x1_.cols(); @@ -483,19 +481,19 @@ class TerminationCheckingCallback : public ceres::IterationCallback { } private: - const EstimateFundamentalOptions &options_; - const Mat &x1_; - const Mat &x2_; - Mat3 *F_; + const EstimateFundamentalOptions& options_; + const Mat& x1_; + const Mat& x2_; + Mat3* F_; }; } // namespace /* Fundamental transformation estimation. */ bool EstimateFundamentalFromCorrespondences( - const Mat &x1, - const Mat &x2, - const EstimateFundamentalOptions &options, - Mat3 *F) { + const Mat& x1, + const Mat& x2, + const EstimateFundamentalOptions& options, + Mat3* F) { // Step 1: Algebraic fundamental estimation. // Assume algebraic estiation always succeeds, @@ -506,16 +504,15 @@ bool EstimateFundamentalFromCorrespondences( // Step 2: Refine matrix using Ceres minimizer. ceres::Problem problem; for (int i = 0; i < x1.cols(); i++) { - FundamentalSymmetricEpipolarCostFunctor - *fundamental_symmetric_epipolar_cost_function = - new FundamentalSymmetricEpipolarCostFunctor(x1.col(i), - x2.col(i)); + FundamentalSymmetricEpipolarCostFunctor* + fundamental_symmetric_epipolar_cost_function = + new FundamentalSymmetricEpipolarCostFunctor(x1.col(i), x2.col(i)); problem.AddResidualBlock( - new ceres::AutoDiffCostFunction< - FundamentalSymmetricEpipolarCostFunctor, - 2, // num_residuals - 9>(fundamental_symmetric_epipolar_cost_function), + new ceres::AutoDiffCostFunction<FundamentalSymmetricEpipolarCostFunctor, + 2, // num_residuals + 9>( + fundamental_symmetric_epipolar_cost_function), NULL, F->data()); } diff --git a/intern/libmv/libmv/multiview/fundamental.h b/intern/libmv/libmv/multiview/fundamental.h index a6c7a6802fe..6d25691c4a3 100644 --- a/intern/libmv/libmv/multiview/fundamental.h +++ b/intern/libmv/libmv/multiview/fundamental.h @@ -27,36 +27,34 @@ namespace libmv { -void ProjectionsFromFundamental(const Mat3 &F, Mat34 *P1, Mat34 *P2); -void FundamentalFromProjections(const Mat34 &P1, const Mat34 &P2, Mat3 *F); +void ProjectionsFromFundamental(const Mat3& F, Mat34* P1, Mat34* P2); +void FundamentalFromProjections(const Mat34& P1, const Mat34& P2, Mat3* F); /** * 7 points (minimal case, points coordinates must be normalized before): */ -double FundamentalFrom7CorrespondencesLinear(const Mat &x1, - const Mat &x2, - std::vector<Mat3> *F); +double FundamentalFrom7CorrespondencesLinear(const Mat& x1, + const Mat& x2, + std::vector<Mat3>* F); /** * 7 points (points coordinates must be in image space): */ -double FundamentalFromCorrespondences7Point(const Mat &x1, - const Mat &x2, - std::vector<Mat3> *F); +double FundamentalFromCorrespondences7Point(const Mat& x1, + const Mat& x2, + std::vector<Mat3>* F); /** * 8 points (points coordinates must be in image space): */ -double NormalizedEightPointSolver(const Mat &x1, - const Mat &x2, - Mat3 *F); +double NormalizedEightPointSolver(const Mat& x1, const Mat& x2, Mat3* F); /** * Fundamental matrix utility function: */ -void EnforceFundamentalRank2Constraint(Mat3 *F); +void EnforceFundamentalRank2Constraint(Mat3* F); -void NormalizeFundamental(const Mat3 &F, Mat3 *F_normalized); +void NormalizeFundamental(const Mat3& F, Mat3* F_normalized); /** * Approximate squared reprojection errror. @@ -64,14 +62,14 @@ void NormalizeFundamental(const Mat3 &F, Mat3 *F_normalized); * See page 287 of HZ equation 11.9. This avoids triangulating the point, * relying only on the entries in F. */ -double SampsonDistance(const Mat &F, const Vec2 &x1, const Vec2 &x2); +double SampsonDistance(const Mat& F, const Vec2& x1, const Vec2& x2); /** * Calculates the sum of the distances from the points to the epipolar lines. * * See page 288 of HZ equation 11.10. */ -double SymmetricEpipolarDistance(const Mat &F, const Vec2 &x1, const Vec2 &x2); +double SymmetricEpipolarDistance(const Mat& F, const Vec2& x1, const Vec2& x2); /** * Compute the relative camera motion between two cameras. @@ -81,32 +79,29 @@ double SymmetricEpipolarDistance(const Mat &F, const Vec2 &x1, const Vec2 &x2); * If T1 and T2 are the camera motions, the computed relative motion is * T = T2 T1^{-1} */ -void RelativeCameraMotion(const Mat3 &R1, - const Vec3 &t1, - const Mat3 &R2, - const Vec3 &t2, - Mat3 *R, - Vec3 *t); - -void EssentialFromFundamental(const Mat3 &F, - const Mat3 &K1, - const Mat3 &K2, - Mat3 *E); - -void FundamentalFromEssential(const Mat3 &E, - const Mat3 &K1, - const Mat3 &K2, - Mat3 *F); - -void EssentialFromRt(const Mat3 &R1, - const Vec3 &t1, - const Mat3 &R2, - const Vec3 &t2, - Mat3 *E); - -void MotionFromEssential(const Mat3 &E, - std::vector<Mat3> *Rs, - std::vector<Vec3> *ts); +void RelativeCameraMotion(const Mat3& R1, + const Vec3& t1, + const Mat3& R2, + const Vec3& t2, + Mat3* R, + Vec3* t); + +void EssentialFromFundamental(const Mat3& F, + const Mat3& K1, + const Mat3& K2, + Mat3* E); + +void FundamentalFromEssential(const Mat3& E, + const Mat3& K1, + const Mat3& K2, + Mat3* F); + +void EssentialFromRt( + const Mat3& R1, const Vec3& t1, const Mat3& R2, const Vec3& t2, Mat3* E); + +void MotionFromEssential(const Mat3& E, + std::vector<Mat3>* Rs, + std::vector<Vec3>* ts); /** * Choose one of the four possible motion solutions from an essential matrix. @@ -117,25 +112,25 @@ void MotionFromEssential(const Mat3 &E, * * \return index of the right solution or -1 if no solution. */ -int MotionFromEssentialChooseSolution(const std::vector<Mat3> &Rs, - const std::vector<Vec3> &ts, - const Mat3 &K1, - const Vec2 &x1, - const Mat3 &K2, - const Vec2 &x2); - -bool MotionFromEssentialAndCorrespondence(const Mat3 &E, - const Mat3 &K1, - const Vec2 &x1, - const Mat3 &K2, - const Vec2 &x2, - Mat3 *R, - Vec3 *t); +int MotionFromEssentialChooseSolution(const std::vector<Mat3>& Rs, + const std::vector<Vec3>& ts, + const Mat3& K1, + const Vec2& x1, + const Mat3& K2, + const Vec2& x2); + +bool MotionFromEssentialAndCorrespondence(const Mat3& E, + const Mat3& K1, + const Vec2& x1, + const Mat3& K2, + const Vec2& x2, + Mat3* R, + Vec3* t); /** * Find closest essential matrix E to fundamental F */ -void FundamentalToEssential(const Mat3 &F, Mat3 *E); +void FundamentalToEssential(const Mat3& F, Mat3* E); /** * This structure contains options that controls how the fundamental @@ -170,10 +165,10 @@ struct EstimateFundamentalOptions { * refinement. */ bool EstimateFundamentalFromCorrespondences( - const Mat &x1, - const Mat &x2, - const EstimateFundamentalOptions &options, - Mat3 *F); + const Mat& x1, + const Mat& x2, + const EstimateFundamentalOptions& options, + Mat3* F); } // namespace libmv diff --git a/intern/libmv/libmv/multiview/fundamental_test.cc b/intern/libmv/libmv/multiview/fundamental_test.cc index da0eb449b8f..0ec91ca8d19 100644 --- a/intern/libmv/libmv/multiview/fundamental_test.cc +++ b/intern/libmv/libmv/multiview/fundamental_test.cc @@ -34,12 +34,14 @@ using namespace libmv; TEST(Fundamental, FundamentalFromProjections) { Mat34 P1_gt, P2_gt; + // clang-format off P1_gt << 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0; P2_gt << 1, 1, 1, 3, 0, 2, 0, 3, 0, 1, 1, 0; + // clang-format on Mat3 F_gt; FundamentalFromProjections(P1_gt, P2_gt, &F_gt); @@ -55,8 +57,10 @@ TEST(Fundamental, FundamentalFromProjections) { TEST(Fundamental, PreconditionerFromPoints) { int n = 4; Mat points(2, n); + // clang-format off points << 0, 0, 1, 1, 0, 2, 1, 3; + // clang-format on Mat3 T; PreconditionerFromPoints(points, &T); @@ -152,8 +156,8 @@ TEST(Fundamental, MotionFromEssentialAndCorrespondence) { Mat3 R_estimated; Vec3 t_estimated; - MotionFromEssentialAndCorrespondence(E, d.K1, x1, d.K2, x2, - &R_estimated, &t_estimated); + MotionFromEssentialAndCorrespondence( + E, d.K1, x1, d.K2, x2, &R_estimated, &t_estimated); EXPECT_LE(FrobeniusDistance(R_estimated, R), 1e-8); EXPECT_LE(DistanceL2(t_estimated, t), 1e-8); diff --git a/intern/libmv/libmv/multiview/homography.cc b/intern/libmv/libmv/multiview/homography.cc index 69177743f94..2db2c0cd3d5 100644 --- a/intern/libmv/libmv/multiview/homography.cc +++ b/intern/libmv/libmv/multiview/homography.cc @@ -26,7 +26,7 @@ #include "libmv/multiview/homography_parameterization.h" namespace libmv { -/** 2D Homography transformation estimation in the case that points are in +/** 2D Homography transformation estimation in the case that points are in * euclidean coordinates. * * x = H y @@ -44,10 +44,7 @@ namespace libmv { * (-x2*a+x1*d)*y1 + (-x2*b+x1*e)*y2 + -x2*c+x1*f |0| */ static bool Homography2DFromCorrespondencesLinearEuc( - const Mat &x1, - const Mat &x2, - Mat3 *H, - double expected_precision) { + const Mat& x1, const Mat& x2, Mat3* H, double expected_precision) { assert(2 == x1.rows()); assert(4 <= x1.cols()); assert(x1.rows() == x2.rows()); @@ -58,27 +55,27 @@ static bool Homography2DFromCorrespondencesLinearEuc( Mat b = Mat::Zero(n * 3, 1); for (int i = 0; i < n; ++i) { int j = 3 * i; - L(j, 0) = x1(0, i); // a - L(j, 1) = x1(1, i); // b - L(j, 2) = 1.0; // c + L(j, 0) = x1(0, i); // a + L(j, 1) = x1(1, i); // b + L(j, 2) = 1.0; // c L(j, 6) = -x2(0, i) * x1(0, i); // g L(j, 7) = -x2(0, i) * x1(1, i); // h - b(j, 0) = x2(0, i); // i + b(j, 0) = x2(0, i); // i ++j; - L(j, 3) = x1(0, i); // d - L(j, 4) = x1(1, i); // e - L(j, 5) = 1.0; // f + L(j, 3) = x1(0, i); // d + L(j, 4) = x1(1, i); // e + L(j, 5) = 1.0; // f L(j, 6) = -x2(1, i) * x1(0, i); // g L(j, 7) = -x2(1, i) * x1(1, i); // h - b(j, 0) = x2(1, i); // i + b(j, 0) = x2(1, i); // i // This ensures better stability // TODO(julien) make a lite version without this 3rd set ++j; - L(j, 0) = x2(1, i) * x1(0, i); // a - L(j, 1) = x2(1, i) * x1(1, i); // b - L(j, 2) = x2(1, i); // c + L(j, 0) = x2(1, i) * x1(0, i); // a + L(j, 1) = x2(1, i) * x1(1, i); // b + L(j, 2) = x2(1, i); // c L(j, 3) = -x2(0, i) * x1(0, i); // d L(j, 4) = -x2(0, i) * x1(1, i); // e L(j, 5) = -x2(0, i); // f @@ -86,14 +83,15 @@ static bool Homography2DFromCorrespondencesLinearEuc( // Solve Lx=B Vec h = L.fullPivLu().solve(b); Homography2DNormalizedParameterization<double>::To(h, H); - if ((L * h).isApprox(b, expected_precision)) { + if ((L * h).isApprox(b, expected_precision)) { return true; } else { return false; } } -/** 2D Homography transformation estimation in the case that points are in +// clang-format off +/** 2D Homography transformation estimation in the case that points are in * homogeneous coordinates. * * | 0 -x3 x2| |a b c| |y1| -x3*d+x2*g -x3*e+x2*h -x3*f+x2*1 |y1| (-x3*d+x2*g)*y1 (-x3*e+x2*h)*y2 (-x3*f+x2*1)*y3 |0| @@ -101,13 +99,14 @@ static bool Homography2DFromCorrespondencesLinearEuc( * |-x2 x1 0| |g h 1| |y3| -x2*a+x1*d -x2*b+x1*e -x2*c+x1*f |y3| (-x2*a+x1*d)*y1 (-x2*b+x1*e)*y2 (-x2*c+x1*f)*y3 |0| * X = |a b c d e f g h|^t */ -bool Homography2DFromCorrespondencesLinear(const Mat &x1, - const Mat &x2, - Mat3 *H, +// clang-format on +bool Homography2DFromCorrespondencesLinear(const Mat& x1, + const Mat& x2, + Mat3* H, double expected_precision) { if (x1.rows() == 2) { - return Homography2DFromCorrespondencesLinearEuc(x1, x2, H, - expected_precision); + return Homography2DFromCorrespondencesLinearEuc( + x1, x2, H, expected_precision); } assert(3 == x1.rows()); assert(4 <= x1.cols()); @@ -122,33 +121,33 @@ bool Homography2DFromCorrespondencesLinear(const Mat &x1, Mat b = Mat::Zero(n * 3, 1); for (int i = 0; i < n; ++i) { int j = 3 * i; - L(j, 0) = x2(w, i) * x1(x, i); // a - L(j, 1) = x2(w, i) * x1(y, i); // b - L(j, 2) = x2(w, i) * x1(w, i); // c + L(j, 0) = x2(w, i) * x1(x, i); // a + L(j, 1) = x2(w, i) * x1(y, i); // b + L(j, 2) = x2(w, i) * x1(w, i); // c L(j, 6) = -x2(x, i) * x1(x, i); // g L(j, 7) = -x2(x, i) * x1(y, i); // h - b(j, 0) = x2(x, i) * x1(w, i); + b(j, 0) = x2(x, i) * x1(w, i); ++j; - L(j, 3) = x2(w, i) * x1(x, i); // d - L(j, 4) = x2(w, i) * x1(y, i); // e - L(j, 5) = x2(w, i) * x1(w, i); // f + L(j, 3) = x2(w, i) * x1(x, i); // d + L(j, 4) = x2(w, i) * x1(y, i); // e + L(j, 5) = x2(w, i) * x1(w, i); // f L(j, 6) = -x2(y, i) * x1(x, i); // g L(j, 7) = -x2(y, i) * x1(y, i); // h - b(j, 0) = x2(y, i) * x1(w, i); + b(j, 0) = x2(y, i) * x1(w, i); // This ensures better stability ++j; - L(j, 0) = x2(y, i) * x1(x, i); // a - L(j, 1) = x2(y, i) * x1(y, i); // b - L(j, 2) = x2(y, i) * x1(w, i); // c + L(j, 0) = x2(y, i) * x1(x, i); // a + L(j, 1) = x2(y, i) * x1(y, i); // b + L(j, 2) = x2(y, i) * x1(w, i); // c L(j, 3) = -x2(x, i) * x1(x, i); // d L(j, 4) = -x2(x, i) * x1(y, i); // e L(j, 5) = -x2(x, i) * x1(w, i); // f } // Solve Lx=B Vec h = L.fullPivLu().solve(b); - if ((L * h).isApprox(b, expected_precision)) { + if ((L * h).isApprox(b, expected_precision)) { Homography2DNormalizedParameterization<double>::To(h, H); return true; } else { @@ -158,32 +157,30 @@ bool Homography2DFromCorrespondencesLinear(const Mat &x1, // Default settings for homography estimation which should be suitable // for a wide range of use cases. -EstimateHomographyOptions::EstimateHomographyOptions(void) : - use_normalization(true), - max_num_iterations(50), - expected_average_symmetric_distance(1e-16) { +EstimateHomographyOptions::EstimateHomographyOptions(void) + : use_normalization(true), + max_num_iterations(50), + expected_average_symmetric_distance(1e-16) { } namespace { -void GetNormalizedPoints(const Mat &original_points, - Mat *normalized_points, - Mat3 *normalization_matrix) { +void GetNormalizedPoints(const Mat& original_points, + Mat* normalized_points, + Mat3* normalization_matrix) { IsotropicPreconditionerFromPoints(original_points, normalization_matrix); - ApplyTransformationToPoints(original_points, - *normalization_matrix, - normalized_points); + ApplyTransformationToPoints( + original_points, *normalization_matrix, normalized_points); } // Cost functor which computes symmetric geometric distance // used for homography matrix refinement. class HomographySymmetricGeometricCostFunctor { public: - HomographySymmetricGeometricCostFunctor(const Vec2 &x, - const Vec2 &y) - : x_(x), y_(y) { } + HomographySymmetricGeometricCostFunctor(const Vec2& x, const Vec2& y) + : x_(x), y_(y) {} - template<typename T> - bool operator()(const T *homography_parameters, T *residuals) const { + template <typename T> + bool operator()(const T* homography_parameters, T* residuals) const { typedef Eigen::Matrix<T, 3, 3> Mat3; typedef Eigen::Matrix<T, 3, 1> Vec3; @@ -221,9 +218,10 @@ class HomographySymmetricGeometricCostFunctor { // average value. class TerminationCheckingCallback : public ceres::IterationCallback { public: - TerminationCheckingCallback(const Mat &x1, const Mat &x2, - const EstimateHomographyOptions &options, - Mat3 *H) + TerminationCheckingCallback(const Mat& x1, + const Mat& x2, + const EstimateHomographyOptions& options, + Mat3* H) : options_(options), x1_(x1), x2_(x2), H_(H) {} virtual ceres::CallbackReturnType operator()( @@ -236,9 +234,8 @@ class TerminationCheckingCallback : public ceres::IterationCallback { // Calculate average of symmetric geometric distance. double average_distance = 0.0; for (int i = 0; i < x1_.cols(); i++) { - average_distance = SymmetricGeometricDistance(*H_, - x1_.col(i), - x2_.col(i)); + average_distance = + SymmetricGeometricDistance(*H_, x1_.col(i), x2_.col(i)); } average_distance /= x1_.cols(); @@ -250,10 +247,10 @@ class TerminationCheckingCallback : public ceres::IterationCallback { } private: - const EstimateHomographyOptions &options_; - const Mat &x1_; - const Mat &x2_; - Mat3 *H_; + const EstimateHomographyOptions& options_; + const Mat& x1_; + const Mat& x2_; + Mat3* H_; }; } // namespace @@ -261,10 +258,10 @@ class TerminationCheckingCallback : public ceres::IterationCallback { * euclidean coordinates. */ bool EstimateHomography2DFromCorrespondences( - const Mat &x1, - const Mat &x2, - const EstimateHomographyOptions &options, - Mat3 *H) { + const Mat& x1, + const Mat& x2, + const EstimateHomographyOptions& options, + Mat3* H) { // TODO(sergey): Support homogenous coordinates, not just euclidean. assert(2 == x1.rows()); @@ -272,8 +269,7 @@ bool EstimateHomography2DFromCorrespondences( assert(x1.rows() == x2.rows()); assert(x1.cols() == x2.cols()); - Mat3 T1 = Mat3::Identity(), - T2 = Mat3::Identity(); + Mat3 T1 = Mat3::Identity(), T2 = Mat3::Identity(); // Step 1: Algebraic homography estimation. Mat x1_normalized, x2_normalized; @@ -300,16 +296,15 @@ bool EstimateHomography2DFromCorrespondences( // Step 2: Refine matrix using Ceres minimizer. ceres::Problem problem; for (int i = 0; i < x1.cols(); i++) { - HomographySymmetricGeometricCostFunctor - *homography_symmetric_geometric_cost_function = - new HomographySymmetricGeometricCostFunctor(x1.col(i), - x2.col(i)); + HomographySymmetricGeometricCostFunctor* + homography_symmetric_geometric_cost_function = + new HomographySymmetricGeometricCostFunctor(x1.col(i), x2.col(i)); problem.AddResidualBlock( - new ceres::AutoDiffCostFunction< - HomographySymmetricGeometricCostFunctor, - 4, // num_residuals - 9>(homography_symmetric_geometric_cost_function), + new ceres::AutoDiffCostFunction<HomographySymmetricGeometricCostFunctor, + 4, // num_residuals + 9>( + homography_symmetric_geometric_cost_function), NULL, H->data()); } @@ -335,15 +330,16 @@ bool EstimateHomography2DFromCorrespondences( return summary.IsSolutionUsable(); } +// clang-format off /** * x2 ~ A * x1 * x2^t * Hi * A *x1 = 0 - * H1 = H2 = H3 = + * H1 = H2 = H3 = * | 0 0 0 1| |-x2w| |0 0 0 0| | 0 | | 0 0 1 0| |-x2z| * | 0 0 0 0| -> | 0 | |0 0 1 0| -> |-x2z| | 0 0 0 0| -> | 0 | * | 0 0 0 0| | 0 | |0-1 0 0| | x2y| |-1 0 0 0| | x2x| * |-1 0 0 0| | x2x| |0 0 0 0| | 0 | | 0 0 0 0| | 0 | - * H4 = H5 = H6 = + * H4 = H5 = H6 = * |0 0 0 0| | 0 | | 0 1 0 0| |-x2y| |0 0 0 0| | 0 | * |0 0 0 1| -> |-x2w| |-1 0 0 0| -> | x2x| |0 0 0 0| -> | 0 | * |0 0 0 0| | 0 | | 0 0 0 0| | 0 | |0 0 0 1| |-x2w| @@ -361,10 +357,11 @@ bool EstimateHomography2DFromCorrespondences( * x2^t * H6 * A *x1 = (-x2w*i +x2z*m )*x1x + (-x2w*j +x2z*n )*x1y + (-x2w*k +x2z*o )*x1z + (-x2w*l +x2z*1 )*x1w = 0 * * X = |a b c d e f g h i j k l m n o|^t -*/ -bool Homography3DFromCorrespondencesLinear(const Mat &x1, - const Mat &x2, - Mat4 *H, + */ +// clang-format on +bool Homography3DFromCorrespondencesLinear(const Mat& x1, + const Mat& x2, + Mat4* H, double expected_precision) { assert(4 == x1.rows()); assert(5 <= x1.cols()); @@ -379,68 +376,68 @@ bool Homography3DFromCorrespondencesLinear(const Mat &x1, Mat b = Mat::Zero(n * 6, 1); for (int i = 0; i < n; ++i) { int j = 6 * i; - L(j, 0) = -x2(w, i) * x1(x, i); // a - L(j, 1) = -x2(w, i) * x1(y, i); // b - L(j, 2) = -x2(w, i) * x1(z, i); // c - L(j, 3) = -x2(w, i) * x1(w, i); // d - L(j, 12) = x2(x, i) * x1(x, i); // m - L(j, 13) = x2(x, i) * x1(y, i); // n - L(j, 14) = x2(x, i) * x1(z, i); // o - b(j, 0) = -x2(x, i) * x1(w, i); + L(j, 0) = -x2(w, i) * x1(x, i); // a + L(j, 1) = -x2(w, i) * x1(y, i); // b + L(j, 2) = -x2(w, i) * x1(z, i); // c + L(j, 3) = -x2(w, i) * x1(w, i); // d + L(j, 12) = x2(x, i) * x1(x, i); // m + L(j, 13) = x2(x, i) * x1(y, i); // n + L(j, 14) = x2(x, i) * x1(z, i); // o + b(j, 0) = -x2(x, i) * x1(w, i); ++j; - L(j, 4) = -x2(z, i) * x1(x, i); // e - L(j, 5) = -x2(z, i) * x1(y, i); // f - L(j, 6) = -x2(z, i) * x1(z, i); // g - L(j, 7) = -x2(z, i) * x1(w, i); // h - L(j, 8) = x2(y, i) * x1(x, i); // i - L(j, 9) = x2(y, i) * x1(y, i); // j - L(j, 10) = x2(y, i) * x1(z, i); // k - L(j, 11) = x2(y, i) * x1(w, i); // l + L(j, 4) = -x2(z, i) * x1(x, i); // e + L(j, 5) = -x2(z, i) * x1(y, i); // f + L(j, 6) = -x2(z, i) * x1(z, i); // g + L(j, 7) = -x2(z, i) * x1(w, i); // h + L(j, 8) = x2(y, i) * x1(x, i); // i + L(j, 9) = x2(y, i) * x1(y, i); // j + L(j, 10) = x2(y, i) * x1(z, i); // k + L(j, 11) = x2(y, i) * x1(w, i); // l ++j; - L(j, 0) = -x2(z, i) * x1(x, i); // a - L(j, 1) = -x2(z, i) * x1(y, i); // b - L(j, 2) = -x2(z, i) * x1(z, i); // c - L(j, 3) = -x2(z, i) * x1(w, i); // d - L(j, 8) = x2(x, i) * x1(x, i); // i - L(j, 9) = x2(x, i) * x1(y, i); // j - L(j, 10) = x2(x, i) * x1(z, i); // k - L(j, 11) = x2(x, i) * x1(w, i); // l + L(j, 0) = -x2(z, i) * x1(x, i); // a + L(j, 1) = -x2(z, i) * x1(y, i); // b + L(j, 2) = -x2(z, i) * x1(z, i); // c + L(j, 3) = -x2(z, i) * x1(w, i); // d + L(j, 8) = x2(x, i) * x1(x, i); // i + L(j, 9) = x2(x, i) * x1(y, i); // j + L(j, 10) = x2(x, i) * x1(z, i); // k + L(j, 11) = x2(x, i) * x1(w, i); // l ++j; - L(j, 4) = -x2(w, i) * x1(x, i); // e - L(j, 5) = -x2(w, i) * x1(y, i); // f - L(j, 6) = -x2(w, i) * x1(z, i); // g - L(j, 7) = -x2(w, i) * x1(w, i); // h - L(j, 12) = x2(y, i) * x1(x, i); // m - L(j, 13) = x2(y, i) * x1(y, i); // n - L(j, 14) = x2(y, i) * x1(z, i); // o - b(j, 0) = -x2(y, i) * x1(w, i); + L(j, 4) = -x2(w, i) * x1(x, i); // e + L(j, 5) = -x2(w, i) * x1(y, i); // f + L(j, 6) = -x2(w, i) * x1(z, i); // g + L(j, 7) = -x2(w, i) * x1(w, i); // h + L(j, 12) = x2(y, i) * x1(x, i); // m + L(j, 13) = x2(y, i) * x1(y, i); // n + L(j, 14) = x2(y, i) * x1(z, i); // o + b(j, 0) = -x2(y, i) * x1(w, i); ++j; L(j, 0) = -x2(y, i) * x1(x, i); // a L(j, 1) = -x2(y, i) * x1(y, i); // b L(j, 2) = -x2(y, i) * x1(z, i); // c L(j, 3) = -x2(y, i) * x1(w, i); // d - L(j, 4) = x2(x, i) * x1(x, i); // e - L(j, 5) = x2(x, i) * x1(y, i); // f - L(j, 6) = x2(x, i) * x1(z, i); // g - L(j, 7) = x2(x, i) * x1(w, i); // h + L(j, 4) = x2(x, i) * x1(x, i); // e + L(j, 5) = x2(x, i) * x1(y, i); // f + L(j, 6) = x2(x, i) * x1(z, i); // g + L(j, 7) = x2(x, i) * x1(w, i); // h ++j; - L(j, 8) = -x2(w, i) * x1(x, i); // i - L(j, 9) = -x2(w, i) * x1(y, i); // j + L(j, 8) = -x2(w, i) * x1(x, i); // i + L(j, 9) = -x2(w, i) * x1(y, i); // j L(j, 10) = -x2(w, i) * x1(z, i); // k L(j, 11) = -x2(w, i) * x1(w, i); // l - L(j, 12) = x2(z, i) * x1(x, i); // m - L(j, 13) = x2(z, i) * x1(y, i); // n - L(j, 14) = x2(z, i) * x1(z, i); // o - b(j, 0) = -x2(z, i) * x1(w, i); + L(j, 12) = x2(z, i) * x1(x, i); // m + L(j, 13) = x2(z, i) * x1(y, i); // n + L(j, 14) = x2(z, i) * x1(z, i); // o + b(j, 0) = -x2(z, i) * x1(w, i); } // Solve Lx=B Vec h = L.fullPivLu().solve(b); - if ((L * h).isApprox(b, expected_precision)) { + if ((L * h).isApprox(b, expected_precision)) { Homography3DNormalizedParameterization<double>::To(h, H); return true; } else { @@ -448,9 +445,9 @@ bool Homography3DFromCorrespondencesLinear(const Mat &x1, } } -double SymmetricGeometricDistance(const Mat3 &H, - const Vec2 &x1, - const Vec2 &x2) { +double SymmetricGeometricDistance(const Mat3& H, + const Vec2& x1, + const Vec2& x2) { Vec3 x(x1(0), x1(1), 1.0); Vec3 y(x2(0), x2(1), 1.0); diff --git a/intern/libmv/libmv/multiview/homography.h b/intern/libmv/libmv/multiview/homography.h index a76aa9405a5..0742c6f7c70 100644 --- a/intern/libmv/libmv/multiview/homography.h +++ b/intern/libmv/libmv/multiview/homography.h @@ -49,11 +49,11 @@ namespace libmv { * \return True if the transformation estimation has succeeded. * \note There must be at least 4 non-colinear points. */ -bool Homography2DFromCorrespondencesLinear(const Mat &x1, - const Mat &x2, - Mat3 *H, - double expected_precision = - EigenDouble::dummy_precision()); +bool Homography2DFromCorrespondencesLinear( + const Mat& x1, + const Mat& x2, + Mat3* H, + double expected_precision = EigenDouble::dummy_precision()); /** * This structure contains options that controls how the homography @@ -101,10 +101,10 @@ struct EstimateHomographyOptions { * refinement. */ bool EstimateHomography2DFromCorrespondences( - const Mat &x1, - const Mat &x2, - const EstimateHomographyOptions &options, - Mat3 *H); + const Mat& x1, + const Mat& x2, + const EstimateHomographyOptions& options, + Mat3* H); /** * 3D Homography transformation estimation. @@ -129,20 +129,20 @@ bool EstimateHomography2DFromCorrespondences( * \note Need at least 5 non coplanar points * \note Points coordinates must be in homogeneous coordinates */ -bool Homography3DFromCorrespondencesLinear(const Mat &x1, - const Mat &x2, - Mat4 *H, - double expected_precision = - EigenDouble::dummy_precision()); +bool Homography3DFromCorrespondencesLinear( + const Mat& x1, + const Mat& x2, + Mat4* H, + double expected_precision = EigenDouble::dummy_precision()); /** * Calculate symmetric geometric cost: * * D(H * x1, x2)^2 + D(H^-1 * x2, x1) */ -double SymmetricGeometricDistance(const Mat3 &H, - const Vec2 &x1, - const Vec2 &x2); +double SymmetricGeometricDistance(const Mat3& H, + const Vec2& x1, + const Vec2& x2); } // namespace libmv diff --git a/intern/libmv/libmv/multiview/homography_error.h b/intern/libmv/libmv/multiview/homography_error.h index f8b9d45e73c..786ca245ea6 100644 --- a/intern/libmv/libmv/multiview/homography_error.h +++ b/intern/libmv/libmv/multiview/homography_error.h @@ -27,18 +27,18 @@ namespace libmv { namespace homography { namespace homography2D { - /** - * Structure for estimating the asymmetric error between a vector x2 and the - * transformed x1 such that - * Error = ||x2 - Psi(H * x1)||^2 - * where Psi is the function that transforms homogeneous to euclidean coords. - * \note It should be distributed as Chi-squared with k = 2. - */ +/** + * Structure for estimating the asymmetric error between a vector x2 and the + * transformed x1 such that + * Error = ||x2 - Psi(H * x1)||^2 + * where Psi is the function that transforms homogeneous to euclidean coords. + * \note It should be distributed as Chi-squared with k = 2. + */ struct AsymmetricError { /** - * Computes the asymmetric residuals between a set of 2D points x2 and the + * Computes the asymmetric residuals between a set of 2D points x2 and the * transformed 2D point set x1 such that - * Residuals_i = x2_i - Psi(H * x1_i) + * Residuals_i = x2_i - Psi(H * x1_i) * where Psi is the function that transforms homogeneous to euclidean coords. * * \param[in] H The 3x3 homography matrix. @@ -47,8 +47,7 @@ struct AsymmetricError { * \param[in] x2 A set of 2D points (2xN or 3xN matrix of column vectors). * \param[out] dx A 2xN matrix of column vectors of residuals errors */ - static void Residuals(const Mat &H, const Mat &x1, - const Mat &x2, Mat2X *dx) { + static void Residuals(const Mat& H, const Mat& x1, const Mat& x2, Mat2X* dx) { dx->resize(2, x1.cols()); Mat3X x2h_est; if (x1.rows() == 2) @@ -63,19 +62,18 @@ struct AsymmetricError { *dx = HomogeneousToEuclidean(static_cast<Mat3X>(x2)) - *dx; } /** - * Computes the asymmetric residuals between a 2D point x2 and the transformed + * Computes the asymmetric residuals between a 2D point x2 and the transformed * 2D point x1 such that - * Residuals = x2 - Psi(H * x1) + * Residuals = x2 - Psi(H * x1) * where Psi is the function that transforms homogeneous to euclidean coords. * * \param[in] H The 3x3 homography matrix. * The estimated homography should approximatelly hold the condition y = H x. - * \param[in] x1 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) - * \param[in] x2 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) + * \param[in] x1 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) + * \param[in] x2 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) * \param[out] dx A vector of size 2 of the residual error */ - static void Residuals(const Mat &H, const Vec &x1, - const Vec &x2, Vec2 *dx) { + static void Residuals(const Mat& H, const Vec& x1, const Vec& x2, Vec2* dx) { Vec3 x2h_est; if (x1.rows() == 2) x2h_est = H * EuclideanToHomogeneous(static_cast<Vec2>(x1)); @@ -85,10 +83,10 @@ struct AsymmetricError { *dx = x2 - x2h_est.head<2>() / x2h_est[2]; else *dx = HomogeneousToEuclidean(static_cast<Vec3>(x2)) - - x2h_est.head<2>() / x2h_est[2]; + x2h_est.head<2>() / x2h_est[2]; } /** - * Computes the squared norm of the residuals between a set of 2D points x2 + * Computes the squared norm of the residuals between a set of 2D points x2 * and the transformed 2D point set x1 such that * Error = || x2 - Psi(H * x1) ||^2 * where Psi is the function that transforms homogeneous to euclidean coords. @@ -99,70 +97,70 @@ struct AsymmetricError { * \param[in] x2 A set of 2D points (2xN or 3xN matrix of column vectors). * \return The squared norm of the asymmetric residuals errors */ - static double Error(const Mat &H, const Mat &x1, const Mat &x2) { + static double Error(const Mat& H, const Mat& x1, const Mat& x2) { Mat2X dx; Residuals(H, x1, x2, &dx); return dx.squaredNorm(); } /** - * Computes the squared norm of the residuals between a 2D point x2 and the - * transformed 2D point x1 such that rms = || x2 - Psi(H * x1) ||^2 + * Computes the squared norm of the residuals between a 2D point x2 and the + * transformed 2D point x1 such that rms = || x2 - Psi(H * x1) ||^2 * where Psi is the function that transforms homogeneous to euclidean coords. * * \param[in] H The 3x3 homography matrix. * The estimated homography should approximatelly hold the condition y = H x. - * \param[in] x1 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) - * \param[in] x2 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) + * \param[in] x1 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) + * \param[in] x2 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) * \return The squared norm of the asymmetric residual error */ - static double Error(const Mat &H, const Vec &x1, const Vec &x2) { + static double Error(const Mat& H, const Vec& x1, const Vec& x2) { Vec2 dx; Residuals(H, x1, x2, &dx); return dx.squaredNorm(); } }; - /** - * Structure for estimating the symmetric error - * between a vector x2 and the transformed x1 such that - * Error = ||x2 - Psi(H * x1)||^2 + ||x1 - Psi(H^-1 * x2)||^2 - * where Psi is the function that transforms homogeneous to euclidean coords. - * \note It should be distributed as Chi-squared with k = 4. - */ +/** + * Structure for estimating the symmetric error + * between a vector x2 and the transformed x1 such that + * Error = ||x2 - Psi(H * x1)||^2 + ||x1 - Psi(H^-1 * x2)||^2 + * where Psi is the function that transforms homogeneous to euclidean coords. + * \note It should be distributed as Chi-squared with k = 4. + */ struct SymmetricError { /** - * Computes the squared norm of the residuals between x2 and the - * transformed x1 such that + * Computes the squared norm of the residuals between x2 and the + * transformed x1 such that * Error = ||x2 - Psi(H * x1)||^2 + ||x1 - Psi(H^-1 * x2)||^2 * where Psi is the function that transforms homogeneous to euclidean coords. * * \param[in] H The 3x3 homography matrix. * The estimated homography should approximatelly hold the condition y = H x. - * \param[in] x1 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) - * \param[in] x2 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) + * \param[in] x1 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) + * \param[in] x2 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) * \return The squared norm of the symmetric residuals errors */ - static double Error(const Mat &H, const Vec &x1, const Vec &x2) { + static double Error(const Mat& H, const Vec& x1, const Vec& x2) { // TODO(keir): This is awesomely inefficient because it does a 3x3 // inversion for each evaluation. Mat3 Hinv = H.inverse(); - return AsymmetricError::Error(H, x1, x2) + + return AsymmetricError::Error(H, x1, x2) + AsymmetricError::Error(Hinv, x2, x1); } // TODO(julien) Add residuals function \see AsymmetricError }; - /** - * Structure for estimating the algebraic error (cross product) - * between a vector x2 and the transformed x1 such that - * Error = ||[x2] * H * x1||^^2 - * where [x2] is the skew matrix of x2. - */ +/** + * Structure for estimating the algebraic error (cross product) + * between a vector x2 and the transformed x1 such that + * Error = ||[x2] * H * x1||^^2 + * where [x2] is the skew matrix of x2. + */ struct AlgebraicError { // TODO(julien) Make an AlgebraicError2Rows and AlgebraicError3Rows /** - * Computes the algebraic residuals (cross product) between a set of 2D - * points x2 and the transformed 2D point set x1 such that + * Computes the algebraic residuals (cross product) between a set of 2D + * points x2 and the transformed 2D point set x1 such that * [x2] * H * x1 where [x2] is the skew matrix of x2. * * \param[in] H The 3x3 homography matrix. @@ -171,8 +169,7 @@ struct AlgebraicError { * \param[in] x2 A set of 2D points (2xN or 3xN matrix of column vectors). * \param[out] dx A 3xN matrix of column vectors of residuals errors */ - static void Residuals(const Mat &H, const Mat &x1, - const Mat &x2, Mat3X *dx) { + static void Residuals(const Mat& H, const Mat& x1, const Mat& x2, Mat3X* dx) { dx->resize(3, x1.cols()); Vec3 col; for (int i = 0; i < x1.cols(); ++i) { @@ -181,18 +178,17 @@ struct AlgebraicError { } } /** - * Computes the algebraic residuals (cross product) between a 2D point x2 - * and the transformed 2D point x1 such that + * Computes the algebraic residuals (cross product) between a 2D point x2 + * and the transformed 2D point x1 such that * [x2] * H * x1 where [x2] is the skew matrix of x2. * * \param[in] H The 3x3 homography matrix. * The estimated homography should approximatelly hold the condition y = H x. - * \param[in] x1 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) - * \param[in] x2 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) + * \param[in] x1 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) + * \param[in] x2 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) * \param[out] dx A vector of size 3 of the residual error */ - static void Residuals(const Mat &H, const Vec &x1, - const Vec &x2, Vec3 *dx) { + static void Residuals(const Mat& H, const Vec& x1, const Vec& x2, Vec3* dx) { Vec3 x2h_est; if (x1.rows() == 2) x2h_est = H * EuclideanToHomogeneous(static_cast<Vec2>(x1)); @@ -206,8 +202,8 @@ struct AlgebraicError { // identical 3x3 skew matrix for each evaluation. } /** - * Computes the squared norm of the algebraic residuals between a set of 2D - * points x2 and the transformed 2D point set x1 such that + * Computes the squared norm of the algebraic residuals between a set of 2D + * points x2 and the transformed 2D point set x1 such that * [x2] * H * x1 where [x2] is the skew matrix of x2. * * \param[in] H The 3x3 homography matrix. @@ -216,23 +212,23 @@ struct AlgebraicError { * \param[in] x2 A set of 2D points (2xN or 3xN matrix of column vectors). * \return The squared norm of the asymmetric residuals errors */ - static double Error(const Mat &H, const Mat &x1, const Mat &x2) { + static double Error(const Mat& H, const Mat& x1, const Mat& x2) { Mat3X dx; Residuals(H, x1, x2, &dx); return dx.squaredNorm(); } /** - * Computes the squared norm of the algebraic residuals between a 2D point x2 - * and the transformed 2D point x1 such that + * Computes the squared norm of the algebraic residuals between a 2D point x2 + * and the transformed 2D point x1 such that * [x2] * H * x1 where [x2] is the skew matrix of x2. * * \param[in] H The 3x3 homography matrix. * The estimated homography should approximatelly hold the condition y = H x. - * \param[in] x1 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) - * \param[in] x2 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) + * \param[in] x1 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) + * \param[in] x2 A 2D point (vector of size 2 or 3 (euclidean/homogeneous)) * \return The squared norm of the asymmetric residual error */ - static double Error(const Mat &H, const Vec &x1, const Vec &x2) { + static double Error(const Mat& H, const Vec& x1, const Vec& x2) { Vec3 dx; Residuals(H, x1, x2, &dx); return dx.squaredNorm(); diff --git a/intern/libmv/libmv/multiview/homography_parameterization.h b/intern/libmv/libmv/multiview/homography_parameterization.h index ca8fbd8066e..ae2d74da9ff 100644 --- a/intern/libmv/libmv/multiview/homography_parameterization.h +++ b/intern/libmv/libmv/multiview/homography_parameterization.h @@ -25,64 +25,72 @@ namespace libmv { -/** A parameterization of the 2D homography matrix that uses 8 parameters so +/** A parameterization of the 2D homography matrix that uses 8 parameters so * that the matrix is normalized (H(2,2) == 1). * The homography matrix H is built from a list of 8 parameters (a, b,...g, h) * as follows - * |a b c| + * |a b c| * H = |d e f| - * |g h 1| + * |g h 1| */ -template<typename T = double> +template <typename T = double> class Homography2DNormalizedParameterization { public: typedef Eigen::Matrix<T, 8, 1> Parameters; // a, b, ... g, h typedef Eigen::Matrix<T, 3, 3> Parameterized; // H /// Convert from the 8 parameters to a H matrix. - static void To(const Parameters &p, Parameterized *h) { + static void To(const Parameters& p, Parameterized* h) { + // clang-format off *h << p(0), p(1), p(2), p(3), p(4), p(5), p(6), p(7), 1.0; + // clang-format on } /// Convert from a H matrix to the 8 parameters. - static void From(const Parameterized &h, Parameters *p) { + static void From(const Parameterized& h, Parameters* p) { + // clang-format off *p << h(0, 0), h(0, 1), h(0, 2), h(1, 0), h(1, 1), h(1, 2), h(2, 0), h(2, 1); + // clang-format on } }; -/** A parameterization of the 2D homography matrix that uses 15 parameters so +/** A parameterization of the 2D homography matrix that uses 15 parameters so * that the matrix is normalized (H(3,3) == 1). * The homography matrix H is built from a list of 15 parameters (a, b,...n, o) * as follows - * |a b c d| + * |a b c d| * H = |e f g h| * |i j k l| - * |m n o 1| + * |m n o 1| */ -template<typename T = double> +template <typename T = double> class Homography3DNormalizedParameterization { public: - typedef Eigen::Matrix<T, 15, 1> Parameters; // a, b, ... n, o - typedef Eigen::Matrix<T, 4, 4> Parameterized; // H + typedef Eigen::Matrix<T, 15, 1> Parameters; // a, b, ... n, o + typedef Eigen::Matrix<T, 4, 4> Parameterized; // H /// Convert from the 15 parameters to a H matrix. - static void To(const Parameters &p, Parameterized *h) { + static void To(const Parameters& p, Parameterized* h) { + // clang-format off *h << p(0), p(1), p(2), p(3), p(4), p(5), p(6), p(7), p(8), p(9), p(10), p(11), p(12), p(13), p(14), 1.0; + // clang-format on } /// Convert from a H matrix to the 15 parameters. - static void From(const Parameterized &h, Parameters *p) { + static void From(const Parameterized& h, Parameters* p) { + // clang-format off *p << h(0, 0), h(0, 1), h(0, 2), h(0, 3), h(1, 0), h(1, 1), h(1, 2), h(1, 3), h(2, 0), h(2, 1), h(2, 2), h(2, 3), h(3, 0), h(3, 1), h(3, 2); + // clang-format on } }; diff --git a/intern/libmv/libmv/multiview/homography_test.cc b/intern/libmv/libmv/multiview/homography_test.cc index 8d7266e3d11..87d1c85028d 100644 --- a/intern/libmv/libmv/multiview/homography_test.cc +++ b/intern/libmv/libmv/multiview/homography_test.cc @@ -18,10 +18,10 @@ // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS // IN THE SOFTWARE. -#include "testing/testing.h" +#include "libmv/multiview/homography.h" #include "libmv/logging/logging.h" #include "libmv/multiview/projection.h" -#include "libmv/multiview/homography.h" +#include "testing/testing.h" namespace { using namespace libmv; @@ -34,9 +34,7 @@ namespace { // TODO(sergey): Consider using this in all tests since possible homography // matrix is not fixed to a single value and different-looking matrices // might actually crrespond to the same exact transform. -void CheckHomography2DTransform(const Mat3 &H, - const Mat &x1, - const Mat &x2) { +void CheckHomography2DTransform(const Mat3& H, const Mat& x1, const Mat& x2) { for (int i = 0; i < x2.cols(); ++i) { Vec3 x2_expected = x2.col(i); Vec3 x2_observed = H * x1.col(i); @@ -49,15 +47,19 @@ void CheckHomography2DTransform(const Mat3 &H, TEST(Homography2DTest, Rotation45AndTranslationXY) { Mat x1(3, 4); + // clang-format off x1 << 0, 1, 0, 5, 0, 0, 2, 3, 1, 1, 1, 1; + // clang-format on double angle = 45.0; Mat3 m; + // clang-format off m << cos(angle), -sin(angle), -2, sin(angle), cos(angle), 5, 0, 0, 1; + // clang-format on Mat x2 = x1; // Transform point from ground truth matrix @@ -76,13 +78,17 @@ TEST(Homography2DTest, Rotation45AndTranslationXY) { TEST(Homography2DTest, AffineGeneral4) { // TODO(julien) find why it doesn't work with 4 points!!! Mat x1(3, 4); + // clang-format off x1 << 0, 1, 0, 2, 0, 0, 1, 2, 1, 1, 1, 1; + // clang-format on Mat3 m; + // clang-format off m << 3, -1, 4, 6, -2, -3, 0, 0, 1; + // clang-format on Mat x2 = x1; for (int i = 0; i < x2.cols(); ++i) { @@ -109,13 +115,17 @@ TEST(Homography2DTest, AffineGeneral4) { TEST(Homography2DTest, AffineGeneral5) { Mat x1(3, 5); + // clang-format off x1 << 0, 1, 0, 2, 5, 0, 0, 1, 2, 2, 1, 1, 1, 1, 1; + // clang-format on Mat3 m; + // clang-format off m << 3, -1, 4, 6, -2, -3, 0, 0, 1; + // clang-format on Mat x2 = x1; for (int i = 0; i < x2.cols(); ++i) @@ -142,13 +152,17 @@ TEST(Homography2DTest, AffineGeneral5) { TEST(Homography2DTest, HomographyGeneral) { Mat x1(3, 4); + // clang-format off x1 << 0, 1, 0, 5, 0, 0, 2, 3, 1, 1, 1, 1; + // clang-format on Mat3 m; + // clang-format off m << 3, -1, 4, 6, -2, -3, 1, -3, 1; + // clang-format on Mat x2 = x1; for (int i = 0; i < x2.cols(); ++i) @@ -164,10 +178,12 @@ TEST(Homography2DTest, HomographyGeneral) { TEST(Homography3DTest, RotationAndTranslationXYZ) { Mat x1(4, 5); + // clang-format off x1 << 0, 0, 1, 5, 2, 0, 1, 2, 3, 5, 0, 2, 0, 1, 5, 1, 1, 1, 1, 1; + // clang-format on Mat4 M; M.setIdentity(); /* @@ -178,24 +194,30 @@ TEST(Homography3DTest, RotationAndTranslationXYZ) { // Rotation on x + translation double angle = 45.0; Mat4 rot; + // clang-format off rot << 1, 0, 0, 1, 0, cos(angle), -sin(angle), 3, 0, sin(angle), cos(angle), -2, 0, 0, 0, 1; + // clang-format on M *= rot; // Rotation on y angle = 25.0; + // clang-format off rot << cos(angle), 0, sin(angle), 0, 0, 1, 0, 0, -sin(angle), 0, cos(angle), 0, 0, 0, 0, 1; + // clang-format on M *= rot; // Rotation on z angle = 5.0; + // clang-format off rot << cos(angle), -sin(angle), 0, 0, sin(angle), cos(angle), 0, 0, 0, 0, 1, 0, 0, 0, 0, 1; + // clang-format on M *= rot; Mat x2 = x1; for (int i = 0; i < x2.cols(); ++i) { @@ -212,15 +234,19 @@ TEST(Homography3DTest, RotationAndTranslationXYZ) { TEST(Homography3DTest, AffineGeneral) { Mat x1(4, 5); + // clang-format off x1 << 0, 0, 1, 5, 2, 0, 1, 2, 3, 5, 0, 2, 0, 1, 5, 1, 1, 1, 1, 1; + // clang-format on Mat4 m; + // clang-format off m << 3, -1, 4, 1, 6, -2, -3, -6, 1, 0, 1, 2, 0, 0, 0, 1; + // clang-format on Mat x2 = x1; for (int i = 0; i < x2.cols(); ++i) { @@ -236,15 +262,19 @@ TEST(Homography3DTest, AffineGeneral) { TEST(Homography3DTest, HomographyGeneral) { Mat x1(4, 5); + // clang-format off x1 << 0, 0, 1, 5, 2, 0, 1, 2, 3, 5, 0, 2, 0, 1, 5, 1, 1, 1, 1, 1; + // clang-format on Mat4 m; + // clang-format off m << 3, -1, 4, 1, 6, -2, -3, -6, 1, 0, 1, 2, -3, 1, 0, 1; + // clang-format on Mat x2 = x1; for (int i = 0; i < x2.cols(); ++i) { diff --git a/intern/libmv/libmv/multiview/nviewtriangulation.h b/intern/libmv/libmv/multiview/nviewtriangulation.h index f4614ab1a5c..b2a320953a7 100644 --- a/intern/libmv/libmv/multiview/nviewtriangulation.h +++ b/intern/libmv/libmv/multiview/nviewtriangulation.h @@ -34,22 +34,22 @@ namespace libmv { // x's are 2D coordinates (x,y,1) in each image; Ps are projective cameras. The // output, X, is a homogeneous four vectors. -template<typename T> -void NViewTriangulate(const Matrix<T, 2, Dynamic> &x, - const vector<Matrix<T, 3, 4> > &Ps, - Matrix<T, 4, 1> *X) { +template <typename T> +void NViewTriangulate(const Matrix<T, 2, Dynamic>& x, + const vector<Matrix<T, 3, 4>>& Ps, + Matrix<T, 4, 1>* X) { int nviews = x.cols(); assert(nviews == Ps.size()); - Matrix<T, Dynamic, Dynamic> design(3*nviews, 4 + nviews); + Matrix<T, Dynamic, Dynamic> design(3 * nviews, 4 + nviews); design.setConstant(0.0); for (int i = 0; i < nviews; i++) { - design.template block<3, 4>(3*i, 0) = -Ps[i]; - design(3*i + 0, 4 + i) = x(0, i); - design(3*i + 1, 4 + i) = x(1, i); - design(3*i + 2, 4 + i) = 1.0; + design.template block<3, 4>(3 * i, 0) = -Ps[i]; + design(3 * i + 0, 4 + i) = x(0, i); + design(3 * i + 1, 4 + i) = x(1, i); + design(3 * i + 2, 4 + i) = 1.0; } - Matrix<T, Dynamic, 1> X_and_alphas; + Matrix<T, Dynamic, 1> X_and_alphas; Nullspace(&design, &X_and_alphas); X->resize(4); *X = X_and_alphas.head(4); @@ -60,16 +60,16 @@ void NViewTriangulate(const Matrix<T, 2, Dynamic> &x, // This method uses the algebraic distance approximation. // Note that this method works better when the 2D points are normalized // with an isotopic normalization. -template<typename T> -void NViewTriangulateAlgebraic(const Matrix<T, 2, Dynamic> &x, - const vector<Matrix<T, 3, 4> > &Ps, - Matrix<T, 4, 1> *X) { +template <typename T> +void NViewTriangulateAlgebraic(const Matrix<T, 2, Dynamic>& x, + const vector<Matrix<T, 3, 4>>& Ps, + Matrix<T, 4, 1>* X) { int nviews = x.cols(); assert(nviews == Ps.size()); - Matrix<T, Dynamic, 4> design(2*nviews, 4); + Matrix<T, Dynamic, 4> design(2 * nviews, 4); for (int i = 0; i < nviews; i++) { - design.template block<2, 4>(2*i, 0) = SkewMatMinimal(x.col(i)) * Ps[i]; + design.template block<2, 4>(2 * i, 0) = SkewMatMinimal(x.col(i)) * Ps[i]; } X->resize(4); Nullspace(&design, X); diff --git a/intern/libmv/libmv/multiview/nviewtriangulation_test.cc b/intern/libmv/libmv/multiview/nviewtriangulation_test.cc index 5a4d8499753..dba5fd07d5c 100644 --- a/intern/libmv/libmv/multiview/nviewtriangulation_test.cc +++ b/intern/libmv/libmv/multiview/nviewtriangulation_test.cc @@ -54,7 +54,7 @@ TEST(NViewTriangulate, FiveViews) { // Check reprojection error. Should be nearly zero. for (int j = 0; j < nviews; ++j) { - Vec3 x_reprojected = Ps[j]*X; + Vec3 x_reprojected = Ps[j] * X; x_reprojected /= x_reprojected(2); double error = (x_reprojected.head(2) - xs.col(j)).norm(); EXPECT_NEAR(error, 0.0, 1e-9); @@ -84,7 +84,7 @@ TEST(NViewTriangulateAlgebraic, FiveViews) { // Check reprojection error. Should be nearly zero. for (int j = 0; j < nviews; ++j) { - Vec3 x_reprojected = Ps[j]*X; + Vec3 x_reprojected = Ps[j] * X; x_reprojected /= x_reprojected(2); double error = (x_reprojected.head<2>() - xs.col(j)).norm(); EXPECT_NEAR(error, 0.0, 1e-9); diff --git a/intern/libmv/libmv/multiview/panography.cc b/intern/libmv/libmv/multiview/panography.cc index b62802948c4..42b1c19d65e 100644 --- a/intern/libmv/libmv/multiview/panography.cc +++ b/intern/libmv/libmv/multiview/panography.cc @@ -24,8 +24,9 @@ namespace libmv { static bool Build_Minimal2Point_PolynomialFactor( - const Mat & x1, const Mat & x2, - double * P) { // P must be a double[4] + const Mat& x1, + const Mat& x2, + double* P) { // P must be a double[4] assert(2 == x1.rows()); assert(2 == x1.cols()); assert(x1.rows() == x2.rows()); @@ -40,11 +41,11 @@ static bool Build_Minimal2Point_PolynomialFactor( Vec yx2 = (x2.col(1)).transpose(); double b12 = xx2.dot(yx2); - double a1 = xx1.squaredNorm(); - double a2 = yx1.squaredNorm(); + double a1 = xx1.squaredNorm(); + double a2 = yx1.squaredNorm(); - double b1 = xx2.squaredNorm(); - double b2 = yx2.squaredNorm(); + double b1 = xx2.squaredNorm(); + double b2 = yx2.squaredNorm(); // Build the 3rd degre polynomial in F^2. // @@ -52,10 +53,12 @@ static bool Build_Minimal2Point_PolynomialFactor( // // Coefficients in ascending powers of alpha, i.e. P[N]*x^N. // Run panography_coeffs.py to get the below coefficients. - P[0] = b1*b2*a12*a12-a1*a2*b12*b12; - P[1] = -2*a1*a2*b12+2*a12*b1*b2+b1*a12*a12+b2*a12*a12-a1*b12*b12-a2*b12*b12; - P[2] = b1*b2-a1*a2-2*a1*b12-2*a2*b12+2*a12*b1+2*a12*b2+a12*a12-b12*b12; - P[3] = b1+b2-2*b12-a1-a2+2*a12; + P[0] = b1 * b2 * a12 * a12 - a1 * a2 * b12 * b12; + P[1] = -2 * a1 * a2 * b12 + 2 * a12 * b1 * b2 + b1 * a12 * a12 + + b2 * a12 * a12 - a1 * b12 * b12 - a2 * b12 * b12; + P[2] = b1 * b2 - a1 * a2 - 2 * a1 * b12 - 2 * a2 * b12 + 2 * a12 * b1 + + 2 * a12 * b2 + a12 * a12 - b12 * b12; + P[3] = b1 + b2 - 2 * b12 - a1 - a2 + 2 * a12; // If P[3] equal to 0 we get ill conditionned data return (P[3] != 0.0); @@ -67,8 +70,9 @@ static bool Build_Minimal2Point_PolynomialFactor( // // [1] M. Brown and R. Hartley and D. Nister. Minimal Solutions for Panoramic // Stitching. CVPR07. -void F_FromCorrespondance_2points(const Mat &x1, const Mat &x2, - vector<double> *fs) { +void F_FromCorrespondance_2points(const Mat& x1, + const Mat& x2, + vector<double>* fs) { // Build Polynomial factor to get squared focal value. double P[4]; Build_Minimal2Point_PolynomialFactor(x1, x2, &P[0]); @@ -79,8 +83,8 @@ void F_FromCorrespondance_2points(const Mat &x1, const Mat &x2, // double roots[3]; int num_roots = SolveCubicPolynomial(P, roots); - for (int i = 0; i < num_roots; ++i) { - if (roots[i] > 0.0) { + for (int i = 0; i < num_roots; ++i) { + if (roots[i] > 0.0) { fs->push_back(sqrt(roots[i])); } } @@ -92,17 +96,18 @@ void F_FromCorrespondance_2points(const Mat &x1, const Mat &x2, // K. Arun,T. Huand and D. Blostein. Least-squares fitting of 2 3-D point // sets. IEEE Transactions on Pattern Analysis and Machine Intelligence, // 9:698-700, 1987. -void GetR_FixedCameraCenter(const Mat &x1, const Mat &x2, +void GetR_FixedCameraCenter(const Mat& x1, + const Mat& x2, const double focal, - Mat3 *R) { + Mat3* R) { assert(3 == x1.rows()); assert(2 <= x1.cols()); assert(x1.rows() == x2.rows()); assert(x1.cols() == x2.cols()); // Build simplified K matrix - Mat3 K(Mat3::Identity() * 1.0/focal); - K(2, 2)= 1.0; + Mat3 K(Mat3::Identity() * 1.0 / focal); + K(2, 2) = 1.0; // Build the correlation matrix; equation (22) in [1]. Mat3 C = Mat3::Zero(); @@ -115,9 +120,9 @@ void GetR_FixedCameraCenter(const Mat &x1, const Mat &x2, // Solve for rotation. Equations (24) and (25) in [1]. Eigen::JacobiSVD<Mat> svd(C, Eigen::ComputeThinU | Eigen::ComputeThinV); Mat3 scale = Mat3::Identity(); - scale(2, 2) = ((svd.matrixU() * svd.matrixV().transpose()).determinant() > 0.0) - ? 1.0 - : -1.0; + scale(2, 2) = + ((svd.matrixU() * svd.matrixV().transpose()).determinant() > 0.0) ? 1.0 + : -1.0; (*R) = svd.matrixU() * scale * svd.matrixV().transpose(); } diff --git a/intern/libmv/libmv/multiview/panography.h b/intern/libmv/libmv/multiview/panography.h index 6e87bd71304..5860a34d1fd 100644 --- a/intern/libmv/libmv/multiview/panography.h +++ b/intern/libmv/libmv/multiview/panography.h @@ -22,9 +22,9 @@ #ifndef LIBMV_MULTIVIEW_PANOGRAPHY_H #define LIBMV_MULTIVIEW_PANOGRAPHY_H +#include "libmv/base/vector.h" #include "libmv/numeric/numeric.h" #include "libmv/numeric/poly.h" -#include "libmv/base/vector.h" namespace libmv { @@ -53,8 +53,9 @@ namespace libmv { // K = [0 f 0] // [0 0 1] // -void F_FromCorrespondance_2points(const Mat &x1, const Mat &x2, - vector<double> *fs); +void F_FromCorrespondance_2points(const Mat& x1, + const Mat& x2, + vector<double>* fs); // Compute the 3x3 rotation matrix that fits two 3D point clouds in the least // square sense. The method is from: @@ -90,9 +91,10 @@ void F_FromCorrespondance_2points(const Mat &x1, const Mat &x2, // // R = arg min || X2 - R * x1 || // -void GetR_FixedCameraCenter(const Mat &x1, const Mat &x2, +void GetR_FixedCameraCenter(const Mat& x1, + const Mat& x2, const double focal, - Mat3 *R); + Mat3* R); } // namespace libmv diff --git a/intern/libmv/libmv/multiview/panography_kernel.cc b/intern/libmv/libmv/multiview/panography_kernel.cc index 8fdc9e79aed..e8ba648e352 100644 --- a/intern/libmv/libmv/multiview/panography_kernel.cc +++ b/intern/libmv/libmv/multiview/panography_kernel.cc @@ -25,7 +25,7 @@ namespace libmv { namespace panography { namespace kernel { -void TwoPointSolver::Solve(const Mat &x1, const Mat &x2, vector<Mat3> *Hs) { +void TwoPointSolver::Solve(const Mat& x1, const Mat& x2, vector<Mat3>* Hs) { // Solve for the focal lengths. vector<double> fs; F_FromCorrespondance_2points(x1, x2, &fs); @@ -34,7 +34,7 @@ void TwoPointSolver::Solve(const Mat &x1, const Mat &x2, vector<Mat3> *Hs) { Mat x1h, x2h; EuclideanToHomogeneous(x1, &x1h); EuclideanToHomogeneous(x2, &x2h); - for (int i = 0; i < fs.size(); ++i) { + for (int i = 0; i < fs.size(); ++i) { Mat3 K1 = Mat3::Identity() * fs[i]; K1(2, 2) = 1.0; diff --git a/intern/libmv/libmv/multiview/panography_kernel.h b/intern/libmv/libmv/multiview/panography_kernel.h index a6adbd54b20..d50d3ea0789 100644 --- a/intern/libmv/libmv/multiview/panography_kernel.h +++ b/intern/libmv/libmv/multiview/panography_kernel.h @@ -23,9 +23,9 @@ #include "libmv/base/vector.h" #include "libmv/multiview/conditioning.h" +#include "libmv/multiview/homography_error.h" #include "libmv/multiview/projection.h" #include "libmv/multiview/two_view_kernel.h" -#include "libmv/multiview/homography_error.h" #include "libmv/numeric/numeric.h" namespace libmv { @@ -34,18 +34,18 @@ namespace kernel { struct TwoPointSolver { enum { MINIMUM_SAMPLES = 2 }; - static void Solve(const Mat &x1, const Mat &x2, vector<Mat3> *Hs); + static void Solve(const Mat& x1, const Mat& x2, vector<Mat3>* Hs); }; -typedef two_view::kernel::Kernel< - TwoPointSolver, homography::homography2D::AsymmetricError, Mat3> - UnnormalizedKernel; +typedef two_view::kernel:: + Kernel<TwoPointSolver, homography::homography2D::AsymmetricError, Mat3> + UnnormalizedKernel; typedef two_view::kernel::Kernel< - two_view::kernel::NormalizedSolver<TwoPointSolver, UnnormalizerI>, - homography::homography2D::AsymmetricError, - Mat3> - Kernel; + two_view::kernel::NormalizedSolver<TwoPointSolver, UnnormalizerI>, + homography::homography2D::AsymmetricError, + Mat3> + Kernel; } // namespace kernel } // namespace panography diff --git a/intern/libmv/libmv/multiview/panography_test.cc b/intern/libmv/libmv/multiview/panography_test.cc index 96d52acfc3c..a7cbd371d40 100644 --- a/intern/libmv/libmv/multiview/panography_test.cc +++ b/intern/libmv/libmv/multiview/panography_test.cc @@ -18,8 +18,8 @@ // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS // IN THE SOFTWARE. -#include "libmv/logging/logging.h" #include "libmv/multiview/panography.h" +#include "libmv/logging/logging.h" #include "libmv/multiview/panography_kernel.h" #include "libmv/multiview/projection.h" #include "libmv/numeric/numeric.h" @@ -30,18 +30,16 @@ namespace { TEST(Panography, PrintSomeSharedFocalEstimationValues) { Mat x1(2, 2), x2(2, 2); - x1<< 158, 78, - 124, 113; - x2<< 300, 214, - 125, 114; + x1 << 158, 78, 124, 113; + x2 << 300, 214, 125, 114; // Normalize data (set principal point 0,0 and image border to 1.0). x1.block<1, 2>(0, 0) /= 320; x1.block<1, 2>(1, 0) /= 240; x2.block<1, 2>(0, 0) /= 320; x2.block<1, 2>(1, 0) /= 240; - x1+=Mat2::Constant(0.5); - x2+=Mat2::Constant(0.5); + x1 += Mat2::Constant(0.5); + x2 += Mat2::Constant(0.5); vector<double> fs; F_FromCorrespondance_2points(x1, x2, &fs); @@ -53,9 +51,11 @@ TEST(Panography, PrintSomeSharedFocalEstimationValues) { TEST(Panography, GetR_FixedCameraCenterWithIdentity) { Mat x1(3, 3); + // clang-format off x1 << 0.5, 0.6, 0.7, 0.5, 0.5, 0.4, 10.0, 10.0, 10.0; + // clang-format on Mat3 R; GetR_FixedCameraCenter(x1, x1, 1.0, &R); @@ -68,16 +68,20 @@ TEST(Panography, Homography_GetR_Test_PitchY30) { int n = 3; Mat x1(3, n); + // clang-format off x1 << 0.5, 0.6, 0.7, 0.5, 0.5, 0.4, 10, 10, 10; + // clang-format on Mat x2 = x1; const double alpha = 30.0 * M_PI / 180.0; Mat3 rotY; + // clang-format off rotY << cos(alpha), 0, -sin(alpha), 0, 1, 0, sin(alpha), 0, cos(alpha); + // clang-format on for (int i = 0; i < n; ++i) { x2.block<3, 1>(0, i) = rotY * x1.col(i); @@ -101,17 +105,23 @@ TEST(Panography, Homography_GetR_Test_PitchY30) { TEST(MinimalPanoramic, Real_Case_Kernel) { const int n = 2; Mat x1(2, n); // From image 0.jpg + // clang-format off x1<< 158, 78, 124, 113; + // clang-format on Mat x2(2, n); // From image 3.jpg + // clang-format off x2<< 300, 214, 125, 114; + // clang-format on Mat3 Ground_TruthHomography; + // clang-format off Ground_TruthHomography<< 1, 0.02, 129.83, -0.02, 1.012, 0.07823, 0, 0, 1; + // clang-format on vector<Mat3> Hs; @@ -130,7 +140,7 @@ TEST(MinimalPanoramic, Real_Case_Kernel) { // Assert that residuals are small enough for (int i = 0; i < n; ++i) { Vec x1p = H * x1h.col(i); - Vec residuals = x1p/x1p(2) - x2h.col(i); + Vec residuals = x1p / x1p(2) - x2h.col(i); EXPECT_MATRIX_NEAR_ZERO(residuals, 1e-5); } } diff --git a/intern/libmv/libmv/multiview/projection.cc b/intern/libmv/libmv/multiview/projection.cc index f8bece3de68..001da89e127 100644 --- a/intern/libmv/libmv/multiview/projection.cc +++ b/intern/libmv/libmv/multiview/projection.cc @@ -23,13 +23,13 @@ namespace libmv { -void P_From_KRt(const Mat3 &K, const Mat3 &R, const Vec3 &t, Mat34 *P) { +void P_From_KRt(const Mat3& K, const Mat3& R, const Vec3& t, Mat34* P) { P->block<3, 3>(0, 0) = R; P->col(3) = t; (*P) = K * (*P); } -void KRt_From_P(const Mat34 &P, Mat3 *Kp, Mat3 *Rp, Vec3 *tp) { +void KRt_From_P(const Mat34& P, Mat3* Kp, Mat3* Rp, Vec3* tp) { // Decompose using the RQ decomposition HZ A4.1.1 pag.579. Mat3 K = P.block(0, 0, 3, 3); @@ -44,9 +44,11 @@ void KRt_From_P(const Mat34 &P, Mat3 *Kp, Mat3 *Rp, Vec3 *tp) { c /= l; s /= l; Mat3 Qx; + // clang-format off Qx << 1, 0, 0, 0, c, -s, 0, s, c; + // clang-format on K = K * Qx; Q = Qx.transpose() * Q; } @@ -58,9 +60,11 @@ void KRt_From_P(const Mat34 &P, Mat3 *Kp, Mat3 *Rp, Vec3 *tp) { c /= l; s /= l; Mat3 Qy; + // clang-format off Qy << c, 0, s, 0, 1, 0, -s, 0, c; + // clang-format on K = K * Qy; Q = Qy.transpose() * Q; } @@ -72,9 +76,11 @@ void KRt_From_P(const Mat34 &P, Mat3 *Kp, Mat3 *Rp, Vec3 *tp) { c /= l; s /= l; Mat3 Qz; + // clang-format off Qz << c, -s, 0, s, c, 0, 0, 0, 1; + // clang-format on K = K * Qz; Q = Qz.transpose() * Q; } @@ -92,17 +98,21 @@ void KRt_From_P(const Mat34 &P, Mat3 *Kp, Mat3 *Rp, Vec3 *tp) { } if (K(1, 1) < 0) { Mat3 S; + // clang-format off S << 1, 0, 0, 0, -1, 0, 0, 0, 1; + // clang-format on K = K * S; R = S * R; } if (K(0, 0) < 0) { Mat3 S; + // clang-format off S << -1, 0, 0, 0, 1, 0, 0, 0, 1; + // clang-format on K = K * S; R = S * R; } @@ -122,26 +132,30 @@ void KRt_From_P(const Mat34 &P, Mat3 *Kp, Mat3 *Rp, Vec3 *tp) { *tp = t; } -void ProjectionShiftPrincipalPoint(const Mat34 &P, - const Vec2 &principal_point, - const Vec2 &principal_point_new, - Mat34 *P_new) { +void ProjectionShiftPrincipalPoint(const Mat34& P, + const Vec2& principal_point, + const Vec2& principal_point_new, + Mat34* P_new) { Mat3 T; + // clang-format off T << 1, 0, principal_point_new(0) - principal_point(0), 0, 1, principal_point_new(1) - principal_point(1), 0, 0, 1; + // clang-format on *P_new = T * P; } -void ProjectionChangeAspectRatio(const Mat34 &P, - const Vec2 &principal_point, +void ProjectionChangeAspectRatio(const Mat34& P, + const Vec2& principal_point, double aspect_ratio, double aspect_ratio_new, - Mat34 *P_new) { + Mat34* P_new) { Mat3 T; + // clang-format off T << 1, 0, 0, 0, aspect_ratio_new / aspect_ratio, 0, 0, 0, 1; + // clang-format on Mat34 P_temp; ProjectionShiftPrincipalPoint(P, principal_point, Vec2(0, 0), &P_temp); @@ -149,7 +163,7 @@ void ProjectionChangeAspectRatio(const Mat34 &P, ProjectionShiftPrincipalPoint(P_temp, Vec2(0, 0), principal_point, P_new); } -void HomogeneousToEuclidean(const Mat &H, Mat *X) { +void HomogeneousToEuclidean(const Mat& H, Mat* X) { int d = H.rows() - 1; int n = H.cols(); X->resize(d, n); @@ -161,29 +175,29 @@ void HomogeneousToEuclidean(const Mat &H, Mat *X) { } } -void HomogeneousToEuclidean(const Mat3X &h, Mat2X *e) { +void HomogeneousToEuclidean(const Mat3X& h, Mat2X* e) { e->resize(2, h.cols()); e->row(0) = h.row(0).array() / h.row(2).array(); e->row(1) = h.row(1).array() / h.row(2).array(); } -void HomogeneousToEuclidean(const Mat4X &h, Mat3X *e) { +void HomogeneousToEuclidean(const Mat4X& h, Mat3X* e) { e->resize(3, h.cols()); e->row(0) = h.row(0).array() / h.row(3).array(); e->row(1) = h.row(1).array() / h.row(3).array(); e->row(2) = h.row(2).array() / h.row(3).array(); } -void HomogeneousToEuclidean(const Vec3 &H, Vec2 *X) { +void HomogeneousToEuclidean(const Vec3& H, Vec2* X) { double w = H(2); *X << H(0) / w, H(1) / w; } -void HomogeneousToEuclidean(const Vec4 &H, Vec3 *X) { +void HomogeneousToEuclidean(const Vec4& H, Vec3* X) { double w = H(3); *X << H(0) / w, H(1) / w, H(2) / w; } -void EuclideanToHomogeneous(const Mat &X, Mat *H) { +void EuclideanToHomogeneous(const Mat& X, Mat* H) { int d = X.rows(); int n = X.cols(); H->resize(d + 1, n); @@ -191,32 +205,32 @@ void EuclideanToHomogeneous(const Mat &X, Mat *H) { H->row(d).setOnes(); } -void EuclideanToHomogeneous(const Vec2 &X, Vec3 *H) { +void EuclideanToHomogeneous(const Vec2& X, Vec3* H) { *H << X(0), X(1), 1; } -void EuclideanToHomogeneous(const Vec3 &X, Vec4 *H) { +void EuclideanToHomogeneous(const Vec3& X, Vec4* H) { *H << X(0), X(1), X(2), 1; } // TODO(julien) Call conditioning.h/ApplyTransformationToPoints ? -void EuclideanToNormalizedCamera(const Mat2X &x, const Mat3 &K, Mat2X *n) { +void EuclideanToNormalizedCamera(const Mat2X& x, const Mat3& K, Mat2X* n) { Mat3X x_image_h; EuclideanToHomogeneous(x, &x_image_h); Mat3X x_camera_h = K.inverse() * x_image_h; HomogeneousToEuclidean(x_camera_h, n); } -void HomogeneousToNormalizedCamera(const Mat3X &x, const Mat3 &K, Mat2X *n) { +void HomogeneousToNormalizedCamera(const Mat3X& x, const Mat3& K, Mat2X* n) { Mat3X x_camera_h = K.inverse() * x; HomogeneousToEuclidean(x_camera_h, n); } -double Depth(const Mat3 &R, const Vec3 &t, const Vec3 &X) { - return (R*X)(2) + t(2); +double Depth(const Mat3& R, const Vec3& t, const Vec3& X) { + return (R * X)(2) + t(2); } -double Depth(const Mat3 &R, const Vec3 &t, const Vec4 &X) { +double Depth(const Mat3& R, const Vec3& t, const Vec4& X) { Vec3 Xe = X.head<3>() / X(3); return Depth(R, t, Xe); } diff --git a/intern/libmv/libmv/multiview/projection.h b/intern/libmv/libmv/multiview/projection.h index 8f304f31ec6..ba8fc5d8303 100644 --- a/intern/libmv/libmv/multiview/projection.h +++ b/intern/libmv/libmv/multiview/projection.h @@ -25,108 +25,108 @@ namespace libmv { -void P_From_KRt(const Mat3 &K, const Mat3 &R, const Vec3 &t, Mat34 *P); -void KRt_From_P(const Mat34 &P, Mat3 *K, Mat3 *R, Vec3 *t); +void P_From_KRt(const Mat3& K, const Mat3& R, const Vec3& t, Mat34* P); +void KRt_From_P(const Mat34& P, Mat3* K, Mat3* R, Vec3* t); // Applies a change of basis to the image coordinates of the projection matrix // so that the principal point becomes principal_point_new. -void ProjectionShiftPrincipalPoint(const Mat34 &P, - const Vec2 &principal_point, - const Vec2 &principal_point_new, - Mat34 *P_new); +void ProjectionShiftPrincipalPoint(const Mat34& P, + const Vec2& principal_point, + const Vec2& principal_point_new, + Mat34* P_new); // Applies a change of basis to the image coordinates of the projection matrix // so that the aspect ratio becomes aspect_ratio_new. This is done by // stretching the y axis. The aspect ratio is defined as the quotient between // the focal length of the y and the x axis. -void ProjectionChangeAspectRatio(const Mat34 &P, - const Vec2 &principal_point, +void ProjectionChangeAspectRatio(const Mat34& P, + const Vec2& principal_point, double aspect_ratio, double aspect_ratio_new, - Mat34 *P_new); - -void HomogeneousToEuclidean(const Mat &H, Mat *X); -void HomogeneousToEuclidean(const Mat3X &h, Mat2X *e); -void HomogeneousToEuclidean(const Mat4X &h, Mat3X *e); -void HomogeneousToEuclidean(const Vec3 &H, Vec2 *X); -void HomogeneousToEuclidean(const Vec4 &H, Vec3 *X); -inline Vec2 HomogeneousToEuclidean(const Vec3 &h) { + Mat34* P_new); + +void HomogeneousToEuclidean(const Mat& H, Mat* X); +void HomogeneousToEuclidean(const Mat3X& h, Mat2X* e); +void HomogeneousToEuclidean(const Mat4X& h, Mat3X* e); +void HomogeneousToEuclidean(const Vec3& H, Vec2* X); +void HomogeneousToEuclidean(const Vec4& H, Vec3* X); +inline Vec2 HomogeneousToEuclidean(const Vec3& h) { return h.head<2>() / h(2); } -inline Vec3 HomogeneousToEuclidean(const Vec4 &h) { +inline Vec3 HomogeneousToEuclidean(const Vec4& h) { return h.head<3>() / h(3); } -inline Mat2X HomogeneousToEuclidean(const Mat3X &h) { +inline Mat2X HomogeneousToEuclidean(const Mat3X& h) { Mat2X e(2, h.cols()); e.row(0) = h.row(0).array() / h.row(2).array(); e.row(1) = h.row(1).array() / h.row(2).array(); return e; } -void EuclideanToHomogeneous(const Mat &X, Mat *H); -inline Mat3X EuclideanToHomogeneous(const Mat2X &x) { +void EuclideanToHomogeneous(const Mat& X, Mat* H); +inline Mat3X EuclideanToHomogeneous(const Mat2X& x) { Mat3X h(3, x.cols()); h.block(0, 0, 2, x.cols()) = x; h.row(2).setOnes(); return h; } -inline void EuclideanToHomogeneous(const Mat2X &x, Mat3X *h) { +inline void EuclideanToHomogeneous(const Mat2X& x, Mat3X* h) { h->resize(3, x.cols()); h->block(0, 0, 2, x.cols()) = x; h->row(2).setOnes(); } -inline Mat4X EuclideanToHomogeneous(const Mat3X &x) { +inline Mat4X EuclideanToHomogeneous(const Mat3X& x) { Mat4X h(4, x.cols()); h.block(0, 0, 3, x.cols()) = x; h.row(3).setOnes(); return h; } -inline void EuclideanToHomogeneous(const Mat3X &x, Mat4X *h) { +inline void EuclideanToHomogeneous(const Mat3X& x, Mat4X* h) { h->resize(4, x.cols()); h->block(0, 0, 3, x.cols()) = x; h->row(3).setOnes(); } -void EuclideanToHomogeneous(const Vec2 &X, Vec3 *H); -void EuclideanToHomogeneous(const Vec3 &X, Vec4 *H); -inline Vec3 EuclideanToHomogeneous(const Vec2 &x) { +void EuclideanToHomogeneous(const Vec2& X, Vec3* H); +void EuclideanToHomogeneous(const Vec3& X, Vec4* H); +inline Vec3 EuclideanToHomogeneous(const Vec2& x) { return Vec3(x(0), x(1), 1); } -inline Vec4 EuclideanToHomogeneous(const Vec3 &x) { +inline Vec4 EuclideanToHomogeneous(const Vec3& x) { return Vec4(x(0), x(1), x(2), 1); } // Conversion from image coordinates to normalized camera coordinates -void EuclideanToNormalizedCamera(const Mat2X &x, const Mat3 &K, Mat2X *n); -void HomogeneousToNormalizedCamera(const Mat3X &x, const Mat3 &K, Mat2X *n); +void EuclideanToNormalizedCamera(const Mat2X& x, const Mat3& K, Mat2X* n); +void HomogeneousToNormalizedCamera(const Mat3X& x, const Mat3& K, Mat2X* n); -inline Vec2 Project(const Mat34 &P, const Vec3 &X) { +inline Vec2 Project(const Mat34& P, const Vec3& X) { Vec4 HX; HX << X, 1.0; Vec3 hx = P * HX; return hx.head<2>() / hx(2); } -inline void Project(const Mat34 &P, const Vec4 &X, Vec3 *x) { +inline void Project(const Mat34& P, const Vec4& X, Vec3* x) { *x = P * X; } -inline void Project(const Mat34 &P, const Vec4 &X, Vec2 *x) { +inline void Project(const Mat34& P, const Vec4& X, Vec2* x) { Vec3 hx = P * X; *x = hx.head<2>() / hx(2); } -inline void Project(const Mat34 &P, const Vec3 &X, Vec3 *x) { +inline void Project(const Mat34& P, const Vec3& X, Vec3* x) { Vec4 HX; HX << X, 1.0; Project(P, HX, x); } -inline void Project(const Mat34 &P, const Vec3 &X, Vec2 *x) { +inline void Project(const Mat34& P, const Vec3& X, Vec2* x) { Vec3 hx; Project(P, X, &hx); *x = hx.head<2>() / hx(2); } -inline void Project(const Mat34 &P, const Mat4X &X, Mat2X *x) { +inline void Project(const Mat34& P, const Mat4X& X, Mat2X* x) { x->resize(2, X.cols()); for (int c = 0; c < X.cols(); ++c) { Vec3 hx = P * X.col(c); @@ -134,13 +134,13 @@ inline void Project(const Mat34 &P, const Mat4X &X, Mat2X *x) { } } -inline Mat2X Project(const Mat34 &P, const Mat4X &X) { +inline Mat2X Project(const Mat34& P, const Mat4X& X) { Mat2X x; Project(P, X, &x); return x; } -inline void Project(const Mat34 &P, const Mat3X &X, Mat2X *x) { +inline void Project(const Mat34& P, const Mat3X& X, Mat2X* x) { x->resize(2, X.cols()); for (int c = 0; c < X.cols(); ++c) { Vec4 HX; @@ -150,7 +150,7 @@ inline void Project(const Mat34 &P, const Mat3X &X, Mat2X *x) { } } -inline void Project(const Mat34 &P, const Mat3X &X, const Vecu &ids, Mat2X *x) { +inline void Project(const Mat34& P, const Mat3X& X, const Vecu& ids, Mat2X* x) { x->resize(2, ids.size()); Vec4 HX; Vec3 hx; @@ -161,26 +161,26 @@ inline void Project(const Mat34 &P, const Mat3X &X, const Vecu &ids, Mat2X *x) { } } -inline Mat2X Project(const Mat34 &P, const Mat3X &X) { +inline Mat2X Project(const Mat34& P, const Mat3X& X) { Mat2X x(2, X.cols()); Project(P, X, &x); return x; } -inline Mat2X Project(const Mat34 &P, const Mat3X &X, const Vecu &ids) { +inline Mat2X Project(const Mat34& P, const Mat3X& X, const Vecu& ids) { Mat2X x(2, ids.size()); Project(P, X, ids, &x); return x; } -double Depth(const Mat3 &R, const Vec3 &t, const Vec3 &X); -double Depth(const Mat3 &R, const Vec3 &t, const Vec4 &X); +double Depth(const Mat3& R, const Vec3& t, const Vec3& X); +double Depth(const Mat3& R, const Vec3& t, const Vec4& X); /** -* Returns true if the homogenious 3D point X is in front of -* the camera P. -*/ -inline bool isInFrontOfCamera(const Mat34 &P, const Vec4 &X) { + * Returns true if the homogenious 3D point X is in front of + * the camera P. + */ +inline bool isInFrontOfCamera(const Mat34& P, const Vec4& X) { double condition_1 = P.row(2).dot(X) * X[3]; double condition_2 = X[2] * X[3]; if (condition_1 > 0 && condition_2 > 0) @@ -189,37 +189,37 @@ inline bool isInFrontOfCamera(const Mat34 &P, const Vec4 &X) { return false; } -inline bool isInFrontOfCamera(const Mat34 &P, const Vec3 &X) { +inline bool isInFrontOfCamera(const Mat34& P, const Vec3& X) { Vec4 X_homo; X_homo.segment<3>(0) = X; X_homo(3) = 1; - return isInFrontOfCamera( P, X_homo); + return isInFrontOfCamera(P, X_homo); } /** -* Transforms a 2D point from pixel image coordinates to a 2D point in -* normalized image coordinates. -*/ -inline Vec2 ImageToNormImageCoordinates(Mat3 &Kinverse, Vec2 &x) { - Vec3 x_h = Kinverse*EuclideanToHomogeneous(x); - return HomogeneousToEuclidean( x_h ); + * Transforms a 2D point from pixel image coordinates to a 2D point in + * normalized image coordinates. + */ +inline Vec2 ImageToNormImageCoordinates(Mat3& Kinverse, Vec2& x) { + Vec3 x_h = Kinverse * EuclideanToHomogeneous(x); + return HomogeneousToEuclidean(x_h); } /// Estimates the root mean square error (2D) -inline double RootMeanSquareError(const Mat2X &x_image, - const Mat4X &X_world, - const Mat34 &P) { +inline double RootMeanSquareError(const Mat2X& x_image, + const Mat4X& X_world, + const Mat34& P) { size_t num_points = x_image.cols(); Mat2X dx = Project(P, X_world) - x_image; return dx.norm() / num_points; } /// Estimates the root mean square error (2D) -inline double RootMeanSquareError(const Mat2X &x_image, - const Mat3X &X_world, - const Mat3 &K, - const Mat3 &R, - const Vec3 &t) { +inline double RootMeanSquareError(const Mat2X& x_image, + const Mat3X& X_world, + const Mat3& K, + const Mat3& R, + const Vec3& t) { Mat34 P; P_From_KRt(K, R, t, &P); size_t num_points = x_image.cols(); diff --git a/intern/libmv/libmv/multiview/projection_test.cc b/intern/libmv/libmv/multiview/projection_test.cc index 40e766bfae7..683edefa99c 100644 --- a/intern/libmv/libmv/multiview/projection_test.cc +++ b/intern/libmv/libmv/multiview/projection_test.cc @@ -29,14 +29,18 @@ using namespace libmv; TEST(Projection, P_From_KRt) { Mat3 K, Kp; + // clang-format off K << 10, 1, 30, 0, 20, 40, 0, 0, 1; + // clang-format on Mat3 R, Rp; + // clang-format off R << 1, 0, 0, 0, 1, 0, 0, 0, 1; + // clang-format on Vec3 t, tp; t << 1, 2, 3; @@ -62,16 +66,18 @@ Vec4 GetRandomPoint() { TEST(Projection, isInFrontOfCamera) { Mat34 P; + // clang-format off P << 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0; + // clang-format on Vec4 X_front = GetRandomPoint(); Vec4 X_back = GetRandomPoint(); - X_front(2) = 10; /* Any point in the positive Z direction - * where Z > 1 is in front of the camera. */ - X_back(2) = -10; /* Any point in the negative Z direction - * is behind the camera. */ + X_front(2) = 10; /* Any point in the positive Z direction + * where Z > 1 is in front of the camera. */ + X_back(2) = -10; /* Any point in the negative Z direction + * is behind the camera. */ bool res_front = isInFrontOfCamera(P, X_front); bool res_back = isInFrontOfCamera(P, X_back); @@ -82,12 +88,14 @@ TEST(Projection, isInFrontOfCamera) { TEST(AutoCalibration, ProjectionShiftPrincipalPoint) { Mat34 P1, P2; + // clang-format off P1 << 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0; P2 << 1, 0, 3, 0, 0, 1, 4, 0, 0, 0, 1, 0; + // clang-format on Mat34 P1_computed, P2_computed; ProjectionShiftPrincipalPoint(P1, Vec2(0, 0), Vec2(3, 4), &P2_computed); ProjectionShiftPrincipalPoint(P2, Vec2(3, 4), Vec2(0, 0), &P1_computed); @@ -98,12 +106,14 @@ TEST(AutoCalibration, ProjectionShiftPrincipalPoint) { TEST(AutoCalibration, ProjectionChangeAspectRatio) { Mat34 P1, P2; + // clang-format off P1 << 1, 0, 3, 0, 0, 1, 4, 0, 0, 0, 1, 0; P2 << 1, 0, 3, 0, 0, 2, 4, 0, 0, 0, 1, 0; + // clang-format on Mat34 P1_computed, P2_computed; ProjectionChangeAspectRatio(P1, Vec2(3, 4), 1, 2, &P2_computed); ProjectionChangeAspectRatio(P2, Vec2(3, 4), 2, 1, &P1_computed); diff --git a/intern/libmv/libmv/multiview/resection.h b/intern/libmv/libmv/multiview/resection.h index c142d6deeb2..e543827c932 100644 --- a/intern/libmv/libmv/multiview/resection.h +++ b/intern/libmv/libmv/multiview/resection.h @@ -33,23 +33,23 @@ namespace libmv { namespace resection { // x's are 2D image coordinates, (x,y,1), and X's are homogeneous four vectors. -template<typename T> -void Resection(const Matrix<T, 2, Dynamic> &x, - const Matrix<T, 4, Dynamic> &X, - Matrix<T, 3, 4> *P) { +template <typename T> +void Resection(const Matrix<T, 2, Dynamic>& x, + const Matrix<T, 4, Dynamic>& X, + Matrix<T, 3, 4>* P) { int N = x.cols(); assert(X.cols() == N); - Matrix<T, Dynamic, 12> design(2*N, 12); + Matrix<T, Dynamic, 12> design(2 * N, 12); design.setZero(); for (int i = 0; i < N; i++) { T xi = x(0, i); T yi = x(1, i); // See equation (7.2) on page 179 of H&Z. - design.template block<1, 4>(2*i, 4) = -X.col(i).transpose(); - design.template block<1, 4>(2*i, 8) = yi*X.col(i).transpose(); - design.template block<1, 4>(2*i + 1, 0) = X.col(i).transpose(); - design.template block<1, 4>(2*i + 1, 8) = -xi*X.col(i).transpose(); + design.template block<1, 4>(2 * i, 4) = -X.col(i).transpose(); + design.template block<1, 4>(2 * i, 8) = yi * X.col(i).transpose(); + design.template block<1, 4>(2 * i + 1, 0) = X.col(i).transpose(); + design.template block<1, 4>(2 * i + 1, 8) = -xi * X.col(i).transpose(); } Matrix<T, 12, 1> p; Nullspace(&design, &p); diff --git a/intern/libmv/libmv/multiview/resection_test.cc b/intern/libmv/libmv/multiview/resection_test.cc index 368e2281cfa..fb075d02d69 100644 --- a/intern/libmv/libmv/multiview/resection_test.cc +++ b/intern/libmv/libmv/multiview/resection_test.cc @@ -20,12 +20,12 @@ #include <iostream> +#include "libmv/logging/logging.h" #include "libmv/multiview/projection.h" #include "libmv/multiview/resection.h" #include "libmv/multiview/test_data_sets.h" #include "libmv/numeric/numeric.h" #include "testing/testing.h" -#include "libmv/logging/logging.h" namespace { @@ -40,15 +40,15 @@ TEST(Resection, ThreeViews) { Mat4X X(4, npoints); X.block(0, 0, 3, npoints) = d.X; X.row(3).setOnes(); - const Mat2X &x = d.x[i]; + const Mat2X& x = d.x[i]; Mat34 P; Resection(x, X, &P); Mat34 P_expected = d.P(i); // Because the P matrices are homogeneous, it is necessary to be tricky // about the scale factor to make them match. - P_expected *= 1/P_expected.array().abs().sum(); - P *= 1/P.array().abs().sum(); + P_expected *= 1 / P_expected.array().abs().sum(); + P *= 1 / P.array().abs().sum(); if (!((P(0, 0) > 0 && P_expected(0, 0) > 0) || (P(0, 0) < 0 && P_expected(0, 0) < 0))) { P *= -1; diff --git a/intern/libmv/libmv/multiview/test_data_sets.cc b/intern/libmv/libmv/multiview/test_data_sets.cc index 110bde6f762..a927c166d19 100644 --- a/intern/libmv/libmv/multiview/test_data_sets.cc +++ b/intern/libmv/libmv/multiview/test_data_sets.cc @@ -22,24 +22,28 @@ #include <cmath> -#include "libmv/numeric/numeric.h" -#include "libmv/multiview/projection.h" #include "libmv/multiview/fundamental.h" +#include "libmv/multiview/projection.h" +#include "libmv/numeric/numeric.h" namespace libmv { TwoViewDataSet TwoRealisticCameras(bool same_K) { TwoViewDataSet d; + // clang-format off d.K1 << 320, 0, 160, 0, 320, 120, 0, 0, 1; + // clang-format on if (same_K) { d.K2 = d.K1; } else { + // clang-format off d.K2 << 360, 0, 170, 0, 360, 110, 0, 0, 1; + // clang-format on } d.R1 = RotationAroundZ(-0.1); d.R2 = RotationAroundX(-0.1); @@ -59,10 +63,8 @@ TwoViewDataSet TwoRealisticCameras(bool same_K) { return d; } -nViewDatasetConfigator::nViewDatasetConfigator(int fx , int fy, - int cx, int cy, - double distance, - double jitter_amount) { +nViewDatasetConfigator::nViewDatasetConfigator( + int fx, int fy, int cx, int cy, double distance, double jitter_amount) { _fx = fx; _fy = fy; _cx = cx; @@ -71,7 +73,8 @@ nViewDatasetConfigator::nViewDatasetConfigator(int fx , int fy, _jitter_amount = jitter_amount; } -NViewDataSet NRealisticCamerasFull(int nviews, int npoints, +NViewDataSet NRealisticCamerasFull(int nviews, + int npoints, const nViewDatasetConfigator config) { NViewDataSet d; d.n = nviews; @@ -102,9 +105,11 @@ NViewDataSet NRealisticCamerasFull(int nviews, int npoints, jitter *= config._jitter_amount / camera_center.norm(); lookdir = -camera_center + jitter; + // clang-format off d.K[i] << config._fx, 0, config._cx, 0, config._fy, config._cy, 0, 0, 1; + // clang-format on d.R[i] = LookAt(lookdir); d.t[i] = -d.R[i] * camera_center; d.x[i] = Project(d.P(i), d.X); @@ -113,9 +118,10 @@ NViewDataSet NRealisticCamerasFull(int nviews, int npoints, return d; } - -NViewDataSet NRealisticCamerasSparse(int nviews, int npoints, - float view_ratio, unsigned min_projections, +NViewDataSet NRealisticCamerasSparse(int nviews, + int npoints, + float view_ratio, + unsigned min_projections, const nViewDatasetConfigator config) { assert(view_ratio <= 1.0); assert(view_ratio > 0.0); @@ -137,7 +143,7 @@ NViewDataSet NRealisticCamerasSparse(int nviews, int npoints, visibility.setZero(); Mat randoms(nviews, npoints); randoms.setRandom(); - randoms = (randoms.array() + 1)/2.0; + randoms = (randoms.array() + 1) / 2.0; unsigned num_visibles = 0; for (size_t i = 0; i < nviews; ++i) { num_visibles = 0; @@ -174,15 +180,17 @@ NViewDataSet NRealisticCamerasSparse(int nviews, int npoints, jitter *= config._jitter_amount / camera_center.norm(); lookdir = -camera_center + jitter; + // clang-format off d.K[i] << config._fx, 0, config._cx, 0, config._fy, config._cy, 0, 0, 1; + // clang-format on d.R[i] = LookAt(lookdir); d.t[i] = -d.R[i] * camera_center; j_visible = 0; for (size_t j = 0; j < npoints; j++) { if (visibility(i, j)) { - X = d.X.col(j); + X = d.X.col(j); d.x[i].col(j_visible) = Project(d.P(i), X); d.x_ids[i][j_visible] = j; j_visible++; @@ -192,5 +200,4 @@ NViewDataSet NRealisticCamerasSparse(int nviews, int npoints, return d; } - } // namespace libmv diff --git a/intern/libmv/libmv/multiview/test_data_sets.h b/intern/libmv/libmv/multiview/test_data_sets.h index cf01663ca02..0c8785728bd 100644 --- a/intern/libmv/libmv/multiview/test_data_sets.h +++ b/intern/libmv/libmv/multiview/test_data_sets.h @@ -34,8 +34,8 @@ struct TwoViewDataSet { Vec3 t1, t2; // Translation. Mat34 P1, P2; // Projection matrix, P = K(R|t) Mat3 F; // Fundamental matrix. - Mat3X X; // 3D points. - Mat2X x1, x2; // Projected points. + Mat3X X; // 3D points. + Mat2X x1, x2; // Projected points. }; // Two cameras at (-1,-1,-10) and (2,1,-10) looking approximately towards z+. @@ -45,13 +45,13 @@ TwoViewDataSet TwoRealisticCameras(bool same_K = false); // and the other reconstruction data types is that all points are seen by all // cameras. struct NViewDataSet { - vector<Mat3> K; // Internal parameters (fx, fy, etc). - vector<Mat3> R; // Rotation. - vector<Vec3> t; // Translation. - vector<Vec3> C; // Camera centers. - Mat3X X; // 3D points. - vector<Mat2X> x; // Projected points; may have noise added. - vector<Vecu> x_ids; // Indexes of points corresponding to the projections + vector<Mat3> K; // Internal parameters (fx, fy, etc). + vector<Mat3> R; // Rotation. + vector<Vec3> t; // Translation. + vector<Vec3> C; // Camera centers. + Mat3X X; // 3D points. + vector<Mat2X> x; // Projected points; may have noise added. + vector<Vecu> x_ids; // Indexes of points corresponding to the projections int n; // Actual number of cameras. @@ -83,22 +83,26 @@ struct nViewDatasetConfigator { double _dist; double _jitter_amount; - nViewDatasetConfigator(int fx = 1000, int fy = 1000, - int cx = 500, int cy = 500, + nViewDatasetConfigator(int fx = 1000, + int fy = 1000, + int cx = 500, + int cy = 500, double distance = 1.5, double jitter_amount = 0.01); }; -NViewDataSet NRealisticCamerasFull(int nviews, int npoints, - const nViewDatasetConfigator - config = nViewDatasetConfigator()); +NViewDataSet NRealisticCamerasFull( + int nviews, + int npoints, + const nViewDatasetConfigator config = nViewDatasetConfigator()); // Generates sparse projections (not all points are projected) -NViewDataSet NRealisticCamerasSparse(int nviews, int npoints, - float view_ratio = 0.6, - unsigned min_projections = 3, - const nViewDatasetConfigator - config = nViewDatasetConfigator()); +NViewDataSet NRealisticCamerasSparse( + int nviews, + int npoints, + float view_ratio = 0.6, + unsigned min_projections = 3, + const nViewDatasetConfigator config = nViewDatasetConfigator()); } // namespace libmv diff --git a/intern/libmv/libmv/multiview/triangulation.cc b/intern/libmv/libmv/multiview/triangulation.cc index 4d146c8f21b..568625de19d 100644 --- a/intern/libmv/libmv/multiview/triangulation.cc +++ b/intern/libmv/libmv/multiview/triangulation.cc @@ -20,15 +20,17 @@ #include "libmv/multiview/triangulation.h" -#include "libmv/numeric/numeric.h" #include "libmv/multiview/projection.h" +#include "libmv/numeric/numeric.h" namespace libmv { // HZ 12.2 pag.312 -void TriangulateDLT(const Mat34 &P1, const Vec2 &x1, - const Mat34 &P2, const Vec2 &x2, - Vec4 *X_homogeneous) { +void TriangulateDLT(const Mat34& P1, + const Vec2& x1, + const Mat34& P2, + const Vec2& x2, + Vec4* X_homogeneous) { Mat4 design; for (int i = 0; i < 4; ++i) { design(0, i) = x1(0) * P1(2, i) - P1(0, i); @@ -39,9 +41,11 @@ void TriangulateDLT(const Mat34 &P1, const Vec2 &x1, Nullspace(&design, X_homogeneous); } -void TriangulateDLT(const Mat34 &P1, const Vec2 &x1, - const Mat34 &P2, const Vec2 &x2, - Vec3 *X_euclidean) { +void TriangulateDLT(const Mat34& P1, + const Vec2& x1, + const Mat34& P2, + const Vec2& x2, + Vec3* X_euclidean) { Vec4 X_homogeneous; TriangulateDLT(P1, x1, P2, x2, &X_homogeneous); HomogeneousToEuclidean(X_homogeneous, X_euclidean); diff --git a/intern/libmv/libmv/multiview/triangulation.h b/intern/libmv/libmv/multiview/triangulation.h index be878890242..c538433eb8b 100644 --- a/intern/libmv/libmv/multiview/triangulation.h +++ b/intern/libmv/libmv/multiview/triangulation.h @@ -25,13 +25,17 @@ namespace libmv { -void TriangulateDLT(const Mat34 &P1, const Vec2 &x1, - const Mat34 &P2, const Vec2 &x2, - Vec4 *X_homogeneous); +void TriangulateDLT(const Mat34& P1, + const Vec2& x1, + const Mat34& P2, + const Vec2& x2, + Vec4* X_homogeneous); -void TriangulateDLT(const Mat34 &P1, const Vec2 &x1, - const Mat34 &P2, const Vec2 &x2, - Vec3 *X_euclidean); +void TriangulateDLT(const Mat34& P1, + const Vec2& x1, + const Mat34& P2, + const Vec2& x2, + Vec3* X_euclidean); } // namespace libmv diff --git a/intern/libmv/libmv/multiview/triangulation_test.cc b/intern/libmv/libmv/multiview/triangulation_test.cc index 66d1ee25a62..54d20f4ee17 100644 --- a/intern/libmv/libmv/multiview/triangulation_test.cc +++ b/intern/libmv/libmv/multiview/triangulation_test.cc @@ -20,10 +20,10 @@ #include <iostream> -#include "libmv/multiview/triangulation.h" #include "libmv/multiview/fundamental.h" #include "libmv/multiview/projection.h" #include "libmv/multiview/test_data_sets.h" +#include "libmv/multiview/triangulation.h" #include "libmv/numeric/numeric.h" #include "testing/testing.h" diff --git a/intern/libmv/libmv/multiview/two_view_kernel.h b/intern/libmv/libmv/multiview/two_view_kernel.h index 7af0ed5ddab..4df99183ee0 100644 --- a/intern/libmv/libmv/multiview/two_view_kernel.h +++ b/intern/libmv/libmv/multiview/two_view_kernel.h @@ -30,10 +30,10 @@ namespace libmv { namespace two_view { namespace kernel { -template<typename Solver, typename Unnormalizer> +template <typename Solver, typename Unnormalizer> struct NormalizedSolver { enum { MINIMUM_SAMPLES = Solver::MINIMUM_SAMPLES }; - static void Solve(const Mat &x1, const Mat &x2, vector<Mat3> *models) { + static void Solve(const Mat& x1, const Mat& x2, vector<Mat3>* models) { assert(2 == x1.rows()); assert(MINIMUM_SAMPLES <= x1.cols()); assert(x1.rows() == x2.rows()); @@ -53,10 +53,10 @@ struct NormalizedSolver { } }; -template<typename Solver, typename Unnormalizer> +template <typename Solver, typename Unnormalizer> struct IsotropicNormalizedSolver { enum { MINIMUM_SAMPLES = Solver::MINIMUM_SAMPLES }; - static void Solve(const Mat &x1, const Mat &x2, vector<Mat3> *models) { + static void Solve(const Mat& x1, const Mat& x2, vector<Mat3>* models) { assert(2 == x1.rows()); assert(MINIMUM_SAMPLES <= x1.cols()); assert(x1.rows() == x2.rows()); @@ -99,35 +99,32 @@ struct IsotropicNormalizedSolver { // // The fit routine must not clear existing entries in the vector of models; it // should append new solutions to the end. -template<typename SolverArg, - typename ErrorArg, - typename ModelArg = Mat3> +template <typename SolverArg, typename ErrorArg, typename ModelArg = Mat3> class Kernel { public: - Kernel(const Mat &x1, const Mat &x2) : x1_(x1), x2_(x2) {} + Kernel(const Mat& x1, const Mat& x2) : x1_(x1), x2_(x2) {} typedef SolverArg Solver; - typedef ModelArg Model; + typedef ModelArg Model; enum { MINIMUM_SAMPLES = Solver::MINIMUM_SAMPLES }; - void Fit(const vector<int> &samples, vector<Model> *models) const { + void Fit(const vector<int>& samples, vector<Model>* models) const { Mat x1 = ExtractColumns(x1_, samples); Mat x2 = ExtractColumns(x2_, samples); Solver::Solve(x1, x2, models); } - double Error(int sample, const Model &model) const { + double Error(int sample, const Model& model) const { return ErrorArg::Error(model, static_cast<Vec>(x1_.col(sample)), static_cast<Vec>(x2_.col(sample))); } - int NumSamples() const { - return x1_.cols(); - } - static void Solve(const Mat &x1, const Mat &x2, vector<Model> *models) { + int NumSamples() const { return x1_.cols(); } + static void Solve(const Mat& x1, const Mat& x2, vector<Model>* models) { // By offering this, Kernel types can be passed to templates. Solver::Solve(x1, x2, models); } + protected: - const Mat &x1_; - const Mat &x2_; + const Mat& x1_; + const Mat& x2_; }; } // namespace kernel diff --git a/intern/libmv/libmv/numeric/dogleg.h b/intern/libmv/libmv/numeric/dogleg.h index bf6f996ddaf..62abfbdcd4b 100644 --- a/intern/libmv/libmv/numeric/dogleg.h +++ b/intern/libmv/libmv/numeric/dogleg.h @@ -32,18 +32,18 @@ #include <cmath> #include <cstdio> -#include "libmv/numeric/numeric.h" -#include "libmv/numeric/function_derivative.h" #include "libmv/logging/logging.h" +#include "libmv/numeric/function_derivative.h" +#include "libmv/numeric/numeric.h" namespace libmv { -template<typename Function, - typename Jacobian = NumericJacobian<Function>, - typename Solver = Eigen::PartialPivLU< - Matrix<typename Function::FMatrixType::RealScalar, - Function::XMatrixType::RowsAtCompileTime, - Function::XMatrixType::RowsAtCompileTime> > > +template <typename Function, + typename Jacobian = NumericJacobian<Function>, + typename Solver = Eigen::PartialPivLU< + Matrix<typename Function::FMatrixType::RealScalar, + Function::XMatrixType::RowsAtCompileTime, + Function::XMatrixType::RowsAtCompileTime>>> class Dogleg { public: typedef typename Function::XMatrixType::RealScalar Scalar; @@ -51,10 +51,12 @@ class Dogleg { typedef typename Function::XMatrixType Parameters; typedef Matrix<typename Function::FMatrixType::RealScalar, Function::FMatrixType::RowsAtCompileTime, - Function::XMatrixType::RowsAtCompileTime> JMatrixType; + Function::XMatrixType::RowsAtCompileTime> + JMatrixType; typedef Matrix<typename JMatrixType::RealScalar, JMatrixType::ColsAtCompileTime, - JMatrixType::ColsAtCompileTime> AMatrixType; + JMatrixType::ColsAtCompileTime> + AMatrixType; enum Status { RUNNING, @@ -71,34 +73,38 @@ class Dogleg { STEEPEST_DESCENT, }; - Dogleg(const Function &f) - : f_(f), df_(f) {} + Dogleg(const Function& f) : f_(f), df_(f) {} struct SolverParameters { SolverParameters() - : gradient_threshold(1e-16), - relative_step_threshold(1e-16), - error_threshold(1e-16), - initial_trust_radius(1e0), - max_iterations(500) {} + : gradient_threshold(1e-16), + relative_step_threshold(1e-16), + error_threshold(1e-16), + initial_trust_radius(1e0), + max_iterations(500) {} Scalar gradient_threshold; // eps > max(J'*f(x)) Scalar relative_step_threshold; // eps > ||dx|| / ||x|| Scalar error_threshold; // eps > ||f(x)|| Scalar initial_trust_radius; // Initial u for solving normal equations. - int max_iterations; // Maximum number of solver iterations. + int max_iterations; // Maximum number of solver iterations. }; struct Results { Scalar error_magnitude; // ||f(x)|| Scalar gradient_magnitude; // ||J'f(x)|| - int iterations; + int iterations; Status status; }; - Status Update(const Parameters &x, const SolverParameters ¶ms, - JMatrixType *J, AMatrixType *A, FVec *error, Parameters *g) { + Status Update(const Parameters& x, + const SolverParameters& params, + JMatrixType* J, + AMatrixType* A, + FVec* error, + Parameters* g) { *J = df_(x); - // TODO(keir): In the case of m = n, avoid computing A and just do J^-1 directly. + // TODO(keir): In the case of m = n, avoid computing A and just do J^-1 + // directly. *A = (*J).transpose() * (*J); *error = f_(x); *g = (*J).transpose() * *error; @@ -110,12 +116,12 @@ class Dogleg { return RUNNING; } - Step SolveDoglegDirection(const Parameters &dx_sd, - const Parameters &dx_gn, + Step SolveDoglegDirection(const Parameters& dx_sd, + const Parameters& dx_gn, Scalar radius, Scalar alpha, - Parameters *dx_dl, - Scalar *beta) { + Parameters* dx_dl, + Scalar* beta) { Parameters a, b_minus_a; // Solve for Dogleg step dx_dl. if (dx_gn.norm() < radius) { @@ -128,30 +134,29 @@ class Dogleg { } else { Parameters a = alpha * dx_sd; - const Parameters &b = dx_gn; + const Parameters& b = dx_gn; b_minus_a = a - b; Scalar Mbma2 = b_minus_a.squaredNorm(); Scalar Ma2 = a.squaredNorm(); Scalar c = a.dot(b_minus_a); - Scalar radius2 = radius*radius; + Scalar radius2 = radius * radius; if (c <= 0) { - *beta = (-c + sqrt(c*c + Mbma2*(radius2 - Ma2)))/(Mbma2); + *beta = (-c + sqrt(c * c + Mbma2 * (radius2 - Ma2))) / (Mbma2); } else { - *beta = (radius2 - Ma2) / - (c + sqrt(c*c + Mbma2*(radius2 - Ma2))); + *beta = (radius2 - Ma2) / (c + sqrt(c * c + Mbma2 * (radius2 - Ma2))); } - *dx_dl = alpha * dx_sd + (*beta) * (dx_gn - alpha*dx_sd); + *dx_dl = alpha * dx_sd + (*beta) * (dx_gn - alpha * dx_sd); return DOGLEG; } } - Results minimize(Parameters *x_and_min) { + Results minimize(Parameters* x_and_min) { SolverParameters params; return minimize(params, x_and_min); } - Results minimize(const SolverParameters ¶ms, Parameters *x_and_min) { - Parameters &x = *x_and_min; + Results minimize(const SolverParameters& params, Parameters* x_and_min) { + Parameters& x = *x_and_min; JMatrixType J; AMatrixType A; FVec error; @@ -167,18 +172,21 @@ class Dogleg { Parameters dx_sd; // Steepest descent step. Parameters dx_dl; // Dogleg step. Parameters dx_gn; // Gauss-Newton step. - printf("iteration ||f(x)|| max(g) radius\n"); + printf("iteration ||f(x)|| max(g) radius\n"); int i = 0; for (; results.status == RUNNING && i < params.max_iterations; ++i) { printf("%9d %12g %12g %12g", - i, f_(x).norm(), g.array().abs().maxCoeff(), radius); + i, + f_(x).norm(), + g.array().abs().maxCoeff(), + radius); - //LG << "iteration: " << i; - //LG << "||f(x)||: " << f_(x).norm(); - //LG << "max(g): " << g.cwise().abs().maxCoeff(); - //LG << "radius: " << radius; + // LG << "iteration: " << i; + // LG << "||f(x)||: " << f_(x).norm(); + // LG << "max(g): " << g.cwise().abs().maxCoeff(); + // LG << "radius: " << radius; // Eqn 3.19 from [1] - Scalar alpha = g.squaredNorm() / (J*g).squaredNorm(); + Scalar alpha = g.squaredNorm() / (J * g).squaredNorm(); // Solve for steepest descent direction dx_sd. dx_sd = -g; @@ -199,11 +207,11 @@ class Dogleg { // Solve for dogleg direction dx_dl. Scalar beta = 0; - Step step = SolveDoglegDirection(dx_sd, dx_gn, radius, alpha, - &dx_dl, &beta); + Step step = + SolveDoglegDirection(dx_sd, dx_gn, radius, alpha, &dx_dl, &beta); Scalar e3 = params.relative_step_threshold; - if (dx_dl.norm() < e3*(x.norm() + e3)) { + if (dx_dl.norm() < e3 * (x.norm() + e3)) { results.status = RELATIVE_STEP_SIZE_TOO_SMALL; break; } @@ -214,16 +222,19 @@ class Dogleg { if (step == GAUSS_NEWTON) { predicted = f_(x).squaredNorm(); } else if (step == STEEPEST_DESCENT) { - predicted = radius * (2*alpha*g.norm() - radius) / 2 / alpha; + predicted = radius * (2 * alpha * g.norm() - radius) / 2 / alpha; } else if (step == DOGLEG) { - predicted = 0.5 * alpha * (1-beta)*(1-beta)*g.squaredNorm() + - beta*(2-beta)*f_(x).squaredNorm(); + predicted = 0.5 * alpha * (1 - beta) * (1 - beta) * g.squaredNorm() + + beta * (2 - beta) * f_(x).squaredNorm(); } Scalar rho = actual / predicted; - if (step == GAUSS_NEWTON) printf(" GAUSS"); - if (step == STEEPEST_DESCENT) printf(" STEE"); - if (step == DOGLEG) printf(" DOGL"); + if (step == GAUSS_NEWTON) + printf(" GAUSS"); + if (step == STEEPEST_DESCENT) + printf(" STEE"); + if (step == DOGLEG) + printf(" DOGL"); printf(" %12g %12g %12g\n", rho, actual, predicted); @@ -234,7 +245,7 @@ class Dogleg { x_updated = true; } if (rho > 0.75) { - radius = std::max(radius, 3*dx_dl.norm()); + radius = std::max(radius, 3 * dx_dl.norm()); } else if (rho < 0.25) { radius /= 2; if (radius < e3 * (x.norm() + e3)) { @@ -252,10 +263,10 @@ class Dogleg { } private: - const Function &f_; + const Function& f_; Jacobian df_; }; -} // namespace mv +} // namespace libmv #endif // LIBMV_NUMERIC_DOGLEG_H diff --git a/intern/libmv/libmv/numeric/dogleg_test.cc b/intern/libmv/libmv/numeric/dogleg_test.cc index 90c46c31672..a5ab1957632 100644 --- a/intern/libmv/libmv/numeric/dogleg_test.cc +++ b/intern/libmv/libmv/numeric/dogleg_test.cc @@ -18,8 +18,8 @@ // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS // IN THE SOFTWARE. -#include "testing/testing.h" #include "libmv/numeric/dogleg.h" +#include "testing/testing.h" using namespace libmv; @@ -29,26 +29,26 @@ class F { public: typedef Vec4 FMatrixType; typedef Vec3 XMatrixType; - Vec4 operator()(const Vec3 &x) const { + Vec4 operator()(const Vec3& x) const { double x1 = x.x() - 2; double y1 = x.y() - 5; double z1 = x.z(); - Vec4 fx; fx << x1*x1 + z1*z1, - y1*y1 + z1*z1, - z1*z1, - x1*x1; + Vec4 fx; + fx << x1 * x1 + z1 * z1, y1 * y1 + z1 * z1, z1 * z1, x1 * x1; return fx; } }; TEST(Dogleg, SimpleCase) { - Vec3 x; x << 0.76026643, -30.01799744, 0.55192142; + Vec3 x; + x << 0.76026643, -30.01799744, 0.55192142; F f; Dogleg<F>::SolverParameters params; Dogleg<F> lm(f); /* TODO(sergey): Better error handling. */ /* Dogleg<F>::Results results = */ lm.minimize(params, &x); - Vec3 expected_min_x; expected_min_x << 2, 5, 0; + Vec3 expected_min_x; + expected_min_x << 2, 5, 0; EXPECT_MATRIX_NEAR(expected_min_x, x, 1e-5); } @@ -59,20 +59,21 @@ class F32 { public: typedef Vec2 FMatrixType; typedef Vec2 XMatrixType; - Vec2 operator()(const Vec2 &x) const { + Vec2 operator()(const Vec2& x) const { double x1 = x(0); - double x2 = 10*x(0)/(x(0) + 0.1) + 2*x(1)*x(1); - Vec2 fx; fx << x1, x2; + double x2 = 10 * x(0) / (x(0) + 0.1) + 2 * x(1) * x(1); + Vec2 fx; + fx << x1, x2; return fx; } }; class JF32 { public: - JF32(const F32 &f) { (void) f; } - Mat2 operator()(const Vec2 &x) { - Mat2 J; J << 1, 0, - 1./pow(x(0) + 0.1, 2), 4*x(1)*x(1); + JF32(const F32& f) { (void)f; } + Mat2 operator()(const Vec2& x) { + Mat2 J; + J << 1, 0, 1. / pow(x(0) + 0.1, 2), 4 * x(1) * x(1); return J; } }; diff --git a/intern/libmv/libmv/numeric/function_derivative.h b/intern/libmv/libmv/numeric/function_derivative.h index 9820885f04e..30d7c4d34e9 100644 --- a/intern/libmv/libmv/numeric/function_derivative.h +++ b/intern/libmv/libmv/numeric/function_derivative.h @@ -23,8 +23,8 @@ #include <cmath> -#include "libmv/numeric/numeric.h" #include "libmv/logging/logging.h" +#include "libmv/numeric/numeric.h" namespace libmv { @@ -36,7 +36,7 @@ enum NumericJacobianMode { FORWARD, }; -template<typename Function, NumericJacobianMode mode = CENTRAL> +template <typename Function, NumericJacobianMode mode = CENTRAL> class NumericJacobian { public: typedef typename Function::XMatrixType Parameters; @@ -45,12 +45,12 @@ class NumericJacobian { typedef Matrix<typename Function::FMatrixType::RealScalar, Function::FMatrixType::RowsAtCompileTime, Function::XMatrixType::RowsAtCompileTime> - JMatrixType; + JMatrixType; - NumericJacobian(const Function &f) : f_(f) {} + NumericJacobian(const Function& f) : f_(f) {} // TODO(keir): Perhaps passing the jacobian back by value is not a good idea. - JMatrixType operator()(const Parameters &x) { + JMatrixType operator()(const Parameters& x) { // Empirically determined constant. Parameters eps = x.array().abs() * XScalar(1e-5); // To handle cases where a paremeter is exactly zero, instead use the mean @@ -87,12 +87,13 @@ class NumericJacobian { } return jacobian; } + private: - const Function &f_; + const Function& f_; }; -template<typename Function, typename Jacobian> -bool CheckJacobian(const Function &f, const typename Function::XMatrixType &x) { +template <typename Function, typename Jacobian> +bool CheckJacobian(const Function& f, const typename Function::XMatrixType& x) { Jacobian j_analytic(f); NumericJacobian<Function> j_numeric(f); diff --git a/intern/libmv/libmv/numeric/function_derivative_test.cc b/intern/libmv/libmv/numeric/function_derivative_test.cc index 8d976d3e9a0..defeedaa8a4 100644 --- a/intern/libmv/libmv/numeric/function_derivative_test.cc +++ b/intern/libmv/libmv/numeric/function_derivative_test.cc @@ -18,9 +18,9 @@ // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS // IN THE SOFTWARE. -#include "testing/testing.h" -#include "libmv/numeric/numeric.h" #include "libmv/numeric/function_derivative.h" +#include "libmv/numeric/numeric.h" +#include "testing/testing.h" using namespace libmv; @@ -30,22 +30,22 @@ class F { public: typedef Vec2 FMatrixType; typedef Vec3 XMatrixType; - Vec2 operator()(const Vec3 &x) const { + Vec2 operator()(const Vec3& x) const { Vec2 fx; - fx << 0.19*x(0) + 0.19*x(1)*x(1) + x(2), - 3*sin(x(0)) + 2*cos(x(1)); + fx << 0.19 * x(0) + 0.19 * x(1) * x(1) + x(2), + 3 * sin(x(0)) + 2 * cos(x(1)); return fx; } - Mat23 J(const Vec3 &x) const { + Mat23 J(const Vec3& x) const { Mat23 jacobian; - jacobian << 0.19, 2*0.19*x(1), 1.0, - 3*cos(x(0)), -2*sin(x(1)), 0; + jacobian << 0.19, 2 * 0.19 * x(1), 1.0, 3 * cos(x(0)), -2 * sin(x(1)), 0; return jacobian; } }; TEST(FunctionDerivative, SimpleCase) { - Vec3 x; x << 0.76026643, 0.01799744, 0.55192142; + Vec3 x; + x << 0.76026643, 0.01799744, 0.55192142; F f; NumericJacobian<F, CENTRAL> J(f); EXPECT_MATRIX_NEAR(f.J(x), J(x), 1e-8); diff --git a/intern/libmv/libmv/numeric/levenberg_marquardt.h b/intern/libmv/libmv/numeric/levenberg_marquardt.h index 2af9a62cf7b..30c04a5ad5c 100644 --- a/intern/libmv/libmv/numeric/levenberg_marquardt.h +++ b/intern/libmv/libmv/numeric/levenberg_marquardt.h @@ -31,18 +31,18 @@ #include <cmath> -#include "libmv/numeric/numeric.h" -#include "libmv/numeric/function_derivative.h" #include "libmv/logging/logging.h" +#include "libmv/numeric/function_derivative.h" +#include "libmv/numeric/numeric.h" namespace libmv { -template<typename Function, - typename Jacobian = NumericJacobian<Function>, - typename Solver = Eigen::PartialPivLU< - Matrix<typename Function::FMatrixType::RealScalar, - Function::XMatrixType::RowsAtCompileTime, - Function::XMatrixType::RowsAtCompileTime> > > +template <typename Function, + typename Jacobian = NumericJacobian<Function>, + typename Solver = Eigen::PartialPivLU< + Matrix<typename Function::FMatrixType::RealScalar, + Function::XMatrixType::RowsAtCompileTime, + Function::XMatrixType::RowsAtCompileTime>>> class LevenbergMarquardt { public: typedef typename Function::XMatrixType::RealScalar Scalar; @@ -50,10 +50,12 @@ class LevenbergMarquardt { typedef typename Function::XMatrixType Parameters; typedef Matrix<typename Function::FMatrixType::RealScalar, Function::FMatrixType::RowsAtCompileTime, - Function::XMatrixType::RowsAtCompileTime> JMatrixType; + Function::XMatrixType::RowsAtCompileTime> + JMatrixType; typedef Matrix<typename JMatrixType::RealScalar, JMatrixType::ColsAtCompileTime, - JMatrixType::ColsAtCompileTime> AMatrixType; + JMatrixType::ColsAtCompileTime> + AMatrixType; // TODO(keir): Some of these knobs can be derived from each other and // removed, instead of requiring the user to set them. @@ -65,32 +67,35 @@ class LevenbergMarquardt { HIT_MAX_ITERATIONS, }; - LevenbergMarquardt(const Function &f) - : f_(f), df_(f) {} + LevenbergMarquardt(const Function& f) : f_(f), df_(f) {} struct SolverParameters { SolverParameters() - : gradient_threshold(1e-16), - relative_step_threshold(1e-16), - error_threshold(1e-16), - initial_scale_factor(1e-3), - max_iterations(100) {} + : gradient_threshold(1e-16), + relative_step_threshold(1e-16), + error_threshold(1e-16), + initial_scale_factor(1e-3), + max_iterations(100) {} Scalar gradient_threshold; // eps > max(J'*f(x)) Scalar relative_step_threshold; // eps > ||dx|| / ||x|| Scalar error_threshold; // eps > ||f(x)|| Scalar initial_scale_factor; // Initial u for solving normal equations. - int max_iterations; // Maximum number of solver iterations. + int max_iterations; // Maximum number of solver iterations. }; struct Results { Scalar error_magnitude; // ||f(x)|| Scalar gradient_magnitude; // ||J'f(x)|| - int iterations; + int iterations; Status status; }; - Status Update(const Parameters &x, const SolverParameters ¶ms, - JMatrixType *J, AMatrixType *A, FVec *error, Parameters *g) { + Status Update(const Parameters& x, + const SolverParameters& params, + JMatrixType* J, + AMatrixType* A, + FVec* error, + Parameters* g) { *J = df_(x); *A = (*J).transpose() * (*J); *error = -f_(x); @@ -103,13 +108,13 @@ class LevenbergMarquardt { return RUNNING; } - Results minimize(Parameters *x_and_min) { + Results minimize(Parameters* x_and_min) { SolverParameters params; minimize(params, x_and_min); } - Results minimize(const SolverParameters ¶ms, Parameters *x_and_min) { - Parameters &x = *x_and_min; + Results minimize(const SolverParameters& params, Parameters* x_and_min) { + Parameters& x = *x_and_min; JMatrixType J; AMatrixType A; FVec error; @@ -118,7 +123,7 @@ class LevenbergMarquardt { Results results; results.status = Update(x, params, &J, &A, &error, &g); - Scalar u = Scalar(params.initial_scale_factor*A.diagonal().maxCoeff()); + Scalar u = Scalar(params.initial_scale_factor * A.diagonal().maxCoeff()); Scalar v = 2; Parameters dx, x_new; @@ -130,7 +135,8 @@ class LevenbergMarquardt { VLOG(3) << "u: " << u; VLOG(3) << "v: " << v; - AMatrixType A_augmented = A + u*AMatrixType::Identity(J.cols(), J.cols()); + AMatrixType A_augmented = + A + u * AMatrixType::Identity(J.cols(), J.cols()); Solver solver(A_augmented); dx = solver.solve(g); bool solved = (A_augmented * dx).isApprox(g); @@ -146,14 +152,14 @@ class LevenbergMarquardt { // Rho is the ratio of the actual reduction in error to the reduction // in error that would be obtained if the problem was linear. // See [1] for details. - Scalar rho((error.squaredNorm() - f_(x_new).squaredNorm()) - / dx.dot(u*dx + g)); + Scalar rho((error.squaredNorm() - f_(x_new).squaredNorm()) / + dx.dot(u * dx + g)); if (rho > 0) { // Accept the Gauss-Newton step because the linear model fits well. x = x_new; results.status = Update(x, params, &J, &A, &error, &g); - Scalar tmp = Scalar(2*rho-1); - u = u*std::max(1/3., 1 - (tmp*tmp*tmp)); + Scalar tmp = Scalar(2 * rho - 1); + u = u * std::max(1 / 3., 1 - (tmp * tmp * tmp)); v = 2; continue; } @@ -174,10 +180,10 @@ class LevenbergMarquardt { } private: - const Function &f_; + const Function& f_; Jacobian df_; }; -} // namespace mv +} // namespace libmv #endif // LIBMV_NUMERIC_LEVENBERG_MARQUARDT_H diff --git a/intern/libmv/libmv/numeric/levenberg_marquardt_test.cc b/intern/libmv/libmv/numeric/levenberg_marquardt_test.cc index fc3f9ebbb29..805aac275b4 100644 --- a/intern/libmv/libmv/numeric/levenberg_marquardt_test.cc +++ b/intern/libmv/libmv/numeric/levenberg_marquardt_test.cc @@ -18,8 +18,8 @@ // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS // IN THE SOFTWARE. -#include "testing/testing.h" #include "libmv/numeric/levenberg_marquardt.h" +#include "testing/testing.h" using namespace libmv; @@ -29,14 +29,12 @@ class F { public: typedef Vec4 FMatrixType; typedef Vec3 XMatrixType; - Vec4 operator()(const Vec3 &x) const { + Vec4 operator()(const Vec3& x) const { double x1 = x.x() - 2; double y1 = x.y() - 5; double z1 = x.z(); - Vec4 fx; fx << x1*x1 + z1*z1, - y1*y1 + z1*z1, - z1*z1, - x1*x1; + Vec4 fx; + fx << x1 * x1 + z1 * z1, y1 * y1 + z1 * z1, z1 * z1, x1 * x1; return fx; } }; diff --git a/intern/libmv/libmv/numeric/numeric.cc b/intern/libmv/libmv/numeric/numeric.cc index 3fc1e3b2bfd..b7660950c2a 100644 --- a/intern/libmv/libmv/numeric/numeric.cc +++ b/intern/libmv/libmv/numeric/numeric.cc @@ -18,7 +18,6 @@ // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS // IN THE SOFTWARE. - #include "libmv/numeric/numeric.h" namespace libmv { @@ -27,9 +26,11 @@ Mat3 RotationAroundX(double angle) { double c, s; sincos(angle, &s, &c); Mat3 R; + // clang-format off R << 1, 0, 0, 0, c, -s, 0, s, c; + // clang-format on return R; } @@ -37,9 +38,11 @@ Mat3 RotationAroundY(double angle) { double c, s; sincos(angle, &s, &c); Mat3 R; + // clang-format off R << c, 0, s, 0, 1, 0, -s, 0, c; + // clang-format on return R; } @@ -47,14 +50,15 @@ Mat3 RotationAroundZ(double angle) { double c, s; sincos(angle, &s, &c); Mat3 R; + // clang-format off R << c, -s, 0, s, c, 0, 0, 0, 1; + // clang-format on return R; } - -Mat3 RotationRodrigues(const Vec3 &axis) { +Mat3 RotationRodrigues(const Vec3& axis) { double theta = axis.norm(); Vec3 w = axis / theta; Mat3 W = CrossProductMatrix(w); @@ -62,7 +66,6 @@ Mat3 RotationRodrigues(const Vec3 &axis) { return Mat3::Identity() + sin(theta) * W + (1 - cos(theta)) * W * W; } - Mat3 LookAt(Vec3 center) { Vec3 zc = center.normalized(); Vec3 xc = Vec3::UnitY().cross(zc).normalized(); @@ -74,19 +77,21 @@ Mat3 LookAt(Vec3 center) { return R; } -Mat3 CrossProductMatrix(const Vec3 &x) { +Mat3 CrossProductMatrix(const Vec3& x) { Mat3 X; + // clang-format off X << 0, -x(2), x(1), x(2), 0, -x(0), -x(1), x(0), 0; + // clang-format on return X; } -void MeanAndVarianceAlongRows(const Mat &A, - Vec *mean_pointer, - Vec *variance_pointer) { - Vec &mean = *mean_pointer; - Vec &variance = *variance_pointer; +void MeanAndVarianceAlongRows(const Mat& A, + Vec* mean_pointer, + Vec* variance_pointer) { + Vec& mean = *mean_pointer; + Vec& variance = *variance_pointer; int n = A.rows(); int m = A.cols(); mean.resize(n); @@ -108,29 +113,28 @@ void MeanAndVarianceAlongRows(const Mat &A, } } -void HorizontalStack(const Mat &left, const Mat &right, Mat *stacked) { +void HorizontalStack(const Mat& left, const Mat& right, Mat* stacked) { assert(left.rows() == right.rows()); int n = left.rows(); int m1 = left.cols(); int m2 = right.cols(); stacked->resize(n, m1 + m2); - stacked->block(0, 0, n, m1) = left; + stacked->block(0, 0, n, m1) = left; stacked->block(0, m1, n, m2) = right; } -void MatrixColumn(const Mat &A, int i, Vec2 *v) { +void MatrixColumn(const Mat& A, int i, Vec2* v) { assert(A.rows() == 2); *v << A(0, i), A(1, i); } -void MatrixColumn(const Mat &A, int i, Vec3 *v) { +void MatrixColumn(const Mat& A, int i, Vec3* v) { assert(A.rows() == 3); *v << A(0, i), A(1, i), A(2, i); } -void MatrixColumn(const Mat &A, int i, Vec4 *v) { +void MatrixColumn(const Mat& A, int i, Vec4* v) { assert(A.rows() == 4); *v << A(0, i), A(1, i), A(2, i), A(3, i); } } // namespace libmv - diff --git a/intern/libmv/libmv/numeric/numeric.h b/intern/libmv/libmv/numeric/numeric.h index f5478bee6ab..e3d44226338 100644 --- a/intern/libmv/libmv/numeric/numeric.h +++ b/intern/libmv/libmv/numeric/numeric.h @@ -34,10 +34,9 @@ #include <Eigen/SVD> #if !defined(__MINGW64__) -# if defined(_WIN32) || defined(__APPLE__) || \ - defined(__FreeBSD__) || defined(__NetBSD__) || \ - defined(__HAIKU__) -inline void sincos(double x, double *sinx, double *cosx) { +# if defined(_WIN32) || defined(__APPLE__) || defined(__FreeBSD__) || \ + defined(__NetBSD__) || defined(__HAIKU__) +inline void sincos(double x, double* sinx, double* cosx) { *sinx = sin(x); *cosx = cos(x); } @@ -46,11 +45,11 @@ inline void sincos(double x, double *sinx, double *cosx) { #if (defined(WIN32) || defined(WIN64)) && !defined(__MINGW32__) inline long lround(double d) { - return (long)(d>0 ? d+0.5 : ceil(d-0.5)); + return (long)(d > 0 ? d + 0.5 : ceil(d - 0.5)); } # if _MSC_VER < 1800 inline int round(double d) { - return (d>0) ? int(d+0.5) : int(d-0.5); + return (d > 0) ? int(d + 0.5) : int(d - 0.5); } # endif // _MSC_VER < 1800 typedef unsigned int uint; @@ -92,25 +91,25 @@ typedef Eigen::Matrix<double, 4, 4, Eigen::RowMajor> RMat4; typedef Eigen::Matrix<double, 2, Eigen::Dynamic> Mat2X; typedef Eigen::Matrix<double, 3, Eigen::Dynamic> Mat3X; typedef Eigen::Matrix<double, 4, Eigen::Dynamic> Mat4X; -typedef Eigen::Matrix<double, Eigen::Dynamic, 2> MatX2; -typedef Eigen::Matrix<double, Eigen::Dynamic, 3> MatX3; -typedef Eigen::Matrix<double, Eigen::Dynamic, 4> MatX4; -typedef Eigen::Matrix<double, Eigen::Dynamic, 5> MatX5; -typedef Eigen::Matrix<double, Eigen::Dynamic, 6> MatX6; -typedef Eigen::Matrix<double, Eigen::Dynamic, 7> MatX7; -typedef Eigen::Matrix<double, Eigen::Dynamic, 8> MatX8; -typedef Eigen::Matrix<double, Eigen::Dynamic, 9> MatX9; +typedef Eigen::Matrix<double, Eigen::Dynamic, 2> MatX2; +typedef Eigen::Matrix<double, Eigen::Dynamic, 3> MatX3; +typedef Eigen::Matrix<double, Eigen::Dynamic, 4> MatX4; +typedef Eigen::Matrix<double, Eigen::Dynamic, 5> MatX5; +typedef Eigen::Matrix<double, Eigen::Dynamic, 6> MatX6; +typedef Eigen::Matrix<double, Eigen::Dynamic, 7> MatX7; +typedef Eigen::Matrix<double, Eigen::Dynamic, 8> MatX8; +typedef Eigen::Matrix<double, Eigen::Dynamic, 9> MatX9; typedef Eigen::Matrix<double, Eigen::Dynamic, 15> MatX15; typedef Eigen::Matrix<double, Eigen::Dynamic, 16> MatX16; typedef Eigen::Vector2d Vec2; typedef Eigen::Vector3d Vec3; typedef Eigen::Vector4d Vec4; -typedef Eigen::Matrix<double, 5, 1> Vec5; -typedef Eigen::Matrix<double, 6, 1> Vec6; -typedef Eigen::Matrix<double, 7, 1> Vec7; -typedef Eigen::Matrix<double, 8, 1> Vec8; -typedef Eigen::Matrix<double, 9, 1> Vec9; +typedef Eigen::Matrix<double, 5, 1> Vec5; +typedef Eigen::Matrix<double, 6, 1> Vec6; +typedef Eigen::Matrix<double, 7, 1> Vec7; +typedef Eigen::Matrix<double, 8, 1> Vec8; +typedef Eigen::Matrix<double, 9, 1> Vec9; typedef Eigen::Matrix<double, 10, 1> Vec10; typedef Eigen::Matrix<double, 11, 1> Vec11; typedef Eigen::Matrix<double, 12, 1> Vec12; @@ -133,15 +132,13 @@ typedef Eigen::Vector2i Vec2i; typedef Eigen::Vector3i Vec3i; typedef Eigen::Vector4i Vec4i; -typedef Eigen::Matrix<float, - Eigen::Dynamic, - Eigen::Dynamic, - Eigen::RowMajor> RMatf; +typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> + RMatf; typedef Eigen::NumTraits<double> EigenDouble; -using Eigen::Map; using Eigen::Dynamic; +using Eigen::Map; using Eigen::Matrix; // Find U, s, and VT such that @@ -149,7 +146,7 @@ using Eigen::Matrix; // A = U * diag(s) * VT // template <typename TMat, typename TVec> -inline void SVD(TMat * /*A*/, Vec * /*s*/, Mat * /*U*/, Mat * /*VT*/) { +inline void SVD(TMat* /*A*/, Vec* /*s*/, Mat* /*U*/, Mat* /*VT*/) { assert(0); } @@ -158,11 +155,11 @@ inline void SVD(TMat * /*A*/, Vec * /*s*/, Mat * /*U*/, Mat * /*VT*/) { // Destroys A and resizes x if necessary. // TODO(maclean): Take the SVD of the transpose instead of this zero padding. template <typename TMat, typename TVec> -double Nullspace(TMat *A, TVec *nullspace) { +double Nullspace(TMat* A, TVec* nullspace) { Eigen::JacobiSVD<TMat> svd(*A, Eigen::ComputeFullV); - (*nullspace) = svd.matrixV().col(A->cols()-1); + (*nullspace) = svd.matrixV().col(A->cols() - 1); if (A->rows() >= A->cols()) - return svd.singularValues()(A->cols()-1); + return svd.singularValues()(A->cols() - 1); else return 0.0; } @@ -173,55 +170,55 @@ double Nullspace(TMat *A, TVec *nullspace) { // the singluar value corresponding to the solution x1. Destroys A and resizes // x if necessary. template <typename TMat, typename TVec1, typename TVec2> -double Nullspace2(TMat *A, TVec1 *x1, TVec2 *x2) { +double Nullspace2(TMat* A, TVec1* x1, TVec2* x2) { Eigen::JacobiSVD<TMat> svd(*A, Eigen::ComputeFullV); *x1 = svd.matrixV().col(A->cols() - 1); *x2 = svd.matrixV().col(A->cols() - 2); if (A->rows() >= A->cols()) - return svd.singularValues()(A->cols()-1); + return svd.singularValues()(A->cols() - 1); else return 0.0; } // In place transpose for square matrices. -template<class TA> -inline void TransposeInPlace(TA *A) { +template <class TA> +inline void TransposeInPlace(TA* A) { *A = A->transpose().eval(); } -template<typename TVec> -inline double NormL1(const TVec &x) { +template <typename TVec> +inline double NormL1(const TVec& x) { return x.array().abs().sum(); } -template<typename TVec> -inline double NormL2(const TVec &x) { +template <typename TVec> +inline double NormL2(const TVec& x) { return x.norm(); } -template<typename TVec> -inline double NormLInfinity(const TVec &x) { +template <typename TVec> +inline double NormLInfinity(const TVec& x) { return x.array().abs().maxCoeff(); } -template<typename TVec> -inline double DistanceL1(const TVec &x, const TVec &y) { +template <typename TVec> +inline double DistanceL1(const TVec& x, const TVec& y) { return (x - y).array().abs().sum(); } -template<typename TVec> -inline double DistanceL2(const TVec &x, const TVec &y) { +template <typename TVec> +inline double DistanceL2(const TVec& x, const TVec& y) { return (x - y).norm(); } -template<typename TVec> -inline double DistanceLInfinity(const TVec &x, const TVec &y) { +template <typename TVec> +inline double DistanceLInfinity(const TVec& x, const TVec& y) { return (x - y).array().abs().maxCoeff(); } // Normalize a vector with the L1 norm, and return the norm before it was // normalized. -template<typename TVec> -inline double NormalizeL1(TVec *x) { +template <typename TVec> +inline double NormalizeL1(TVec* x) { double norm = NormL1(*x); *x /= norm; return norm; @@ -229,8 +226,8 @@ inline double NormalizeL1(TVec *x) { // Normalize a vector with the L2 norm, and return the norm before it was // normalized. -template<typename TVec> -inline double NormalizeL2(TVec *x) { +template <typename TVec> +inline double NormalizeL2(TVec* x) { double norm = NormL2(*x); *x /= norm; return norm; @@ -238,15 +235,15 @@ inline double NormalizeL2(TVec *x) { // Normalize a vector with the L^Infinity norm, and return the norm before it // was normalized. -template<typename TVec> -inline double NormalizeLInfinity(TVec *x) { +template <typename TVec> +inline double NormalizeLInfinity(TVec* x) { double norm = NormLInfinity(*x); *x /= norm; return norm; } // Return the square of a number. -template<typename T> +template <typename T> inline T Square(T x) { return x * x; } @@ -258,7 +255,7 @@ Mat3 RotationAroundZ(double angle); // Returns the rotation matrix of a rotation of angle |axis| around axis. // This is computed using the Rodrigues formula, see: // http://mathworld.wolfram.com/RodriguesRotationFormula.html -Mat3 RotationRodrigues(const Vec3 &axis); +Mat3 RotationRodrigues(const Vec3& axis); // Make a rotation matrix such that center becomes the direction of the // positive z-axis, and y is oriented close to up. @@ -266,177 +263,173 @@ Mat3 LookAt(Vec3 center); // Return a diagonal matrix from a vector containg the diagonal values. template <typename TVec> -inline Mat Diag(const TVec &x) { +inline Mat Diag(const TVec& x) { return x.asDiagonal(); } -template<typename TMat> -inline double FrobeniusNorm(const TMat &A) { +template <typename TMat> +inline double FrobeniusNorm(const TMat& A) { return sqrt(A.array().abs2().sum()); } -template<typename TMat> -inline double FrobeniusDistance(const TMat &A, const TMat &B) { +template <typename TMat> +inline double FrobeniusDistance(const TMat& A, const TMat& B) { return FrobeniusNorm(A - B); } -inline Vec3 CrossProduct(const Vec3 &x, const Vec3 &y) { +inline Vec3 CrossProduct(const Vec3& x, const Vec3& y) { return x.cross(y); } -Mat3 CrossProductMatrix(const Vec3 &x); +Mat3 CrossProductMatrix(const Vec3& x); -void MeanAndVarianceAlongRows(const Mat &A, - Vec *mean_pointer, - Vec *variance_pointer); +void MeanAndVarianceAlongRows(const Mat& A, + Vec* mean_pointer, + Vec* variance_pointer); #if defined(_WIN32) - // TODO(bomboze): un-#if this for both platforms once tested under Windows - /* This solution was extensively discussed here - http://forum.kde.org/viewtopic.php?f=74&t=61940 */ - #define SUM_OR_DYNAMIC(x, y) (x == Eigen::Dynamic || y == Eigen::Dynamic) ? Eigen::Dynamic : (x+y) - - template<typename Derived1, typename Derived2> - struct hstack_return { - typedef typename Derived1::Scalar Scalar; - enum { - RowsAtCompileTime = Derived1::RowsAtCompileTime, - ColsAtCompileTime = SUM_OR_DYNAMIC(Derived1::ColsAtCompileTime, - Derived2::ColsAtCompileTime), - Options = Derived1::Flags&Eigen::RowMajorBit ? Eigen::RowMajor : 0, - MaxRowsAtCompileTime = Derived1::MaxRowsAtCompileTime, - MaxColsAtCompileTime = SUM_OR_DYNAMIC(Derived1::MaxColsAtCompileTime, - Derived2::MaxColsAtCompileTime) - }; - typedef Eigen::Matrix<Scalar, - RowsAtCompileTime, - ColsAtCompileTime, - Options, - MaxRowsAtCompileTime, - MaxColsAtCompileTime> type; +// TODO(bomboze): un-#if this for both platforms once tested under Windows +/* This solution was extensively discussed here + http://forum.kde.org/viewtopic.php?f=74&t=61940 */ +# define SUM_OR_DYNAMIC(x, y) \ + (x == Eigen::Dynamic || y == Eigen::Dynamic) ? Eigen::Dynamic : (x + y) + +template <typename Derived1, typename Derived2> +struct hstack_return { + typedef typename Derived1::Scalar Scalar; + enum { + RowsAtCompileTime = Derived1::RowsAtCompileTime, + ColsAtCompileTime = SUM_OR_DYNAMIC(Derived1::ColsAtCompileTime, + Derived2::ColsAtCompileTime), + Options = Derived1::Flags & Eigen::RowMajorBit ? Eigen::RowMajor : 0, + MaxRowsAtCompileTime = Derived1::MaxRowsAtCompileTime, + MaxColsAtCompileTime = SUM_OR_DYNAMIC(Derived1::MaxColsAtCompileTime, + Derived2::MaxColsAtCompileTime) }; - - template<typename Derived1, typename Derived2> - typename hstack_return<Derived1, Derived2>::type - HStack(const Eigen::MatrixBase<Derived1>& lhs, - const Eigen::MatrixBase<Derived2>& rhs) { - typename hstack_return<Derived1, Derived2>::type res; - res.resize(lhs.rows(), lhs.cols()+rhs.cols()); - res << lhs, rhs; - return res; - }; - - - template<typename Derived1, typename Derived2> - struct vstack_return { - typedef typename Derived1::Scalar Scalar; - enum { - RowsAtCompileTime = SUM_OR_DYNAMIC(Derived1::RowsAtCompileTime, - Derived2::RowsAtCompileTime), - ColsAtCompileTime = Derived1::ColsAtCompileTime, - Options = Derived1::Flags&Eigen::RowMajorBit ? Eigen::RowMajor : 0, - MaxRowsAtCompileTime = SUM_OR_DYNAMIC(Derived1::MaxRowsAtCompileTime, - Derived2::MaxRowsAtCompileTime), - MaxColsAtCompileTime = Derived1::MaxColsAtCompileTime - }; - typedef Eigen::Matrix<Scalar, - RowsAtCompileTime, - ColsAtCompileTime, - Options, - MaxRowsAtCompileTime, - MaxColsAtCompileTime> type; + typedef Eigen::Matrix<Scalar, + RowsAtCompileTime, + ColsAtCompileTime, + Options, + MaxRowsAtCompileTime, + MaxColsAtCompileTime> + type; +}; + +template <typename Derived1, typename Derived2> +typename hstack_return<Derived1, Derived2>::type HStack( + const Eigen::MatrixBase<Derived1>& lhs, + const Eigen::MatrixBase<Derived2>& rhs) { + typename hstack_return<Derived1, Derived2>::type res; + res.resize(lhs.rows(), lhs.cols() + rhs.cols()); + res << lhs, rhs; + return res; +}; + +template <typename Derived1, typename Derived2> +struct vstack_return { + typedef typename Derived1::Scalar Scalar; + enum { + RowsAtCompileTime = SUM_OR_DYNAMIC(Derived1::RowsAtCompileTime, + Derived2::RowsAtCompileTime), + ColsAtCompileTime = Derived1::ColsAtCompileTime, + Options = Derived1::Flags & Eigen::RowMajorBit ? Eigen::RowMajor : 0, + MaxRowsAtCompileTime = SUM_OR_DYNAMIC(Derived1::MaxRowsAtCompileTime, + Derived2::MaxRowsAtCompileTime), + MaxColsAtCompileTime = Derived1::MaxColsAtCompileTime }; - - template<typename Derived1, typename Derived2> - typename vstack_return<Derived1, Derived2>::type - VStack(const Eigen::MatrixBase<Derived1>& lhs, - const Eigen::MatrixBase<Derived2>& rhs) { - typename vstack_return<Derived1, Derived2>::type res; - res.resize(lhs.rows()+rhs.rows(), lhs.cols()); - res << lhs, rhs; - return res; - }; - + typedef Eigen::Matrix<Scalar, + RowsAtCompileTime, + ColsAtCompileTime, + Options, + MaxRowsAtCompileTime, + MaxColsAtCompileTime> + type; +}; + +template <typename Derived1, typename Derived2> +typename vstack_return<Derived1, Derived2>::type VStack( + const Eigen::MatrixBase<Derived1>& lhs, + const Eigen::MatrixBase<Derived2>& rhs) { + typename vstack_return<Derived1, Derived2>::type res; + res.resize(lhs.rows() + rhs.rows(), lhs.cols()); + res << lhs, rhs; + return res; +}; #else // _WIN32 - // Since it is not possible to typedef privately here, use a macro. - // Always take dynamic columns if either side is dynamic. - #define COLS \ - ((ColsLeft == Eigen::Dynamic || ColsRight == Eigen::Dynamic) \ - ? Eigen::Dynamic : (ColsLeft + ColsRight)) - - // Same as above, except that prefer fixed size if either is fixed. - #define ROWS \ - ((RowsLeft == Eigen::Dynamic && RowsRight == Eigen::Dynamic) \ - ? Eigen::Dynamic \ - : ((RowsLeft == Eigen::Dynamic) \ - ? RowsRight \ - : RowsLeft \ - ) \ - ) - - // TODO(keir): Add a static assert if both rows are at compiletime. - template<typename T, int RowsLeft, int RowsRight, int ColsLeft, int ColsRight> - Eigen::Matrix<T, ROWS, COLS> - HStack(const Eigen::Matrix<T, RowsLeft, ColsLeft> &left, - const Eigen::Matrix<T, RowsRight, ColsRight> &right) { - assert(left.rows() == right.rows()); - int n = left.rows(); - int m1 = left.cols(); - int m2 = right.cols(); - - Eigen::Matrix<T, ROWS, COLS> stacked(n, m1 + m2); - stacked.block(0, 0, n, m1) = left; - stacked.block(0, m1, n, m2) = right; - return stacked; - } - - // Reuse the above macros by swapping the order of Rows and Cols. Nasty, but - // the duplication is worse. - // TODO(keir): Add a static assert if both rows are at compiletime. - // TODO(keir): Mail eigen list about making this work for general expressions - // rather than only matrix types. - template<typename T, int RowsLeft, int RowsRight, int ColsLeft, int ColsRight> - Eigen::Matrix<T, COLS, ROWS> - VStack(const Eigen::Matrix<T, ColsLeft, RowsLeft> &top, - const Eigen::Matrix<T, ColsRight, RowsRight> &bottom) { - assert(top.cols() == bottom.cols()); - int n1 = top.rows(); - int n2 = bottom.rows(); - int m = top.cols(); - - Eigen::Matrix<T, COLS, ROWS> stacked(n1 + n2, m); - stacked.block(0, 0, n1, m) = top; - stacked.block(n1, 0, n2, m) = bottom; - return stacked; - } - #undef COLS - #undef ROWS -#endif // _WIN32 +// Since it is not possible to typedef privately here, use a macro. +// Always take dynamic columns if either side is dynamic. +# define COLS \ + ((ColsLeft == Eigen::Dynamic || ColsRight == Eigen::Dynamic) \ + ? Eigen::Dynamic \ + : (ColsLeft + ColsRight)) + +// Same as above, except that prefer fixed size if either is fixed. +# define ROWS \ + ((RowsLeft == Eigen::Dynamic && RowsRight == Eigen::Dynamic) \ + ? Eigen::Dynamic \ + : ((RowsLeft == Eigen::Dynamic) ? RowsRight : RowsLeft)) + +// TODO(keir): Add a static assert if both rows are at compiletime. +template <typename T, int RowsLeft, int RowsRight, int ColsLeft, int ColsRight> +Eigen::Matrix<T, ROWS, COLS> HStack( + const Eigen::Matrix<T, RowsLeft, ColsLeft>& left, + const Eigen::Matrix<T, RowsRight, ColsRight>& right) { + assert(left.rows() == right.rows()); + int n = left.rows(); + int m1 = left.cols(); + int m2 = right.cols(); + + Eigen::Matrix<T, ROWS, COLS> stacked(n, m1 + m2); + stacked.block(0, 0, n, m1) = left; + stacked.block(0, m1, n, m2) = right; + return stacked; +} +// Reuse the above macros by swapping the order of Rows and Cols. Nasty, but +// the duplication is worse. +// TODO(keir): Add a static assert if both rows are at compiletime. +// TODO(keir): Mail eigen list about making this work for general expressions +// rather than only matrix types. +template <typename T, int RowsLeft, int RowsRight, int ColsLeft, int ColsRight> +Eigen::Matrix<T, COLS, ROWS> VStack( + const Eigen::Matrix<T, ColsLeft, RowsLeft>& top, + const Eigen::Matrix<T, ColsRight, RowsRight>& bottom) { + assert(top.cols() == bottom.cols()); + int n1 = top.rows(); + int n2 = bottom.rows(); + int m = top.cols(); + Eigen::Matrix<T, COLS, ROWS> stacked(n1 + n2, m); + stacked.block(0, 0, n1, m) = top; + stacked.block(n1, 0, n2, m) = bottom; + return stacked; +} +# undef COLS +# undef ROWS +#endif // _WIN32 -void HorizontalStack(const Mat &left, const Mat &right, Mat *stacked); +void HorizontalStack(const Mat& left, const Mat& right, Mat* stacked); -template<typename TTop, typename TBot, typename TStacked> -void VerticalStack(const TTop &top, const TBot &bottom, TStacked *stacked) { +template <typename TTop, typename TBot, typename TStacked> +void VerticalStack(const TTop& top, const TBot& bottom, TStacked* stacked) { assert(top.cols() == bottom.cols()); int n1 = top.rows(); int n2 = bottom.rows(); int m = top.cols(); stacked->resize(n1 + n2, m); - stacked->block(0, 0, n1, m) = top; + stacked->block(0, 0, n1, m) = top; stacked->block(n1, 0, n2, m) = bottom; } -void MatrixColumn(const Mat &A, int i, Vec2 *v); -void MatrixColumn(const Mat &A, int i, Vec3 *v); -void MatrixColumn(const Mat &A, int i, Vec4 *v); +void MatrixColumn(const Mat& A, int i, Vec2* v); +void MatrixColumn(const Mat& A, int i, Vec3* v); +void MatrixColumn(const Mat& A, int i, Vec4* v); template <typename TMat, typename TCols> -TMat ExtractColumns(const TMat &A, const TCols &columns) { +TMat ExtractColumns(const TMat& A, const TCols& columns) { TMat compressed(A.rows(), columns.size()); for (int i = 0; i < columns.size(); ++i) { compressed.col(i) = A.col(columns[i]); @@ -445,12 +438,12 @@ TMat ExtractColumns(const TMat &A, const TCols &columns) { } template <typename TMat, typename TDest> -void reshape(const TMat &a, int rows, int cols, TDest *b) { - assert(a.rows()*a.cols() == rows*cols); +void reshape(const TMat& a, int rows, int cols, TDest* b) { + assert(a.rows() * a.cols() == rows * cols); b->resize(rows, cols); for (int i = 0; i < rows; i++) { for (int j = 0; j < cols; j++) { - (*b)(i, j) = a[cols*i + j]; + (*b)(i, j) = a[cols * i + j]; } } } @@ -467,24 +460,21 @@ inline bool isnan(double i) { /// and negative values template <typename FloatType> FloatType ceil0(const FloatType& value) { - FloatType result = std::ceil(std::fabs(value)); - return (value < 0.0) ? -result : result; + FloatType result = std::ceil(std::fabs(value)); + return (value < 0.0) ? -result : result; } /// Returns the skew anti-symmetric matrix of a vector -inline Mat3 SkewMat(const Vec3 &x) { +inline Mat3 SkewMat(const Vec3& x) { Mat3 skew; - skew << 0 , -x(2), x(1), - x(2), 0 , -x(0), - -x(1), x(0), 0; + skew << 0, -x(2), x(1), x(2), 0, -x(0), -x(1), x(0), 0; return skew; } /// Returns the skew anti-symmetric matrix of a vector with only /// the first two (independent) lines -inline Mat23 SkewMatMinimal(const Vec2 &x) { +inline Mat23 SkewMatMinimal(const Vec2& x) { Mat23 skew; - skew << 0, -1, x(1), - 1, 0, -x(0); + skew << 0, -1, x(1), 1, 0, -x(0); return skew; } @@ -496,7 +486,8 @@ inline Mat3 RotationFromEulerVector(Vec3 euler_vector) { } Vec3 w = euler_vector / theta; Mat3 w_hat = CrossProductMatrix(w); - return Mat3::Identity() + w_hat*sin(theta) + w_hat*w_hat*(1 - cos(theta)); + return Mat3::Identity() + w_hat * sin(theta) + + w_hat * w_hat * (1 - cos(theta)); } } // namespace libmv diff --git a/intern/libmv/libmv/numeric/numeric_test.cc b/intern/libmv/libmv/numeric/numeric_test.cc index 0cdfaf33ab2..b2650a04658 100644 --- a/intern/libmv/libmv/numeric/numeric_test.cc +++ b/intern/libmv/libmv/numeric/numeric_test.cc @@ -27,9 +27,11 @@ namespace { TEST(Numeric, DynamicSizedNullspace) { Mat A(3, 4); + // clang-format off A << 0.76026643, 0.01799744, 0.55192142, 0.8699745, 0.42016166, 0.97863392, 0.33711682, 0.14479271, 0.51016811, 0.66528302, 0.54395496, 0.57794893; + // clang-format on Vec x; double s = Nullspace(&A, &x); EXPECT_NEAR(0.0, s, 1e-15); @@ -39,9 +41,11 @@ TEST(Numeric, DynamicSizedNullspace) { TEST(Numeric, FixedSizeMatrixNullspace) { Mat34 A; + // clang-format off A << 0.76026643, 0.01799744, 0.55192142, 0.8699745, 0.42016166, 0.97863392, 0.33711682, 0.14479271, 0.51016811, 0.66528302, 0.54395496, 0.57794893; + // clang-format on Vec x; double s = Nullspace(&A, &x); EXPECT_NEAR(0.0, s, 1e-15); @@ -51,10 +55,12 @@ TEST(Numeric, FixedSizeMatrixNullspace) { TEST(Numeric, NullspaceMatchesLapackSVD) { Mat43 A; + // clang-format off A << 0.76026643, 0.01799744, 0.55192142, 0.8699745, 0.42016166, 0.97863392, 0.33711682, 0.14479271, 0.51016811, 0.66528302, 0.54395496, 0.57794893; + // clang-format on Vec x; double s = Nullspace(&A, &x); EXPECT_NEAR(1.0, x.norm(), 1e-15); @@ -68,10 +74,12 @@ TEST(Numeric, NullspaceMatchesLapackSVD) { TEST(Numeric, Nullspace2) { Mat43 A; + // clang-format off A << 0.76026643, 0.01799744, 0.55192142, 0.8699745, 0.42016166, 0.97863392, 0.33711682, 0.14479271, 0.51016811, 0.66528302, 0.54395496, 0.57794893; + // clang-format on Vec3 x1, x2; double s = Nullspace2(&A, &x1, &x2); EXPECT_NEAR(1.0, x1.norm(), 1e-15); @@ -80,14 +88,14 @@ TEST(Numeric, Nullspace2) { EXPECT_NEAR(-0.64999717, x1(0), 1e-8); EXPECT_NEAR(-0.18452646, x1(1), 1e-8); - EXPECT_NEAR( 0.7371931, x1(2), 1e-8); + EXPECT_NEAR(0.7371931, x1(2), 1e-8); if (x2(0) < 0) { x2 *= -1; } - EXPECT_NEAR( 0.34679618, x2(0), 1e-8); + EXPECT_NEAR(0.34679618, x2(0), 1e-8); EXPECT_NEAR(-0.93519689, x2(1), 1e-8); - EXPECT_NEAR( 0.07168809, x2(2), 1e-8); + EXPECT_NEAR(0.07168809, x2(2), 1e-8); } TEST(Numeric, TinyMatrixSquareTranspose) { @@ -105,8 +113,8 @@ TEST(Numeric, NormalizeL1) { x << 1, 2; double l1 = NormalizeL1(&x); EXPECT_DOUBLE_EQ(3., l1); - EXPECT_DOUBLE_EQ(1./3., x(0)); - EXPECT_DOUBLE_EQ(2./3., x(1)); + EXPECT_DOUBLE_EQ(1. / 3., x(0)); + EXPECT_DOUBLE_EQ(2. / 3., x(1)); } TEST(Numeric, NormalizeL2) { @@ -114,8 +122,8 @@ TEST(Numeric, NormalizeL2) { x << 1, 2; double l2 = NormalizeL2(&x); EXPECT_DOUBLE_EQ(sqrt(5.0), l2); - EXPECT_DOUBLE_EQ(1./sqrt(5.), x(0)); - EXPECT_DOUBLE_EQ(2./sqrt(5.), x(1)); + EXPECT_DOUBLE_EQ(1. / sqrt(5.), x(0)); + EXPECT_DOUBLE_EQ(2. / sqrt(5.), x(1)); } TEST(Numeric, Diag) { @@ -130,31 +138,32 @@ TEST(Numeric, Diag) { TEST(Numeric, Determinant) { Mat A(2, 2); - A << 1, 2, - -1, 3; + A << 1, 2, -1, 3; double detA = A.determinant(); EXPECT_NEAR(5, detA, 1e-8); Mat B(4, 4); + // clang-format off B << 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15; + // clang-format on double detB = B.determinant(); EXPECT_NEAR(0, detB, 1e-8); Mat3 C; - C << 0, 1, 2, - 3, 4, 5, - 6, 7, 1; + C << 0, 1, 2, 3, 4, 5, 6, 7, 1; double detC = C.determinant(); EXPECT_NEAR(21, detC, 1e-8); } TEST(Numeric, Inverse) { Mat A(2, 2), A1; + // clang-format off A << 1, 2, -1, 3; + // clang-format on Mat I = A * A.inverse(); EXPECT_NEAR(1, I(0, 0), 1e-8); @@ -163,10 +172,12 @@ TEST(Numeric, Inverse) { EXPECT_NEAR(1, I(1, 1), 1e-8); Mat B(4, 4), B1; + // clang-format off B << 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 2, 11, 12, 13, 14, 4; + // clang-format on Mat I2 = B * B.inverse(); EXPECT_NEAR(1, I2(0, 0), 1e-8); EXPECT_NEAR(0, I2(0, 1), 1e-8); @@ -182,8 +193,10 @@ TEST(Numeric, Inverse) { TEST(Numeric, MeanAndVarianceAlongRows) { int n = 4; Mat points(2, n); + // clang-format off points << 0, 0, 1, 1, 0, 2, 1, 3; + // clang-format on Vec mean, variance; MeanAndVarianceAlongRows(points, &mean, &variance); @@ -213,15 +226,17 @@ TEST(Numeric, HStack) { Mat x(2, 1), y(2, 1), z(2, 2); x << 1, 2; y << 3, 4; + // clang-format off z << 1, 3, 2, 4; + // clang-format on Vec2 xC = x, yC = y; - Mat2 xy = HStack(x, y); + Mat2 xy = HStack(x, y); EXPECT_MATRIX_EQ(z, xy); - EXPECT_MATRIX_EQ(z, HStack(x, y)); - EXPECT_MATRIX_EQ(z, HStack(x, yC)); + EXPECT_MATRIX_EQ(z, HStack(x, y)); + EXPECT_MATRIX_EQ(z, HStack(x, yC)); EXPECT_MATRIX_EQ(z, HStack(xC, y)); EXPECT_MATRIX_EQ(z, HStack(xC, yC)); } @@ -230,6 +245,7 @@ TEST(Numeric, HStack) { // resulting stacked matrices properly propagate the fixed dimensions. TEST(Numeric, VStack) { Mat x(2, 2), y(2, 2), z(4, 2); + // clang-format off x << 1, 2, 3, 4; y << 10, 20, @@ -238,13 +254,14 @@ TEST(Numeric, VStack) { 3, 4, 10, 20, 30, 40; + // clang-format on Mat2 xC = x, yC = y; - Mat xy = VStack(x, y); + Mat xy = VStack(x, y); EXPECT_MATRIX_EQ(z, xy); - EXPECT_MATRIX_EQ(z, VStack(x, y)); - EXPECT_MATRIX_EQ(z, VStack(x, yC)); + EXPECT_MATRIX_EQ(z, VStack(x, y)); + EXPECT_MATRIX_EQ(z, VStack(x, yC)); EXPECT_MATRIX_EQ(z, VStack(xC, y)); EXPECT_MATRIX_EQ(z, VStack(xC, yC)); } @@ -293,17 +310,21 @@ TEST(Numeric, CrossProductMatrix) { TEST(Numeric, MatrixColumn) { Mat A2(2, 3); Vec2 v2; + // clang-format off A2 << 1, 2, 3, 4, 5, 6; + // clang-format on MatrixColumn(A2, 1, &v2); EXPECT_EQ(2, v2(0)); EXPECT_EQ(5, v2(1)); Mat A3(3, 3); Vec3 v3; + // clang-format off A3 << 1, 2, 3, 4, 5, 6, 7, 8, 9; + // clang-format on MatrixColumn(A3, 1, &v3); EXPECT_EQ(2, v3(0)); EXPECT_EQ(5, v3(1)); @@ -311,14 +332,16 @@ TEST(Numeric, MatrixColumn) { Mat A4(4, 3); Vec4 v4; + // clang-format off A4 << 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12; + // clang-format on MatrixColumn(A4, 1, &v4); - EXPECT_EQ( 2, v4(0)); - EXPECT_EQ( 5, v4(1)); - EXPECT_EQ( 8, v4(2)); + EXPECT_EQ(2, v4(0)); + EXPECT_EQ(5, v4(1)); + EXPECT_EQ(8, v4(2)); EXPECT_EQ(11, v4(3)); } @@ -337,7 +360,8 @@ TEST(Numeric, Mat3MatProduct) { // This gives a compile error. TEST(Numeric, Vec3Negative) { - Vec3 y; y << 1, 2, 3; + Vec3 y; + y << 1, 2, 3; Vec3 x = -y; EXPECT_EQ(-1, x(0)); EXPECT_EQ(-2, x(1)); @@ -357,19 +381,23 @@ TEST(Numeric, Vec3VecInteroperability) { // This segfaults inside lapack. TEST(Numeric, DeterminantLU7) { Mat A(5, 5); + // clang-format off A << 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1; + // clang-format on EXPECT_NEAR(1, A.determinant(), 1e-8); } // This segfaults inside lapack. TEST(Numeric, DeterminantLU) { Mat A(2, 2); + // clang-format off A << 1, 2, -1, 3; + // clang-format on EXPECT_NEAR(5, A.determinant(), 1e-8); } @@ -377,19 +405,24 @@ TEST(Numeric, DeterminantLU) { // Keir: Not with eigen2! TEST(Numeric, InplaceProduct) { Mat2 K, S; + // clang-format off K << 1, 0, 0, 1; S << 1, 0, 0, 1; K = K * S; + // clang-format on EXPECT_MATRIX_NEAR(Mat2::Identity(), K, 1e-8); } TEST(Numeric, ExtractColumns) { Mat2X A(2, 5); + // clang-format off A << 1, 2, 3, 4, 5, 6, 7, 8, 9, 10; - Vec2i columns; columns << 0, 2; + // clang-format on + Vec2i columns; + columns << 0, 2; Mat2X extracted = ExtractColumns(A, columns); EXPECT_NEAR(1, extracted(0, 0), 1e-15); EXPECT_NEAR(3, extracted(0, 1), 1e-15); @@ -418,21 +451,22 @@ TEST(Numeric, RotationRodrigues) { TEST(Numeric, LookAt) { // Simple orthogonality check. - Vec3 e; e << 1, 2, 3; + Vec3 e; + e << 1, 2, 3; Mat3 R = LookAt(e), I = Mat3::Identity(); - Mat3 RRT = R*R.transpose(); - Mat3 RTR = R.transpose()*R; + Mat3 RRT = R * R.transpose(); + Mat3 RTR = R.transpose() * R; EXPECT_MATRIX_NEAR(I, RRT, 1e-15); EXPECT_MATRIX_NEAR(I, RTR, 1e-15); } TEST(Numeric, Reshape) { - Vec4 x; x << 1, 2, 3, 4; + Vec4 x; + x << 1, 2, 3, 4; Mat2 M, M_expected; reshape(x, 2, 2, &M); - M_expected << 1, 2, - 3, 4; + M_expected << 1, 2, 3, 4; EXPECT_MATRIX_NEAR(M_expected, M, 1e-15); } diff --git a/intern/libmv/libmv/numeric/poly.h b/intern/libmv/libmv/numeric/poly.h index 76ba062d475..a3d3801a399 100644 --- a/intern/libmv/libmv/numeric/poly.h +++ b/intern/libmv/libmv/numeric/poly.h @@ -21,8 +21,8 @@ #ifndef LIBMV_NUMERIC_POLY_H_ #define LIBMV_NUMERIC_POLY_H_ -#include <cmath> #include <stdio.h> +#include <cmath> namespace libmv { @@ -35,9 +35,8 @@ namespace libmv { // if there are 2 roots, only x0 and x1 are set. // // The GSL cubic solver was used as a reference for this routine. -template<typename Real> -int SolveCubicPolynomial(Real a, Real b, Real c, - Real *x0, Real *x1, Real *x2) { +template <typename Real> +int SolveCubicPolynomial(Real a, Real b, Real c, Real* x0, Real* x1, Real* x2) { Real q = a * a - 3 * b; Real r = 2 * a * a * a - 9 * a * b + 27 * c; @@ -65,12 +64,12 @@ int SolveCubicPolynomial(Real a, Real b, Real c, Real sqrtQ = sqrt(Q); if (R > 0) { *x0 = -2 * sqrtQ - a / 3; - *x1 = sqrtQ - a / 3; - *x2 = sqrtQ - a / 3; + *x1 = sqrtQ - a / 3; + *x2 = sqrtQ - a / 3; } else { - *x0 = -sqrtQ - a / 3; - *x1 = -sqrtQ - a / 3; - *x2 = 2 * sqrtQ - a / 3; + *x0 = -sqrtQ - a / 3; + *x1 = -sqrtQ - a / 3; + *x2 = 2 * sqrtQ - a / 3; } return 3; @@ -97,15 +96,15 @@ int SolveCubicPolynomial(Real a, Real b, Real c, return 3; } Real sgnR = (R >= 0 ? 1 : -1); - Real A = -sgnR * pow(fabs(R) + sqrt(R2 - Q3), 1.0/3.0); + Real A = -sgnR * pow(fabs(R) + sqrt(R2 - Q3), 1.0 / 3.0); Real B = Q / A; *x0 = A + B - a / 3; return 1; } // The coefficients are in ascending powers, i.e. coeffs[N]*x^N. -template<typename Real> -int SolveCubicPolynomial(const Real *coeffs, Real *solutions) { +template <typename Real> +int SolveCubicPolynomial(const Real* coeffs, Real* solutions) { if (coeffs[0] == 0.0) { // TODO(keir): This is a quadratic not a cubic. Implement a quadratic // solver! @@ -114,10 +113,8 @@ int SolveCubicPolynomial(const Real *coeffs, Real *solutions) { Real a = coeffs[2] / coeffs[3]; Real b = coeffs[1] / coeffs[3]; Real c = coeffs[0] / coeffs[3]; - return SolveCubicPolynomial(a, b, c, - solutions + 0, - solutions + 1, - solutions + 2); + return SolveCubicPolynomial( + a, b, c, solutions + 0, solutions + 1, solutions + 2); } } // namespace libmv #endif // LIBMV_NUMERIC_POLY_H_ diff --git a/intern/libmv/libmv/numeric/poly_test.cc b/intern/libmv/libmv/numeric/poly_test.cc index 69f887b416c..cb85c068468 100644 --- a/intern/libmv/libmv/numeric/poly_test.cc +++ b/intern/libmv/libmv/numeric/poly_test.cc @@ -18,8 +18,8 @@ // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS // IN THE SOFTWARE. -#include "libmv/numeric/numeric.h" #include "libmv/numeric/poly.h" +#include "libmv/numeric/numeric.h" #include "testing/testing.h" using namespace libmv; @@ -34,8 +34,8 @@ namespace { // // x^3 - (c+b+a) * x^2 + (a*b+(b+a)*c) * x - a*b*c = 0. // = p = q = r -void CoeffsForCubicZeros(double a, double b, double c, - double *p, double *q, double *r) { +void CoeffsForCubicZeros( + double a, double b, double c, double* p, double* q, double* r) { *p = -(c + b + a); *q = (a * b + (b + a) * c); *r = -a * b * c; @@ -45,35 +45,45 @@ TEST(Poly, SolveCubicPolynomial) { double a, b, c, aa, bb, cc; double p, q, r; - a = 1; b = 2; c = 3; + a = 1; + b = 2; + c = 3; CoeffsForCubicZeros(a, b, c, &p, &q, &r); ASSERT_EQ(3, SolveCubicPolynomial(p, q, r, &aa, &bb, &cc)); EXPECT_NEAR(a, aa, 1e-10); EXPECT_NEAR(b, bb, 1e-10); EXPECT_NEAR(c, cc, 1e-10); - a = 0; b = 1; c = 3; + a = 0; + b = 1; + c = 3; CoeffsForCubicZeros(a, b, c, &p, &q, &r); ASSERT_EQ(3, SolveCubicPolynomial(p, q, r, &aa, &bb, &cc)); EXPECT_NEAR(a, aa, 1e-10); EXPECT_NEAR(b, bb, 1e-10); EXPECT_NEAR(c, cc, 1e-10); - a = -10; b = 0; c = 1; + a = -10; + b = 0; + c = 1; CoeffsForCubicZeros(a, b, c, &p, &q, &r); ASSERT_EQ(3, SolveCubicPolynomial(p, q, r, &aa, &bb, &cc)); EXPECT_NEAR(a, aa, 1e-10); EXPECT_NEAR(b, bb, 1e-10); EXPECT_NEAR(c, cc, 1e-10); - a = -8; b = 1; c = 3; + a = -8; + b = 1; + c = 3; CoeffsForCubicZeros(a, b, c, &p, &q, &r); ASSERT_EQ(3, SolveCubicPolynomial(p, q, r, &aa, &bb, &cc)); EXPECT_NEAR(a, aa, 1e-10); EXPECT_NEAR(b, bb, 1e-10); EXPECT_NEAR(c, cc, 1e-10); - a = 28; b = 28; c = 105; + a = 28; + b = 28; + c = 105; CoeffsForCubicZeros(a, b, c, &p, &q, &r); ASSERT_EQ(3, SolveCubicPolynomial(p, q, r, &aa, &bb, &cc)); EXPECT_NEAR(a, aa, 1e-10); diff --git a/intern/libmv/libmv/simple_pipeline/bundle.cc b/intern/libmv/libmv/simple_pipeline/bundle.cc index 25a63c87e1b..e86c3bca57f 100644 --- a/intern/libmv/libmv/simple_pipeline/bundle.cc +++ b/intern/libmv/libmv/simple_pipeline/bundle.cc @@ -32,16 +32,16 @@ #include "libmv/multiview/projection.h" #include "libmv/numeric/numeric.h" #include "libmv/simple_pipeline/camera_intrinsics.h" -#include "libmv/simple_pipeline/reconstruction.h" -#include "libmv/simple_pipeline/tracks.h" #include "libmv/simple_pipeline/distortion_models.h" #include "libmv/simple_pipeline/packed_intrinsics.h" +#include "libmv/simple_pipeline/reconstruction.h" +#include "libmv/simple_pipeline/tracks.h" namespace libmv { namespace { -bool NeedUseInvertIntrinsicsPipeline(const CameraIntrinsics *intrinsics) { +bool NeedUseInvertIntrinsicsPipeline(const CameraIntrinsics* intrinsics) { const DistortionModelType distortion_model = intrinsics->GetDistortionModelType(); return (distortion_model == DISTORTION_MODEL_NUKE); @@ -59,12 +59,14 @@ bool NeedUseInvertIntrinsicsPipeline(const CameraIntrinsics *intrinsics) { // The invariant_intrinsics are used to access intrinsics which are never // packed into parameter block: for example, distortion model type and image // dimension. -template<typename T> +template <typename T> void ApplyDistortionModelUsingIntrinsicsBlock( - const CameraIntrinsics *invariant_intrinsics, + const CameraIntrinsics* invariant_intrinsics, const T* const intrinsics_block, - const T& normalized_x, const T& normalized_y, - T* distorted_x, T* distorted_y) { + const T& normalized_x, + const T& normalized_y, + T* distorted_x, + T* distorted_y) { // Unpack the intrinsics. const T& focal_length = intrinsics_block[PackedIntrinsics::OFFSET_FOCAL_LENGTH]; @@ -76,65 +78,75 @@ void ApplyDistortionModelUsingIntrinsicsBlock( // TODO(keir): Do early bailouts for zero distortion; these are expensive // jet operations. switch (invariant_intrinsics->GetDistortionModelType()) { - case DISTORTION_MODEL_POLYNOMIAL: - { - const T& k1 = intrinsics_block[PackedIntrinsics::OFFSET_K1]; - const T& k2 = intrinsics_block[PackedIntrinsics::OFFSET_K2]; - const T& k3 = intrinsics_block[PackedIntrinsics::OFFSET_K3]; - const T& p1 = intrinsics_block[PackedIntrinsics::OFFSET_P1]; - const T& p2 = intrinsics_block[PackedIntrinsics::OFFSET_P2]; - - ApplyPolynomialDistortionModel(focal_length, - focal_length, - principal_point_x, - principal_point_y, - k1, k2, k3, - p1, p2, - normalized_x, normalized_y, - distorted_x, distorted_y); - return; - } - - case DISTORTION_MODEL_DIVISION: - { - const T& k1 = intrinsics_block[PackedIntrinsics::OFFSET_K1]; - const T& k2 = intrinsics_block[PackedIntrinsics::OFFSET_K2]; - - ApplyDivisionDistortionModel(focal_length, + case DISTORTION_MODEL_POLYNOMIAL: { + const T& k1 = intrinsics_block[PackedIntrinsics::OFFSET_K1]; + const T& k2 = intrinsics_block[PackedIntrinsics::OFFSET_K2]; + const T& k3 = intrinsics_block[PackedIntrinsics::OFFSET_K3]; + const T& p1 = intrinsics_block[PackedIntrinsics::OFFSET_P1]; + const T& p2 = intrinsics_block[PackedIntrinsics::OFFSET_P2]; + + ApplyPolynomialDistortionModel(focal_length, focal_length, principal_point_x, principal_point_y, - k1, k2, - normalized_x, normalized_y, - distorted_x, distorted_y); - return; - } + k1, + k2, + k3, + p1, + p2, + normalized_x, + normalized_y, + distorted_x, + distorted_y); + return; + } - case DISTORTION_MODEL_NUKE: - { - LOG(FATAL) << "Unsupported distortion model."; - return; - } + case DISTORTION_MODEL_DIVISION: { + const T& k1 = intrinsics_block[PackedIntrinsics::OFFSET_K1]; + const T& k2 = intrinsics_block[PackedIntrinsics::OFFSET_K2]; + + ApplyDivisionDistortionModel(focal_length, + focal_length, + principal_point_x, + principal_point_y, + k1, + k2, + normalized_x, + normalized_y, + distorted_x, + distorted_y); + return; + } - case DISTORTION_MODEL_BROWN: - { - const T& k1 = intrinsics_block[PackedIntrinsics::OFFSET_K1]; - const T& k2 = intrinsics_block[PackedIntrinsics::OFFSET_K2]; - const T& k3 = intrinsics_block[PackedIntrinsics::OFFSET_K3]; - const T& k4 = intrinsics_block[PackedIntrinsics::OFFSET_K4]; - const T& p1 = intrinsics_block[PackedIntrinsics::OFFSET_P1]; - const T& p2 = intrinsics_block[PackedIntrinsics::OFFSET_P2]; - - ApplyBrownDistortionModel(focal_length, - focal_length, - principal_point_x, - principal_point_y, - k1, k2, k3, k4, - p1, p2, - normalized_x, normalized_y, - distorted_x, distorted_y); - return; - } + case DISTORTION_MODEL_NUKE: { + LOG(FATAL) << "Unsupported distortion model."; + return; + } + + case DISTORTION_MODEL_BROWN: { + const T& k1 = intrinsics_block[PackedIntrinsics::OFFSET_K1]; + const T& k2 = intrinsics_block[PackedIntrinsics::OFFSET_K2]; + const T& k3 = intrinsics_block[PackedIntrinsics::OFFSET_K3]; + const T& k4 = intrinsics_block[PackedIntrinsics::OFFSET_K4]; + const T& p1 = intrinsics_block[PackedIntrinsics::OFFSET_P1]; + const T& p2 = intrinsics_block[PackedIntrinsics::OFFSET_P2]; + + ApplyBrownDistortionModel(focal_length, + focal_length, + principal_point_x, + principal_point_y, + k1, + k2, + k3, + k4, + p1, + p2, + normalized_x, + normalized_y, + distorted_x, + distorted_y); + return; + } } LOG(FATAL) << "Unknown distortion model."; @@ -152,12 +164,14 @@ void ApplyDistortionModelUsingIntrinsicsBlock( // The invariant_intrinsics are used to access intrinsics which are never // packed into parameter block: for example, distortion model type and image // dimension. -template<typename T> +template <typename T> void InvertDistortionModelUsingIntrinsicsBlock( - const CameraIntrinsics *invariant_intrinsics, + const CameraIntrinsics* invariant_intrinsics, const T* const intrinsics_block, - const T& image_x, const T& image_y, - T* normalized_x, T* normalized_y) { + const T& image_x, + const T& image_y, + T* normalized_x, + T* normalized_y) { // Unpack the intrinsics. const T& focal_length = intrinsics_block[PackedIntrinsics::OFFSET_FOCAL_LENGTH]; @@ -175,31 +189,35 @@ void InvertDistortionModelUsingIntrinsicsBlock( LOG(FATAL) << "Unsupported distortion model."; return; - case DISTORTION_MODEL_NUKE: - { - const T& k1 = intrinsics_block[PackedIntrinsics::OFFSET_K1]; - const T& k2 = intrinsics_block[PackedIntrinsics::OFFSET_K2]; - - InvertNukeDistortionModel(focal_length, - focal_length, - principal_point_x, - principal_point_y, - invariant_intrinsics->image_width(), - invariant_intrinsics->image_height(), - k1, k2, - image_x, image_y, - normalized_x, normalized_y); - return; - } + case DISTORTION_MODEL_NUKE: { + const T& k1 = intrinsics_block[PackedIntrinsics::OFFSET_K1]; + const T& k2 = intrinsics_block[PackedIntrinsics::OFFSET_K2]; + + InvertNukeDistortionModel(focal_length, + focal_length, + principal_point_x, + principal_point_y, + invariant_intrinsics->image_width(), + invariant_intrinsics->image_height(), + k1, + k2, + image_x, + image_y, + normalized_x, + normalized_y); + return; + } } LOG(FATAL) << "Unknown distortion model."; } -template<typename T> +template <typename T> void NormalizedToImageSpace(const T* const intrinsics_block, - const T& normalized_x, const T& normalized_y, - T* image_x, T* image_y) { + const T& normalized_x, + const T& normalized_y, + T* image_x, + T* image_y) { // Unpack the intrinsics. const T& focal_length = intrinsics_block[PackedIntrinsics::OFFSET_FOCAL_LENGTH]; @@ -219,11 +237,10 @@ void NormalizedToImageSpace(const T* const intrinsics_block, // This functor can only be used for distortion models which have analytically // defined Apply() function. struct ReprojectionErrorApplyIntrinsics { - ReprojectionErrorApplyIntrinsics( - const CameraIntrinsics *invariant_intrinsics, - const double observed_distorted_x, - const double observed_distorted_y, - const double weight) + ReprojectionErrorApplyIntrinsics(const CameraIntrinsics* invariant_intrinsics, + const double observed_distorted_x, + const double observed_distorted_y, + const double weight) : invariant_intrinsics_(invariant_intrinsics), observed_distorted_x_(observed_distorted_x), observed_distorted_y_(observed_distorted_y), @@ -253,11 +270,12 @@ struct ReprojectionErrorApplyIntrinsics { T yn = x[1] / x[2]; T predicted_distorted_x, predicted_distorted_y; - ApplyDistortionModelUsingIntrinsicsBlock( - invariant_intrinsics_, - intrinsics, - xn, yn, - &predicted_distorted_x, &predicted_distorted_y); + ApplyDistortionModelUsingIntrinsicsBlock(invariant_intrinsics_, + intrinsics, + xn, + yn, + &predicted_distorted_x, + &predicted_distorted_y); // The error is the difference between the predicted and observed position. residuals[0] = (predicted_distorted_x - T(observed_distorted_x_)) * weight_; @@ -265,7 +283,7 @@ struct ReprojectionErrorApplyIntrinsics { return true; } - const CameraIntrinsics *invariant_intrinsics_; + const CameraIntrinsics* invariant_intrinsics_; const double observed_distorted_x_; const double observed_distorted_y_; const double weight_; @@ -279,7 +297,7 @@ struct ReprojectionErrorApplyIntrinsics { // defined Invert() function. struct ReprojectionErrorInvertIntrinsics { ReprojectionErrorInvertIntrinsics( - const CameraIntrinsics *invariant_intrinsics, + const CameraIntrinsics* invariant_intrinsics, const double observed_distorted_x, const double observed_distorted_y, const double weight) @@ -295,8 +313,7 @@ struct ReprojectionErrorInvertIntrinsics { const T* const X, // Point coordinates 3x1. T* residuals) const { // Unpack the intrinsics. - const T& focal_length = - intrinsics[PackedIntrinsics::OFFSET_FOCAL_LENGTH]; + const T& focal_length = intrinsics[PackedIntrinsics::OFFSET_FOCAL_LENGTH]; const T& principal_point_x = intrinsics[PackedIntrinsics::OFFSET_PRINCIPAL_POINT_X]; const T& principal_point_y = @@ -327,14 +344,17 @@ struct ReprojectionErrorInvertIntrinsics { InvertDistortionModelUsingIntrinsicsBlock( invariant_intrinsics_, intrinsics, - T(observed_distorted_x_), T(observed_distorted_y_), - &observed_undistorted_normalized_x, &observed_undistorted_normalized_y); + T(observed_distorted_x_), + T(observed_distorted_y_), + &observed_undistorted_normalized_x, + &observed_undistorted_normalized_y); T observed_undistorted_image_x, observed_undistorted_image_y; - NormalizedToImageSpace( - intrinsics, - observed_undistorted_normalized_x, observed_undistorted_normalized_y, - &observed_undistorted_image_x, &observed_undistorted_image_y); + NormalizedToImageSpace(intrinsics, + observed_undistorted_normalized_x, + observed_undistorted_normalized_y, + &observed_undistorted_image_x, + &observed_undistorted_image_y); // The error is the difference between the predicted and observed position. residuals[0] = (predicted_x - observed_undistorted_image_x) * weight_; @@ -343,7 +363,7 @@ struct ReprojectionErrorInvertIntrinsics { return true; } - const CameraIntrinsics *invariant_intrinsics_; + const CameraIntrinsics* invariant_intrinsics_; const double observed_distorted_x_; const double observed_distorted_y_; const double weight_; @@ -356,22 +376,23 @@ void BundleIntrinsicsLogMessage(const int bundle_intrinsics) { } else { std::string bundling_message = ""; -#define APPEND_BUNDLING_INTRINSICS(name, flag) \ - if (bundle_intrinsics & flag) { \ - if (!bundling_message.empty()) { \ - bundling_message += ", "; \ - } \ - bundling_message += name; \ - } (void)0 +#define APPEND_BUNDLING_INTRINSICS(name, flag) \ + if (bundle_intrinsics & flag) { \ + if (!bundling_message.empty()) { \ + bundling_message += ", "; \ + } \ + bundling_message += name; \ + } \ + (void)0 - APPEND_BUNDLING_INTRINSICS("f", BUNDLE_FOCAL_LENGTH); + APPEND_BUNDLING_INTRINSICS("f", BUNDLE_FOCAL_LENGTH); APPEND_BUNDLING_INTRINSICS("px, py", BUNDLE_PRINCIPAL_POINT); - APPEND_BUNDLING_INTRINSICS("k1", BUNDLE_RADIAL_K1); - APPEND_BUNDLING_INTRINSICS("k2", BUNDLE_RADIAL_K2); - APPEND_BUNDLING_INTRINSICS("k3", BUNDLE_RADIAL_K3); - APPEND_BUNDLING_INTRINSICS("k4", BUNDLE_RADIAL_K4); - APPEND_BUNDLING_INTRINSICS("p1", BUNDLE_TANGENTIAL_P1); - APPEND_BUNDLING_INTRINSICS("p2", BUNDLE_TANGENTIAL_P2); + APPEND_BUNDLING_INTRINSICS("k1", BUNDLE_RADIAL_K1); + APPEND_BUNDLING_INTRINSICS("k2", BUNDLE_RADIAL_K2); + APPEND_BUNDLING_INTRINSICS("k3", BUNDLE_RADIAL_K3); + APPEND_BUNDLING_INTRINSICS("k4", BUNDLE_RADIAL_K4); + APPEND_BUNDLING_INTRINSICS("p1", BUNDLE_TANGENTIAL_P1); + APPEND_BUNDLING_INTRINSICS("p2", BUNDLE_TANGENTIAL_P2); LG << "Bundling " << bundling_message << "."; } @@ -383,7 +404,7 @@ void BundleIntrinsicsLogMessage(const int bundle_intrinsics) { // Element with key i matches to a rotation+translation for // camera at image i. map<int, Vec6> PackCamerasRotationAndTranslation( - const EuclideanReconstruction &reconstruction) { + const EuclideanReconstruction& reconstruction) { map<int, Vec6> all_cameras_R_t; vector<EuclideanCamera> all_cameras = reconstruction.AllCameras(); @@ -399,14 +420,13 @@ map<int, Vec6> PackCamerasRotationAndTranslation( // Convert cameras rotations fro mangle axis back to rotation matrix. void UnpackCamerasRotationAndTranslation( - const map<int, Vec6> &all_cameras_R_t, - EuclideanReconstruction *reconstruction) { - + const map<int, Vec6>& all_cameras_R_t, + EuclideanReconstruction* reconstruction) { for (map<int, Vec6>::value_type image_and_camera_R_T : all_cameras_R_t) { const int image = image_and_camera_R_T.first; const Vec6& camera_R_t = image_and_camera_R_T.second; - EuclideanCamera *camera = reconstruction->CameraForImage(image); + EuclideanCamera* camera = reconstruction->CameraForImage(image); if (!camera) { continue; } @@ -421,8 +441,8 @@ void UnpackCamerasRotationAndTranslation( // // TODO(sergey): currently uses dense Eigen matrices, best would // be to use sparse Eigen matrices -void CRSMatrixToEigenMatrix(const ceres::CRSMatrix &crs_matrix, - Mat *eigen_matrix) { +void CRSMatrixToEigenMatrix(const ceres::CRSMatrix& crs_matrix, + Mat* eigen_matrix) { eigen_matrix->resize(crs_matrix.num_rows, crs_matrix.num_cols); eigen_matrix->setZero(); @@ -439,11 +459,11 @@ void CRSMatrixToEigenMatrix(const ceres::CRSMatrix &crs_matrix, } } -void EuclideanBundlerPerformEvaluation(const Tracks &tracks, - EuclideanReconstruction *reconstruction, - map<int, Vec6> *all_cameras_R_t, - ceres::Problem *problem, - BundleEvaluation *evaluation) { +void EuclideanBundlerPerformEvaluation(const Tracks& tracks, + EuclideanReconstruction* reconstruction, + map<int, Vec6>* all_cameras_R_t, + ceres::Problem* problem, + BundleEvaluation* evaluation) { int max_track = tracks.MaxTrack(); // Number of camera rotations equals to number of translation, int num_cameras = all_cameras_R_t->size(); @@ -451,7 +471,7 @@ void EuclideanBundlerPerformEvaluation(const Tracks &tracks, vector<EuclideanPoint*> minimized_points; for (int i = 0; i <= max_track; i++) { - EuclideanPoint *point = reconstruction->PointForTrack(i); + EuclideanPoint* point = reconstruction->PointForTrack(i); if (point) { // We need to know whether the track is a constant zero weight. // If it is so it wouldn't have a parameter block in the problem. @@ -477,16 +497,16 @@ void EuclideanBundlerPerformEvaluation(const Tracks &tracks, evaluation->num_cameras = num_cameras; evaluation->num_points = num_points; - if (evaluation->evaluate_jacobian) { // Evaluate jacobian matrix. + if (evaluation->evaluate_jacobian) { // Evaluate jacobian matrix. ceres::CRSMatrix evaluated_jacobian; ceres::Problem::EvaluateOptions eval_options; // Cameras goes first in the ordering. int max_image = tracks.MaxImage(); for (int i = 0; i <= max_image; i++) { - const EuclideanCamera *camera = reconstruction->CameraForImage(i); + const EuclideanCamera* camera = reconstruction->CameraForImage(i); if (camera) { - double *current_camera_R_t = &(*all_cameras_R_t)[i](0); + double* current_camera_R_t = &(*all_cameras_R_t)[i](0); // All cameras are variable now. problem->SetParameterBlockVariable(current_camera_R_t); @@ -497,63 +517,65 @@ void EuclideanBundlerPerformEvaluation(const Tracks &tracks, // Points goes at the end of ordering, for (int i = 0; i < minimized_points.size(); i++) { - EuclideanPoint *point = minimized_points.at(i); + EuclideanPoint* point = minimized_points.at(i); eval_options.parameter_blocks.push_back(&point->X(0)); } - problem->Evaluate(eval_options, - NULL, NULL, NULL, - &evaluated_jacobian); + problem->Evaluate(eval_options, NULL, NULL, NULL, &evaluated_jacobian); CRSMatrixToEigenMatrix(evaluated_jacobian, &evaluation->jacobian); } } -template<typename CostFunction> -void AddResidualBlockToProblemImpl(const CameraIntrinsics *invariant_intrinsics, - double observed_x, double observed_y, +template <typename CostFunction> +void AddResidualBlockToProblemImpl(const CameraIntrinsics* invariant_intrinsics, + double observed_x, + double observed_y, double weight, - double *intrinsics_block, - double *camera_R_t, - EuclideanPoint *point, + double* intrinsics_block, + double* camera_R_t, + EuclideanPoint* point, ceres::Problem* problem) { - problem->AddResidualBlock(new ceres::AutoDiffCostFunction< - CostFunction, 2, PackedIntrinsics::NUM_PARAMETERS, 6, 3>( - new CostFunction( - invariant_intrinsics, - observed_x, observed_y, - weight)), + problem->AddResidualBlock( + new ceres::AutoDiffCostFunction<CostFunction, + 2, + PackedIntrinsics::NUM_PARAMETERS, + 6, + 3>(new CostFunction( + invariant_intrinsics, observed_x, observed_y, weight)), NULL, intrinsics_block, camera_R_t, &point->X(0)); } -void AddResidualBlockToProblem(const CameraIntrinsics *invariant_intrinsics, - const Marker &marker, +void AddResidualBlockToProblem(const CameraIntrinsics* invariant_intrinsics, + const Marker& marker, double marker_weight, double* intrinsics_block, - double *camera_R_t, - EuclideanPoint *point, + double* camera_R_t, + EuclideanPoint* point, ceres::Problem* problem) { if (NeedUseInvertIntrinsicsPipeline(invariant_intrinsics)) { AddResidualBlockToProblemImpl<ReprojectionErrorInvertIntrinsics>( - invariant_intrinsics, - marker.x, marker.y, - marker_weight, - intrinsics_block, - camera_R_t, - point, - problem); + invariant_intrinsics, + marker.x, + marker.y, + marker_weight, + intrinsics_block, + camera_R_t, + point, + problem); } else { AddResidualBlockToProblemImpl<ReprojectionErrorApplyIntrinsics>( - invariant_intrinsics, - marker.x, marker.y, - marker_weight, - intrinsics_block, - camera_R_t, - point, - problem); + invariant_intrinsics, + marker.x, + marker.y, + marker_weight, + intrinsics_block, + camera_R_t, + point, + problem); } } @@ -566,25 +588,25 @@ void AddResidualBlockToProblem(const CameraIntrinsics *invariant_intrinsics, // // At this point we only need to bundle points positions, cameras // are to be totally still here. -void EuclideanBundlePointsOnly(const CameraIntrinsics *invariant_intrinsics, - const vector<Marker> &markers, - map<int, Vec6> &all_cameras_R_t, +void EuclideanBundlePointsOnly(const CameraIntrinsics* invariant_intrinsics, + const vector<Marker>& markers, + map<int, Vec6>& all_cameras_R_t, double* intrinsics_block, - EuclideanReconstruction *reconstruction) { + EuclideanReconstruction* reconstruction) { ceres::Problem::Options problem_options; ceres::Problem problem(problem_options); int num_residuals = 0; for (int i = 0; i < markers.size(); ++i) { - const Marker &marker = markers[i]; - EuclideanCamera *camera = reconstruction->CameraForImage(marker.image); - EuclideanPoint *point = reconstruction->PointForTrack(marker.track); + const Marker& marker = markers[i]; + EuclideanCamera* camera = reconstruction->CameraForImage(marker.image); + EuclideanPoint* point = reconstruction->PointForTrack(marker.track); if (camera == NULL || point == NULL) { continue; } // Rotation of camera denoted in angle axis followed with // camera translation. - double *current_camera_R_t = &all_cameras_R_t[camera->image](0); + double* current_camera_R_t = &all_cameras_R_t[camera->image](0); AddResidualBlockToProblem(invariant_intrinsics, marker, @@ -625,8 +647,8 @@ void EuclideanBundlePointsOnly(const CameraIntrinsics *invariant_intrinsics, } // namespace -void EuclideanBundle(const Tracks &tracks, - EuclideanReconstruction *reconstruction) { +void EuclideanBundle(const Tracks& tracks, + EuclideanReconstruction* reconstruction) { PolynomialCameraIntrinsics empty_intrinsics; EuclideanBundleCommonIntrinsics(tracks, BUNDLE_NO_INTRINSICS, @@ -636,13 +658,12 @@ void EuclideanBundle(const Tracks &tracks, NULL); } -void EuclideanBundleCommonIntrinsics( - const Tracks &tracks, - const int bundle_intrinsics, - const int bundle_constraints, - EuclideanReconstruction *reconstruction, - CameraIntrinsics *intrinsics, - BundleEvaluation *evaluation) { +void EuclideanBundleCommonIntrinsics(const Tracks& tracks, + const int bundle_intrinsics, + const int bundle_constraints, + EuclideanReconstruction* reconstruction, + CameraIntrinsics* intrinsics, + BundleEvaluation* evaluation) { LG << "Original intrinsics: " << *intrinsics; vector<Marker> markers = tracks.AllMarkers(); @@ -661,19 +682,19 @@ void EuclideanBundleCommonIntrinsics( // Block for minimization has got the following structure: // <3 elements for angle-axis> <3 elements for translation> map<int, Vec6> all_cameras_R_t = - PackCamerasRotationAndTranslation(*reconstruction); + PackCamerasRotationAndTranslation(*reconstruction); // Parameterization used to restrict camera motion for modal solvers. - ceres::SubsetParameterization *constant_translation_parameterization = NULL; + ceres::SubsetParameterization* constant_translation_parameterization = NULL; if (bundle_constraints & BUNDLE_NO_TRANSLATION) { - std::vector<int> constant_translation; + std::vector<int> constant_translation; - // First three elements are rotation, ast three are translation. - constant_translation.push_back(3); - constant_translation.push_back(4); - constant_translation.push_back(5); + // First three elements are rotation, ast three are translation. + constant_translation.push_back(3); + constant_translation.push_back(4); + constant_translation.push_back(5); - constant_translation_parameterization = + constant_translation_parameterization = new ceres::SubsetParameterization(6, constant_translation); } @@ -683,16 +704,16 @@ void EuclideanBundleCommonIntrinsics( int num_residuals = 0; bool have_locked_camera = false; for (int i = 0; i < markers.size(); ++i) { - const Marker &marker = markers[i]; - EuclideanCamera *camera = reconstruction->CameraForImage(marker.image); - EuclideanPoint *point = reconstruction->PointForTrack(marker.track); + const Marker& marker = markers[i]; + EuclideanCamera* camera = reconstruction->CameraForImage(marker.image); + EuclideanPoint* point = reconstruction->PointForTrack(marker.track); if (camera == NULL || point == NULL) { continue; } // Rotation of camera denoted in angle axis followed with // camera translation. - double *current_camera_R_t = &all_cameras_R_t[camera->image](0); + double* current_camera_R_t = &all_cameras_R_t[camera->image](0); // Skip residual block for markers which does have absolutely // no affect on the final solution. @@ -706,7 +727,8 @@ void EuclideanBundleCommonIntrinsics( point, &problem); - // We lock the first camera to better deal with scene orientation ambiguity. + // We lock the first camera to better deal with scene orientation + // ambiguity. if (!have_locked_camera) { problem.SetParameterBlockConstant(current_camera_R_t); have_locked_camera = true; @@ -729,7 +751,7 @@ void EuclideanBundleCommonIntrinsics( } if (intrinsics->GetDistortionModelType() == DISTORTION_MODEL_DIVISION && - (bundle_intrinsics & BUNDLE_TANGENTIAL) != 0) { + (bundle_intrinsics & BUNDLE_TANGENTIAL) != 0) { LOG(FATAL) << "Division model doesn't support bundling " "of tangential distortion"; } @@ -745,29 +767,29 @@ void EuclideanBundleCommonIntrinsics( // constant using some macro trickery. std::vector<int> constant_intrinsics; -#define MAYBE_SET_CONSTANT(bundle_enum, offset) \ - if (!(bundle_intrinsics & bundle_enum) || \ - !packed_intrinsics.IsParameterDefined(offset)) { \ - constant_intrinsics.push_back(offset); \ - } +#define MAYBE_SET_CONSTANT(bundle_enum, offset) \ + if (!(bundle_intrinsics & bundle_enum) || \ + !packed_intrinsics.IsParameterDefined(offset)) { \ + constant_intrinsics.push_back(offset); \ + } MAYBE_SET_CONSTANT(BUNDLE_FOCAL_LENGTH, PackedIntrinsics::OFFSET_FOCAL_LENGTH); MAYBE_SET_CONSTANT(BUNDLE_PRINCIPAL_POINT, PackedIntrinsics::OFFSET_PRINCIPAL_POINT_X); MAYBE_SET_CONSTANT(BUNDLE_PRINCIPAL_POINT, PackedIntrinsics::OFFSET_PRINCIPAL_POINT_Y); - MAYBE_SET_CONSTANT(BUNDLE_RADIAL_K1, PackedIntrinsics::OFFSET_K1); - MAYBE_SET_CONSTANT(BUNDLE_RADIAL_K2, PackedIntrinsics::OFFSET_K2); - MAYBE_SET_CONSTANT(BUNDLE_RADIAL_K3, PackedIntrinsics::OFFSET_K3); - MAYBE_SET_CONSTANT(BUNDLE_RADIAL_K4, PackedIntrinsics::OFFSET_K4); - MAYBE_SET_CONSTANT(BUNDLE_TANGENTIAL_P1, PackedIntrinsics::OFFSET_P1); - MAYBE_SET_CONSTANT(BUNDLE_TANGENTIAL_P2, PackedIntrinsics::OFFSET_P2); + MAYBE_SET_CONSTANT(BUNDLE_RADIAL_K1, PackedIntrinsics::OFFSET_K1); + MAYBE_SET_CONSTANT(BUNDLE_RADIAL_K2, PackedIntrinsics::OFFSET_K2); + MAYBE_SET_CONSTANT(BUNDLE_RADIAL_K3, PackedIntrinsics::OFFSET_K3); + MAYBE_SET_CONSTANT(BUNDLE_RADIAL_K4, PackedIntrinsics::OFFSET_K4); + MAYBE_SET_CONSTANT(BUNDLE_TANGENTIAL_P1, PackedIntrinsics::OFFSET_P1); + MAYBE_SET_CONSTANT(BUNDLE_TANGENTIAL_P2, PackedIntrinsics::OFFSET_P2); #undef MAYBE_SET_CONSTANT if (!constant_intrinsics.empty()) { - ceres::SubsetParameterization *subset_parameterization = - new ceres::SubsetParameterization(PackedIntrinsics::NUM_PARAMETERS, - constant_intrinsics); + ceres::SubsetParameterization* subset_parameterization = + new ceres::SubsetParameterization(PackedIntrinsics::NUM_PARAMETERS, + constant_intrinsics); problem.SetParameterization(intrinsics_block, subset_parameterization); } @@ -800,8 +822,8 @@ void EuclideanBundleCommonIntrinsics( LG << "Final intrinsics: " << *intrinsics; if (evaluation) { - EuclideanBundlerPerformEvaluation(tracks, reconstruction, &all_cameras_R_t, - &problem, evaluation); + EuclideanBundlerPerformEvaluation( + tracks, reconstruction, &all_cameras_R_t, &problem, evaluation); } // Separate step to adjust positions of tracks which are @@ -828,8 +850,8 @@ void EuclideanBundleCommonIntrinsics( } } -void ProjectiveBundle(const Tracks & /*tracks*/, - ProjectiveReconstruction * /*reconstruction*/) { +void ProjectiveBundle(const Tracks& /*tracks*/, + ProjectiveReconstruction* /*reconstruction*/) { // TODO(keir): Implement this! This can't work until we have a better bundler // than SSBA, since SSBA has no support for projective bundling. } diff --git a/intern/libmv/libmv/simple_pipeline/bundle.h b/intern/libmv/libmv/simple_pipeline/bundle.h index 5f420da0045..662313b396a 100644 --- a/intern/libmv/libmv/simple_pipeline/bundle.h +++ b/intern/libmv/libmv/simple_pipeline/bundle.h @@ -31,11 +31,8 @@ class ProjectiveReconstruction; class Tracks; struct BundleEvaluation { - BundleEvaluation() : - num_cameras(0), - num_points(0), - evaluate_jacobian(false) { - } + BundleEvaluation() + : num_cameras(0), num_points(0), evaluate_jacobian(false) {} // Number of cameras appeared in bundle adjustment problem int num_cameras; @@ -72,8 +69,8 @@ struct BundleEvaluation { \sa EuclideanResect, EuclideanIntersect, EuclideanReconstructTwoFrames */ -void EuclideanBundle(const Tracks &tracks, - EuclideanReconstruction *reconstruction); +void EuclideanBundle(const Tracks& tracks, + EuclideanReconstruction* reconstruction); /*! Refine camera poses and 3D coordinates using bundle adjustment. @@ -109,9 +106,7 @@ enum BundleIntrinsics { BUNDLE_RADIAL_K2 = (1 << 3), BUNDLE_RADIAL_K3 = (1 << 4), BUNDLE_RADIAL_K4 = (1 << 5), - BUNDLE_RADIAL = (BUNDLE_RADIAL_K1 | - BUNDLE_RADIAL_K2 | - BUNDLE_RADIAL_K3 | + BUNDLE_RADIAL = (BUNDLE_RADIAL_K1 | BUNDLE_RADIAL_K2 | BUNDLE_RADIAL_K3 | BUNDLE_RADIAL_K4), BUNDLE_TANGENTIAL_P1 = (1 << 6), @@ -122,13 +117,12 @@ enum BundleConstraints { BUNDLE_NO_CONSTRAINTS = 0, BUNDLE_NO_TRANSLATION = 1, }; -void EuclideanBundleCommonIntrinsics( - const Tracks &tracks, - const int bundle_intrinsics, - const int bundle_constraints, - EuclideanReconstruction *reconstruction, - CameraIntrinsics *intrinsics, - BundleEvaluation *evaluation = NULL); +void EuclideanBundleCommonIntrinsics(const Tracks& tracks, + const int bundle_intrinsics, + const int bundle_constraints, + EuclideanReconstruction* reconstruction, + CameraIntrinsics* intrinsics, + BundleEvaluation* evaluation = NULL); /*! Refine camera poses and 3D coordinates using bundle adjustment. @@ -147,10 +141,9 @@ void EuclideanBundleCommonIntrinsics( \sa ProjectiveResect, ProjectiveIntersect, ProjectiveReconstructTwoFrames */ -void ProjectiveBundle(const Tracks &tracks, - ProjectiveReconstruction *reconstruction); +void ProjectiveBundle(const Tracks& tracks, + ProjectiveReconstruction* reconstruction); } // namespace libmv -#endif // LIBMV_SIMPLE_PIPELINE_BUNDLE_H - +#endif // LIBMV_SIMPLE_PIPELINE_BUNDLE_H diff --git a/intern/libmv/libmv/simple_pipeline/callbacks.h b/intern/libmv/libmv/simple_pipeline/callbacks.h index 58f7b0d3cc9..a6855a9e5e7 100644 --- a/intern/libmv/libmv/simple_pipeline/callbacks.h +++ b/intern/libmv/libmv/simple_pipeline/callbacks.h @@ -26,7 +26,7 @@ namespace libmv { class ProgressUpdateCallback { public: virtual ~ProgressUpdateCallback() {} - virtual void invoke(double progress, const char *message) = 0; + virtual void invoke(double progress, const char* message) = 0; }; } // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/camera_intrinsics.cc b/intern/libmv/libmv/simple_pipeline/camera_intrinsics.cc index ccb6e3d34c8..b86e316b139 100644 --- a/intern/libmv/libmv/simple_pipeline/camera_intrinsics.cc +++ b/intern/libmv/libmv/simple_pipeline/camera_intrinsics.cc @@ -29,13 +29,10 @@ namespace libmv { namespace internal { LookupWarpGrid::LookupWarpGrid() - : offset_(NULL), - width_(0), - height_(0), - overscan_(0.0), - threads_(1) {} + : offset_(NULL), width_(0), height_(0), overscan_(0.0), threads_(1) { +} -LookupWarpGrid::LookupWarpGrid(const LookupWarpGrid &from) +LookupWarpGrid::LookupWarpGrid(const LookupWarpGrid& from) : offset_(NULL), width_(from.width_), height_(from.height_), @@ -48,11 +45,11 @@ LookupWarpGrid::LookupWarpGrid(const LookupWarpGrid &from) } LookupWarpGrid::~LookupWarpGrid() { - delete [] offset_; + delete[] offset_; } void LookupWarpGrid::Reset() { - delete [] offset_; + delete[] offset_; offset_ = NULL; } @@ -64,16 +61,16 @@ void LookupWarpGrid::SetThreads(int threads) { } // namespace internal CameraIntrinsics::CameraIntrinsics() - : image_width_(0), - image_height_(0), - K_(Mat3::Identity()) {} + : image_width_(0), image_height_(0), K_(Mat3::Identity()) { +} -CameraIntrinsics::CameraIntrinsics(const CameraIntrinsics &from) +CameraIntrinsics::CameraIntrinsics(const CameraIntrinsics& from) : image_width_(from.image_width_), image_height_(from.image_height_), K_(from.K_), distort_(from.distort_), - undistort_(from.undistort_) {} + undistort_(from.undistort_) { +} // Set the image size in pixels. void CameraIntrinsics::SetImageSize(int width, int height) { @@ -89,16 +86,14 @@ void CameraIntrinsics::SetK(const Mat3 new_k) { } // Set both x and y focal length in pixels. -void CameraIntrinsics::SetFocalLength(double focal_x, - double focal_y) { +void CameraIntrinsics::SetFocalLength(double focal_x, double focal_y) { K_(0, 0) = focal_x; K_(1, 1) = focal_y; ResetLookupGrids(); } // Set principal point in pixels. -void CameraIntrinsics::SetPrincipalPoint(double cx, - double cy) { +void CameraIntrinsics::SetPrincipalPoint(double cx, double cy) { K_(0, 2) = cx; K_(1, 2) = cy; ResetLookupGrids(); @@ -112,16 +107,16 @@ void CameraIntrinsics::SetThreads(int threads) { void CameraIntrinsics::ImageSpaceToNormalized(double image_x, double image_y, - double *normalized_x, - double *normalized_y) const { + double* normalized_x, + double* normalized_y) const { *normalized_x = (image_x - principal_point_x()) / focal_length_x(); *normalized_y = (image_y - principal_point_y()) / focal_length_y(); } void CameraIntrinsics::NormalizedToImageSpace(double normalized_x, double normalized_y, - double *image_x, - double *image_y) const { + double* image_x, + double* image_y) const { *image_x = normalized_x * focal_length_x() + principal_point_x(); *image_y = normalized_y * focal_length_y() + principal_point_y(); } @@ -148,14 +143,13 @@ void CameraIntrinsics::Unpack(const PackedIntrinsics& packed_intrinsics) { // Polynomial model. -PolynomialCameraIntrinsics::PolynomialCameraIntrinsics() - : CameraIntrinsics() { +PolynomialCameraIntrinsics::PolynomialCameraIntrinsics() : CameraIntrinsics() { SetRadialDistortion(0.0, 0.0, 0.0); SetTangentialDistortion(0.0, 0.0); } PolynomialCameraIntrinsics::PolynomialCameraIntrinsics( - const PolynomialCameraIntrinsics &from) + const PolynomialCameraIntrinsics& from) : CameraIntrinsics(from) { SetRadialDistortion(from.k1(), from.k2(), from.k3()); SetTangentialDistortion(from.p1(), from.p2()); @@ -170,8 +164,7 @@ void PolynomialCameraIntrinsics::SetRadialDistortion(double k1, ResetLookupGrids(); } -void PolynomialCameraIntrinsics::SetTangentialDistortion(double p1, - double p2) { +void PolynomialCameraIntrinsics::SetTangentialDistortion(double p1, double p2) { parameters_[OFFSET_P1] = p1; parameters_[OFFSET_P2] = p2; ResetLookupGrids(); @@ -179,31 +172,36 @@ void PolynomialCameraIntrinsics::SetTangentialDistortion(double p1, void PolynomialCameraIntrinsics::ApplyIntrinsics(double normalized_x, double normalized_y, - double *image_x, - double *image_y) const { + double* image_x, + double* image_y) const { ApplyPolynomialDistortionModel(focal_length_x(), focal_length_y(), principal_point_x(), principal_point_y(), - k1(), k2(), k3(), - p1(), p2(), + k1(), + k2(), + k3(), + p1(), + p2(), normalized_x, normalized_y, image_x, image_y); } -void PolynomialCameraIntrinsics::InvertIntrinsics( - double image_x, - double image_y, - double *normalized_x, - double *normalized_y) const { +void PolynomialCameraIntrinsics::InvertIntrinsics(double image_x, + double image_y, + double* normalized_x, + double* normalized_y) const { InvertPolynomialDistortionModel(focal_length_x(), focal_length_y(), principal_point_x(), principal_point_y(), - k1(), k2(), k3(), - p1(), p2(), + k1(), + k2(), + k3(), + p1(), + p2(), image_x, image_y, normalized_x, @@ -230,25 +228,22 @@ void PolynomialCameraIntrinsics::Unpack( packed_intrinsics.GetK2(), packed_intrinsics.GetK3()); - SetTangentialDistortion(packed_intrinsics.GetP1(), - packed_intrinsics.GetP2()); + SetTangentialDistortion(packed_intrinsics.GetP1(), packed_intrinsics.GetP2()); } // Division model. -DivisionCameraIntrinsics::DivisionCameraIntrinsics() - : CameraIntrinsics() { +DivisionCameraIntrinsics::DivisionCameraIntrinsics() : CameraIntrinsics() { SetDistortion(0.0, 0.0); } DivisionCameraIntrinsics::DivisionCameraIntrinsics( - const DivisionCameraIntrinsics &from) + const DivisionCameraIntrinsics& from) : CameraIntrinsics(from) { SetDistortion(from.k1(), from.k1()); } -void DivisionCameraIntrinsics::SetDistortion(double k1, - double k2) { +void DivisionCameraIntrinsics::SetDistortion(double k1, double k2) { parameters_[OFFSET_K1] = k1; parameters_[OFFSET_K2] = k2; ResetLookupGrids(); @@ -256,13 +251,14 @@ void DivisionCameraIntrinsics::SetDistortion(double k1, void DivisionCameraIntrinsics::ApplyIntrinsics(double normalized_x, double normalized_y, - double *image_x, - double *image_y) const { + double* image_x, + double* image_y) const { ApplyDivisionDistortionModel(focal_length_x(), focal_length_y(), principal_point_x(), principal_point_y(), - k1(), k2(), + k1(), + k2(), normalized_x, normalized_y, image_x, @@ -271,21 +267,21 @@ void DivisionCameraIntrinsics::ApplyIntrinsics(double normalized_x, void DivisionCameraIntrinsics::InvertIntrinsics(double image_x, double image_y, - double *normalized_x, - double *normalized_y) const { + double* normalized_x, + double* normalized_y) const { InvertDivisionDistortionModel(focal_length_x(), focal_length_y(), principal_point_x(), principal_point_y(), - k1(), k2(), + k1(), + k2(), image_x, image_y, normalized_x, normalized_y); } -void DivisionCameraIntrinsics::Pack( - PackedIntrinsics* packed_intrinsics) const { +void DivisionCameraIntrinsics::Pack(PackedIntrinsics* packed_intrinsics) const { CameraIntrinsics::Pack(packed_intrinsics); packed_intrinsics->SetK1(k1()); @@ -301,13 +297,11 @@ void DivisionCameraIntrinsics::Unpack( // Nuke model. -NukeCameraIntrinsics::NukeCameraIntrinsics() - : CameraIntrinsics() { +NukeCameraIntrinsics::NukeCameraIntrinsics() : CameraIntrinsics() { SetDistortion(0.0, 0.0); } -NukeCameraIntrinsics::NukeCameraIntrinsics( - const NukeCameraIntrinsics &from) +NukeCameraIntrinsics::NukeCameraIntrinsics(const NukeCameraIntrinsics& from) : CameraIntrinsics(from) { SetDistortion(from.k1(), from.k2()); } @@ -320,14 +314,16 @@ void NukeCameraIntrinsics::SetDistortion(double k1, double k2) { void NukeCameraIntrinsics::ApplyIntrinsics(double normalized_x, double normalized_y, - double *image_x, - double *image_y) const { + double* image_x, + double* image_y) const { ApplyNukeDistortionModel(focal_length_x(), focal_length_y(), principal_point_x(), principal_point_y(), - image_width(), image_height(), - k1(), k2(), + image_width(), + image_height(), + k1(), + k2(), normalized_x, normalized_y, image_x, @@ -335,31 +331,31 @@ void NukeCameraIntrinsics::ApplyIntrinsics(double normalized_x, } void NukeCameraIntrinsics::InvertIntrinsics(double image_x, - double image_y, - double *normalized_x, - double *normalized_y) const { + double image_y, + double* normalized_x, + double* normalized_y) const { InvertNukeDistortionModel(focal_length_x(), focal_length_y(), principal_point_x(), principal_point_y(), - image_width(), image_height(), - k1(), k2(), + image_width(), + image_height(), + k1(), + k2(), image_x, image_y, normalized_x, normalized_y); } -void NukeCameraIntrinsics::Pack( - PackedIntrinsics* packed_intrinsics) const { +void NukeCameraIntrinsics::Pack(PackedIntrinsics* packed_intrinsics) const { CameraIntrinsics::Pack(packed_intrinsics); packed_intrinsics->SetK1(k1()); packed_intrinsics->SetK2(k2()); } -void NukeCameraIntrinsics::Unpack( - const PackedIntrinsics& packed_intrinsics) { +void NukeCameraIntrinsics::Unpack(const PackedIntrinsics& packed_intrinsics) { CameraIntrinsics::Unpack(packed_intrinsics); SetDistortion(packed_intrinsics.GetK1(), packed_intrinsics.GetK2()); @@ -367,14 +363,12 @@ void NukeCameraIntrinsics::Unpack( // Brown model. -BrownCameraIntrinsics::BrownCameraIntrinsics() - : CameraIntrinsics() { +BrownCameraIntrinsics::BrownCameraIntrinsics() : CameraIntrinsics() { SetRadialDistortion(0.0, 0.0, 0.0, 0.0); SetTangentialDistortion(0.0, 0.0); } -BrownCameraIntrinsics::BrownCameraIntrinsics( - const BrownCameraIntrinsics &from) +BrownCameraIntrinsics::BrownCameraIntrinsics(const BrownCameraIntrinsics& from) : CameraIntrinsics(from) { SetRadialDistortion(from.k1(), from.k2(), from.k3(), from.k4()); SetTangentialDistortion(from.p1(), from.p2()); @@ -391,8 +385,7 @@ void BrownCameraIntrinsics::SetRadialDistortion(double k1, ResetLookupGrids(); } -void BrownCameraIntrinsics::SetTangentialDistortion(double p1, - double p2) { +void BrownCameraIntrinsics::SetTangentialDistortion(double p1, double p2) { parameters_[OFFSET_P1] = p1; parameters_[OFFSET_P2] = p2; ResetLookupGrids(); @@ -400,39 +393,45 @@ void BrownCameraIntrinsics::SetTangentialDistortion(double p1, void BrownCameraIntrinsics::ApplyIntrinsics(double normalized_x, double normalized_y, - double *image_x, - double *image_y) const { + double* image_x, + double* image_y) const { ApplyBrownDistortionModel(focal_length_x(), focal_length_y(), principal_point_x(), principal_point_y(), - k1(), k2(), k3(), k4(), - p1(), p2(), + k1(), + k2(), + k3(), + k4(), + p1(), + p2(), normalized_x, normalized_y, image_x, image_y); } -void BrownCameraIntrinsics::InvertIntrinsics( - double image_x, - double image_y, - double *normalized_x, - double *normalized_y) const { +void BrownCameraIntrinsics::InvertIntrinsics(double image_x, + double image_y, + double* normalized_x, + double* normalized_y) const { InvertBrownDistortionModel(focal_length_x(), focal_length_y(), principal_point_x(), principal_point_y(), - k1(), k2(), k3(), k4(), - p1(), p2(), + k1(), + k2(), + k3(), + k4(), + p1(), + p2(), image_x, image_y, normalized_x, normalized_y); } -void BrownCameraIntrinsics::Pack( - PackedIntrinsics* packed_intrinsics) const { +void BrownCameraIntrinsics::Pack(PackedIntrinsics* packed_intrinsics) const { CameraIntrinsics::Pack(packed_intrinsics); packed_intrinsics->SetK1(k1()); @@ -444,8 +443,7 @@ void BrownCameraIntrinsics::Pack( packed_intrinsics->SetP2(p2()); } -void BrownCameraIntrinsics::Unpack( - const PackedIntrinsics& packed_intrinsics) { +void BrownCameraIntrinsics::Unpack(const PackedIntrinsics& packed_intrinsics) { CameraIntrinsics::Unpack(packed_intrinsics); SetRadialDistortion(packed_intrinsics.GetK1(), @@ -453,72 +451,65 @@ void BrownCameraIntrinsics::Unpack( packed_intrinsics.GetK3(), packed_intrinsics.GetK4()); - SetTangentialDistortion(packed_intrinsics.GetP1(), - packed_intrinsics.GetP2()); + SetTangentialDistortion(packed_intrinsics.GetP1(), packed_intrinsics.GetP2()); } -std::ostream& operator <<(std::ostream &os, - const CameraIntrinsics &intrinsics) { +std::ostream& operator<<(std::ostream& os, const CameraIntrinsics& intrinsics) { if (intrinsics.focal_length_x() == intrinsics.focal_length_x()) { os << "f=" << intrinsics.focal_length(); } else { - os << "fx=" << intrinsics.focal_length_x() + os << "fx=" << intrinsics.focal_length_x() << " fy=" << intrinsics.focal_length_y(); } os << " cx=" << intrinsics.principal_point_x() << " cy=" << intrinsics.principal_point_y() - << " w=" << intrinsics.image_width() - << " h=" << intrinsics.image_height(); + << " w=" << intrinsics.image_width() << " h=" << intrinsics.image_height(); -#define PRINT_NONZERO_COEFFICIENT(intrinsics, coeff) \ - { \ - if (intrinsics->coeff() != 0.0) { \ - os << " " #coeff "=" << intrinsics->coeff(); \ - } \ - } (void) 0 +#define PRINT_NONZERO_COEFFICIENT(intrinsics, coeff) \ + { \ + if (intrinsics->coeff() != 0.0) { \ + os << " " #coeff "=" << intrinsics->coeff(); \ + } \ + } \ + (void)0 switch (intrinsics.GetDistortionModelType()) { - case DISTORTION_MODEL_POLYNOMIAL: - { - const PolynomialCameraIntrinsics *polynomial_intrinsics = - static_cast<const PolynomialCameraIntrinsics *>(&intrinsics); - PRINT_NONZERO_COEFFICIENT(polynomial_intrinsics, k1); - PRINT_NONZERO_COEFFICIENT(polynomial_intrinsics, k2); - PRINT_NONZERO_COEFFICIENT(polynomial_intrinsics, k3); - PRINT_NONZERO_COEFFICIENT(polynomial_intrinsics, p1); - PRINT_NONZERO_COEFFICIENT(polynomial_intrinsics, p2); - break; - } - case DISTORTION_MODEL_DIVISION: - { - const DivisionCameraIntrinsics *division_intrinsics = - static_cast<const DivisionCameraIntrinsics *>(&intrinsics); - PRINT_NONZERO_COEFFICIENT(division_intrinsics, k1); - PRINT_NONZERO_COEFFICIENT(division_intrinsics, k2); - break; - } - case DISTORTION_MODEL_NUKE: - { - const NukeCameraIntrinsics *nuke_intrinsics = - static_cast<const NukeCameraIntrinsics *>(&intrinsics); - PRINT_NONZERO_COEFFICIENT(nuke_intrinsics, k1); - PRINT_NONZERO_COEFFICIENT(nuke_intrinsics, k2); - break; - } - case DISTORTION_MODEL_BROWN: - { - const BrownCameraIntrinsics *brown_intrinsics = - static_cast<const BrownCameraIntrinsics *>(&intrinsics); - PRINT_NONZERO_COEFFICIENT(brown_intrinsics, k1); - PRINT_NONZERO_COEFFICIENT(brown_intrinsics, k2); - PRINT_NONZERO_COEFFICIENT(brown_intrinsics, k3); - PRINT_NONZERO_COEFFICIENT(brown_intrinsics, k4); - PRINT_NONZERO_COEFFICIENT(brown_intrinsics, p1); - PRINT_NONZERO_COEFFICIENT(brown_intrinsics, p2); - break; - } - default: - LOG(FATAL) << "Unknown distortion model."; + case DISTORTION_MODEL_POLYNOMIAL: { + const PolynomialCameraIntrinsics* polynomial_intrinsics = + static_cast<const PolynomialCameraIntrinsics*>(&intrinsics); + PRINT_NONZERO_COEFFICIENT(polynomial_intrinsics, k1); + PRINT_NONZERO_COEFFICIENT(polynomial_intrinsics, k2); + PRINT_NONZERO_COEFFICIENT(polynomial_intrinsics, k3); + PRINT_NONZERO_COEFFICIENT(polynomial_intrinsics, p1); + PRINT_NONZERO_COEFFICIENT(polynomial_intrinsics, p2); + break; + } + case DISTORTION_MODEL_DIVISION: { + const DivisionCameraIntrinsics* division_intrinsics = + static_cast<const DivisionCameraIntrinsics*>(&intrinsics); + PRINT_NONZERO_COEFFICIENT(division_intrinsics, k1); + PRINT_NONZERO_COEFFICIENT(division_intrinsics, k2); + break; + } + case DISTORTION_MODEL_NUKE: { + const NukeCameraIntrinsics* nuke_intrinsics = + static_cast<const NukeCameraIntrinsics*>(&intrinsics); + PRINT_NONZERO_COEFFICIENT(nuke_intrinsics, k1); + PRINT_NONZERO_COEFFICIENT(nuke_intrinsics, k2); + break; + } + case DISTORTION_MODEL_BROWN: { + const BrownCameraIntrinsics* brown_intrinsics = + static_cast<const BrownCameraIntrinsics*>(&intrinsics); + PRINT_NONZERO_COEFFICIENT(brown_intrinsics, k1); + PRINT_NONZERO_COEFFICIENT(brown_intrinsics, k2); + PRINT_NONZERO_COEFFICIENT(brown_intrinsics, k3); + PRINT_NONZERO_COEFFICIENT(brown_intrinsics, k4); + PRINT_NONZERO_COEFFICIENT(brown_intrinsics, p1); + PRINT_NONZERO_COEFFICIENT(brown_intrinsics, p2); + break; + } + default: LOG(FATAL) << "Unknown distortion model."; } #undef PRINT_NONZERO_COEFFICIENT diff --git a/intern/libmv/libmv/simple_pipeline/camera_intrinsics.h b/intern/libmv/libmv/simple_pipeline/camera_intrinsics.h index ba67ec468dc..efe0735bd93 100644 --- a/intern/libmv/libmv/simple_pipeline/camera_intrinsics.h +++ b/intern/libmv/libmv/simple_pipeline/camera_intrinsics.h @@ -43,11 +43,11 @@ namespace internal { class LookupWarpGrid { public: LookupWarpGrid(); - LookupWarpGrid(const LookupWarpGrid &from); + LookupWarpGrid(const LookupWarpGrid& from); ~LookupWarpGrid(); // Width and height og the image, measured in pixels. - int width() const { return width_; } + int width() const { return width_; } int height() const { return height_; } // Overscan factor of the image, so that @@ -61,8 +61,8 @@ class LookupWarpGrid { // // See comment for CameraIntrinsics::DistortBuffer to get more // details about what overscan is. - template<typename WarpFunction> - void Update(const CameraIntrinsics &intrinsics, + template <typename WarpFunction> + void Update(const CameraIntrinsics& intrinsics, int width, int height, double overscan); @@ -71,12 +71,12 @@ class LookupWarpGrid { // // See comment for CameraIntrinsics::DistortBuffer to get more // details about template type. - template<typename PixelType> - void Apply(const PixelType *input_buffer, + template <typename PixelType> + void Apply(const PixelType* input_buffer, int width, int height, int channels, - PixelType *output_buffer); + PixelType* output_buffer); // Reset lookup grids. // This will tag the grid for update without re-computing it. @@ -105,15 +105,15 @@ class LookupWarpGrid { // // width and height corresponds to a size of buffer which will // be warped later. - template<typename WarpFunction> - void Compute(const CameraIntrinsics &intrinsics, + template <typename WarpFunction> + void Compute(const CameraIntrinsics& intrinsics, int width, int height, double overscan); // This is a buffer which contains per-pixel offset of the // pixels from input buffer to correspond the warping function. - Offset *offset_; + Offset* offset_; // Dimensions of the image this lookup grid processes. int width_, height_; @@ -130,19 +130,19 @@ class LookupWarpGrid { class CameraIntrinsics { public: CameraIntrinsics(); - CameraIntrinsics(const CameraIntrinsics &from); + CameraIntrinsics(const CameraIntrinsics& from); virtual ~CameraIntrinsics() {} virtual DistortionModelType GetDistortionModelType() const = 0; - int image_width() const { return image_width_; } + int image_width() const { return image_width_; } int image_height() const { return image_height_; } - const Mat3 &K() const { return K_; } + const Mat3& K() const { return K_; } - double focal_length() const { return K_(0, 0); } - double focal_length_x() const { return K_(0, 0); } - double focal_length_y() const { return K_(1, 1); } + double focal_length() const { return K_(0, 0); } + double focal_length_x() const { return K_(0, 0); } + double focal_length_y() const { return K_(1, 1); } double principal_point_x() const { return K_(0, 2); } double principal_point_y() const { return K_(1, 2); } @@ -166,14 +166,14 @@ class CameraIntrinsics { // Convert image space coordinates to normalized. void ImageSpaceToNormalized(double image_x, double image_y, - double *normalized_x, - double *normalized_y) const; + double* normalized_x, + double* normalized_y) const; // Convert normalized coordinates to image space. void NormalizedToImageSpace(double normalized_x, double normalized_y, - double *image_x, - double *image_y) const; + double* image_x, + double* image_y) const; // Apply camera intrinsics to the normalized point to get image coordinates. // @@ -182,8 +182,8 @@ class CameraIntrinsics { // coordinates in pixels. virtual void ApplyIntrinsics(double normalized_x, double normalized_y, - double *image_x, - double *image_y) const = 0; + double* image_x, + double* image_y) const = 0; // Invert camera intrinsics on the image point to get normalized coordinates. // @@ -191,8 +191,8 @@ class CameraIntrinsics { // coordinates to get normalized camera coordinates. virtual void InvertIntrinsics(double image_x, double image_y, - double *normalized_x, - double *normalized_y) const = 0; + double* normalized_x, + double* normalized_y) const = 0; virtual void Pack(PackedIntrinsics* packed_intrinsics) const; virtual void Unpack(const PackedIntrinsics& packed_intrinsics); @@ -218,13 +218,13 @@ class CameraIntrinsics { // But in fact PixelType might be any type for which multiplication by // a scalar and addition are implemented. For example PixelType might be // Vec3 as well. - template<typename PixelType> - void DistortBuffer(const PixelType *input_buffer, + template <typename PixelType> + void DistortBuffer(const PixelType* input_buffer, int width, int height, double overscan, int channels, - PixelType *output_buffer); + PixelType* output_buffer); // Undistort an image using the current camera instrinsics // @@ -247,13 +247,13 @@ class CameraIntrinsics { // But in fact PixelType might be any type for which multiplication by // a scalar and addition are implemented. For example PixelType might be // Vec3 as well. - template<typename PixelType> - void UndistortBuffer(const PixelType *input_buffer, + template <typename PixelType> + void UndistortBuffer(const PixelType* input_buffer, int width, int height, double overscan, int channels, - PixelType *output_buffer); + PixelType* output_buffer); private: // This is the size of the image. This is necessary to, for example, handle @@ -290,7 +290,7 @@ class PolynomialCameraIntrinsics : public CameraIntrinsics { }; PolynomialCameraIntrinsics(); - PolynomialCameraIntrinsics(const PolynomialCameraIntrinsics &from); + PolynomialCameraIntrinsics(const PolynomialCameraIntrinsics& from); DistortionModelType GetDistortionModelType() const override { return DISTORTION_MODEL_POLYNOMIAL; @@ -315,8 +315,8 @@ class PolynomialCameraIntrinsics : public CameraIntrinsics { // coordinates in pixels. void ApplyIntrinsics(double normalized_x, double normalized_y, - double *image_x, - double *image_y) const override; + double* image_x, + double* image_y) const override; // Invert camera intrinsics on the image point to get normalized coordinates. // @@ -324,8 +324,8 @@ class PolynomialCameraIntrinsics : public CameraIntrinsics { // coordinates to get normalized camera coordinates. void InvertIntrinsics(double image_x, double image_y, - double *normalized_x, - double *normalized_y) const override; + double* normalized_x, + double* normalized_y) const override; virtual void Pack(PackedIntrinsics* packed_intrinsics) const override; virtual void Unpack(const PackedIntrinsics& packed_intrinsics) override; @@ -352,7 +352,7 @@ class DivisionCameraIntrinsics : public CameraIntrinsics { }; DivisionCameraIntrinsics(); - DivisionCameraIntrinsics(const DivisionCameraIntrinsics &from); + DivisionCameraIntrinsics(const DivisionCameraIntrinsics& from); DistortionModelType GetDistortionModelType() const override { return DISTORTION_MODEL_DIVISION; @@ -371,8 +371,8 @@ class DivisionCameraIntrinsics : public CameraIntrinsics { // coordinates in pixels. void ApplyIntrinsics(double normalized_x, double normalized_y, - double *image_x, - double *image_y) const override; + double* image_x, + double* image_y) const override; // Invert camera intrinsics on the image point to get normalized coordinates. // @@ -380,8 +380,8 @@ class DivisionCameraIntrinsics : public CameraIntrinsics { // coordinates to get normalized camera coordinates. void InvertIntrinsics(double image_x, double image_y, - double *normalized_x, - double *normalized_y) const override; + double* normalized_x, + double* normalized_y) const override; virtual void Pack(PackedIntrinsics* packed_intrinsics) const override; virtual void Unpack(const PackedIntrinsics& packed_intrinsics) override; @@ -405,7 +405,7 @@ class NukeCameraIntrinsics : public CameraIntrinsics { }; NukeCameraIntrinsics(); - NukeCameraIntrinsics(const NukeCameraIntrinsics &from); + NukeCameraIntrinsics(const NukeCameraIntrinsics& from); DistortionModelType GetDistortionModelType() const override { return DISTORTION_MODEL_NUKE; @@ -424,8 +424,8 @@ class NukeCameraIntrinsics : public CameraIntrinsics { // coordinates in pixels. void ApplyIntrinsics(double normalized_x, double normalized_y, - double *image_x, - double *image_y) const override; + double* image_x, + double* image_y) const override; // Invert camera intrinsics on the image point to get normalized coordinates. // @@ -433,8 +433,8 @@ class NukeCameraIntrinsics : public CameraIntrinsics { // coordinates to get normalized camera coordinates. void InvertIntrinsics(double image_x, double image_y, - double *normalized_x, - double *normalized_y) const override; + double* normalized_x, + double* normalized_y) const override; virtual void Pack(PackedIntrinsics* packed_intrinsics) const override; virtual void Unpack(const PackedIntrinsics& packed_intrinsics) override; @@ -462,7 +462,7 @@ class BrownCameraIntrinsics : public CameraIntrinsics { }; BrownCameraIntrinsics(); - BrownCameraIntrinsics(const BrownCameraIntrinsics &from); + BrownCameraIntrinsics(const BrownCameraIntrinsics& from); DistortionModelType GetDistortionModelType() const override { return DISTORTION_MODEL_BROWN; @@ -488,8 +488,8 @@ class BrownCameraIntrinsics : public CameraIntrinsics { // coordinates in pixels. void ApplyIntrinsics(double normalized_x, double normalized_y, - double *image_x, - double *image_y) const override; + double* image_x, + double* image_y) const override; // Invert camera intrinsics on the image point to get normalized coordinates. // @@ -497,8 +497,8 @@ class BrownCameraIntrinsics : public CameraIntrinsics { // coordinates to get normalized camera coordinates. void InvertIntrinsics(double image_x, double image_y, - double *normalized_x, - double *normalized_y) const override; + double* normalized_x, + double* normalized_y) const override; virtual void Pack(PackedIntrinsics* packed_intrinsics) const override; virtual void Unpack(const PackedIntrinsics& packed_intrinsics) override; @@ -507,10 +507,8 @@ class BrownCameraIntrinsics : public CameraIntrinsics { double parameters_[NUM_PARAMETERS]; }; - /// A human-readable representation of the camera intrinsic parameters. -std::ostream& operator <<(std::ostream &os, - const CameraIntrinsics &intrinsics); +std::ostream& operator<<(std::ostream& os, const CameraIntrinsics& intrinsics); } // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/camera_intrinsics_impl.h b/intern/libmv/libmv/simple_pipeline/camera_intrinsics_impl.h index e1b53992dfd..c8c4700f5c6 100644 --- a/intern/libmv/libmv/simple_pipeline/camera_intrinsics_impl.h +++ b/intern/libmv/libmv/simple_pipeline/camera_intrinsics_impl.h @@ -25,11 +25,11 @@ namespace { // FIXME: C++ templates limitations makes thing complicated, // but maybe there is a simpler method. struct ApplyIntrinsicsFunction { - ApplyIntrinsicsFunction(const CameraIntrinsics &intrinsics, + ApplyIntrinsicsFunction(const CameraIntrinsics& intrinsics, double x, double y, - double *warp_x, - double *warp_y) { + double* warp_x, + double* warp_y) { double normalized_x, normalized_y; intrinsics.ImageSpaceToNormalized(x, y, &normalized_x, &normalized_y); intrinsics.ApplyIntrinsics(normalized_x, normalized_y, warp_x, warp_y); @@ -37,14 +37,15 @@ struct ApplyIntrinsicsFunction { }; struct InvertIntrinsicsFunction { - InvertIntrinsicsFunction(const CameraIntrinsics &intrinsics, + InvertIntrinsicsFunction(const CameraIntrinsics& intrinsics, double x, double y, - double *warp_x, - double *warp_y) { + double* warp_x, + double* warp_y) { double normalized_x, normalized_y; intrinsics.InvertIntrinsics(x, y, &normalized_x, &normalized_y); - intrinsics.NormalizedToImageSpace(normalized_x, normalized_y, warp_x, warp_y); + intrinsics.NormalizedToImageSpace( + normalized_x, normalized_y, warp_x, warp_y); } }; @@ -53,18 +54,18 @@ struct InvertIntrinsicsFunction { namespace internal { // TODO(MatthiasF): downsample lookup -template<typename WarpFunction> -void LookupWarpGrid::Compute(const CameraIntrinsics &intrinsics, +template <typename WarpFunction> +void LookupWarpGrid::Compute(const CameraIntrinsics& intrinsics, int width, int height, double overscan) { - double w = (double) width / (1.0 + overscan); - double h = (double) height / (1.0 + overscan); - double aspx = (double) w / intrinsics.image_width(); - double aspy = (double) h / intrinsics.image_height(); + double w = (double)width / (1.0 + overscan); + double h = (double)height / (1.0 + overscan); + double aspx = (double)w / intrinsics.image_width(); + double aspy = (double)h / intrinsics.image_height(); #if defined(_OPENMP) -# pragma omp parallel for schedule(static) num_threads(threads_) \ - if (threads_ > 1 && height > 100) +# pragma omp parallel for schedule(static) \ + num_threads(threads_) if (threads_ > 1 && height > 100) #endif for (int y = 0; y < height; y++) { for (int x = 0; x < width; x++) { @@ -76,40 +77,47 @@ void LookupWarpGrid::Compute(const CameraIntrinsics &intrinsics, warp_y = warp_y * aspy + 0.5 * overscan * h; int ix = int(warp_x), iy = int(warp_y); int fx = round((warp_x - ix) * 256), fy = round((warp_y - iy) * 256); - if (fx == 256) { fx = 0; ix++; } // NOLINT - if (fy == 256) { fy = 0; iy++; } // NOLINT + if (fx == 256) { + fx = 0; + ix++; + } // NOLINT + if (fy == 256) { + fy = 0; + iy++; + } // NOLINT // Use nearest border pixel - if (ix < 0) { ix = 0, fx = 0; } // NOLINT - if (iy < 0) { iy = 0, fy = 0; } // NOLINT - if (ix >= width - 2) ix = width - 2; - if (iy >= height - 2) iy = height - 2; - - Offset offset = { (short) (ix - x), - (short) (iy - y), - (unsigned char) fx, - (unsigned char) fy }; + if (ix < 0) { + ix = 0, fx = 0; + } // NOLINT + if (iy < 0) { + iy = 0, fy = 0; + } // NOLINT + if (ix >= width - 2) + ix = width - 2; + if (iy >= height - 2) + iy = height - 2; + + Offset offset = {(short)(ix - x), + (short)(iy - y), + (unsigned char)fx, + (unsigned char)fy}; offset_[y * width + x] = offset; } } } -template<typename WarpFunction> -void LookupWarpGrid::Update(const CameraIntrinsics &intrinsics, +template <typename WarpFunction> +void LookupWarpGrid::Update(const CameraIntrinsics& intrinsics, int width, int height, double overscan) { - if (width_ != width || - height_ != height || - overscan_ != overscan) { + if (width_ != width || height_ != height || overscan_ != overscan) { Reset(); } if (offset_ == NULL) { offset_ = new Offset[width * height]; - Compute<WarpFunction>(intrinsics, - width, - height, - overscan); + Compute<WarpFunction>(intrinsics, width, height, overscan); } width_ = width; @@ -118,29 +126,30 @@ void LookupWarpGrid::Update(const CameraIntrinsics &intrinsics, } // TODO(MatthiasF): cubic B-Spline image sampling, bilinear lookup -template<typename PixelType> -void LookupWarpGrid::Apply(const PixelType *input_buffer, +template <typename PixelType> +void LookupWarpGrid::Apply(const PixelType* input_buffer, int width, int height, int channels, - PixelType *output_buffer) { + PixelType* output_buffer) { #if defined(_OPENMP) -# pragma omp parallel for schedule(static) num_threads(threads_) \ - if (threads_ > 1 && height > 100) +# pragma omp parallel for schedule(static) \ + num_threads(threads_) if (threads_ > 1 && height > 100) #endif for (int y = 0; y < height; y++) { for (int x = 0; x < width; x++) { Offset offset = offset_[y * width + x]; - const int pixel_index = ((y + offset.iy) * width + - (x + offset.ix)) * channels; - const PixelType *s = &input_buffer[pixel_index]; + const int pixel_index = + ((y + offset.iy) * width + (x + offset.ix)) * channels; + const PixelType* s = &input_buffer[pixel_index]; for (int i = 0; i < channels; i++) { output_buffer[(y * width + x) * channels + i] = - ((s[i] * (256 - offset.fx) + - s[channels + i] * offset.fx) * (256 - offset.fy) + - (s[width * channels + i] * (256 - offset.fx) + - s[width * channels + channels + i] * offset.fx) * offset.fy) - / (256 * 256); + ((s[i] * (256 - offset.fx) + s[channels + i] * offset.fx) * + (256 - offset.fy) + + (s[width * channels + i] * (256 - offset.fx) + + s[width * channels + channels + i] * offset.fx) * + offset.fy) / + (256 * 256); } } } @@ -148,45 +157,33 @@ void LookupWarpGrid::Apply(const PixelType *input_buffer, } // namespace internal -template<typename PixelType> -void CameraIntrinsics::DistortBuffer(const PixelType *input_buffer, +template <typename PixelType> +void CameraIntrinsics::DistortBuffer(const PixelType* input_buffer, int width, int height, double overscan, int channels, - PixelType *output_buffer) { + PixelType* output_buffer) { assert(channels >= 1); assert(channels <= 4); - distort_.Update<InvertIntrinsicsFunction>(*this, - width, - height, - overscan); - distort_.Apply<PixelType>(input_buffer, - width, - height, - channels, - output_buffer); + distort_.Update<InvertIntrinsicsFunction>(*this, width, height, overscan); + distort_.Apply<PixelType>( + input_buffer, width, height, channels, output_buffer); } -template<typename PixelType> -void CameraIntrinsics::UndistortBuffer(const PixelType *input_buffer, +template <typename PixelType> +void CameraIntrinsics::UndistortBuffer(const PixelType* input_buffer, int width, int height, double overscan, int channels, - PixelType *output_buffer) { + PixelType* output_buffer) { assert(channels >= 1); assert(channels <= 4); - undistort_.Update<ApplyIntrinsicsFunction>(*this, - width, - height, - overscan); - - undistort_.Apply<PixelType>(input_buffer, - width, - height, - channels, - output_buffer); + undistort_.Update<ApplyIntrinsicsFunction>(*this, width, height, overscan); + + undistort_.Apply<PixelType>( + input_buffer, width, height, channels, output_buffer); } } // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/camera_intrinsics_test.cc b/intern/libmv/libmv/simple_pipeline/camera_intrinsics_test.cc index 96d35a29ef8..cfcc2d16682 100644 --- a/intern/libmv/libmv/simple_pipeline/camera_intrinsics_test.cc +++ b/intern/libmv/libmv/simple_pipeline/camera_intrinsics_test.cc @@ -22,10 +22,10 @@ #include <iostream> -#include "testing/testing.h" #include "libmv/image/image.h" #include "libmv/image/image_drawing.h" #include "libmv/logging/logging.h" +#include "testing/testing.h" namespace libmv { @@ -59,26 +59,36 @@ TEST(PolynomialCameraIntrinsics, ApplyIntrinsics) { const int N = 5; double expected[N][N][2] = { - { {75.312500, -24.687500}, {338.982239, -62.035522}, - {640.000000, -72.929688}, {941.017761, -62.035522}, - {1204.687500, -24.687500}}, - - { {37.964478, 238.982239}, {323.664551, 223.664551}, - {640.000000, 219.193420}, {956.335449, 223.664551}, - {1242.035522, 238.982239}}, - - { {27.070312, 540.000000}, {319.193420, 540.000000}, - {640.000000, 540.000000}, {960.806580, 540.000000}, - {1252.929688, 540.000000}}, - - { {37.964478, 841.017761}, {323.664551, 856.335449}, - {640.000000, 860.806580}, {956.335449, 856.335449}, - {1242.035522, 841.017761}}, - - { {75.312500, 1104.687500}, {338.982239, 1142.035522}, - {640.000000, 1152.929688}, {941.017761, 1142.035522}, - {1204.687500, 1104.687500}} - }; + {{75.312500, -24.687500}, + {338.982239, -62.035522}, + {640.000000, -72.929688}, + {941.017761, -62.035522}, + {1204.687500, -24.687500}}, + + {{37.964478, 238.982239}, + {323.664551, 223.664551}, + {640.000000, 219.193420}, + {956.335449, 223.664551}, + {1242.035522, 238.982239}}, + + {{27.070312, 540.000000}, + {319.193420, 540.000000}, + {640.000000, 540.000000}, + {960.806580, 540.000000}, + {1252.929688, 540.000000}}, + + {{37.964478, 841.017761}, + {323.664551, 856.335449}, + {640.000000, 860.806580}, + {956.335449, 856.335449}, + {1242.035522, 841.017761}}, + + {{75.312500, 1104.687500}, + {338.982239, 1142.035522}, + {640.000000, 1152.929688}, + {941.017761, 1142.035522}, + {1204.687500, 1104.687500}}, + }; PolynomialCameraIntrinsics intrinsics; intrinsics.SetFocalLength(1300.0, 1300.0); @@ -89,12 +99,11 @@ TEST(PolynomialCameraIntrinsics, ApplyIntrinsics) { for (int i = 0; i < N; i++) { for (int j = 0; j < N; j++) { - double normalized_x = j * step - 0.5, - normalized_y = i * step - 0.5; + double normalized_x = j * step - 0.5, normalized_y = i * step - 0.5; double distorted_x, distorted_y; - intrinsics.ApplyIntrinsics(normalized_x, normalized_y, - &distorted_x, &distorted_y); + intrinsics.ApplyIntrinsics( + normalized_x, normalized_y, &distorted_x, &distorted_y); EXPECT_NEAR(expected[i][j][0], distorted_x, 1e-6); EXPECT_NEAR(expected[i][j][1], distorted_y, 1e-6); @@ -106,43 +115,51 @@ TEST(PolynomialCameraIntrinsics, InvertIntrinsics) { const int N = 5; double expected[N][N][2] = { - { {-0.524482, -0.437069}, {-0.226237, -0.403994}, - { 0.031876, -0.398446}, { 0.293917, -0.408218}, - { 0.632438, -0.465028}}, - - { {-0.493496, -0.189173}, {-0.219052, -0.179936}, - { 0.030975, -0.178107}, { 0.283742, -0.181280}, - { 0.574557, -0.194335}}, - - { {-0.488013, 0.032534}, {-0.217537, 0.031077}, - { 0.030781, 0.030781}, { 0.281635, 0.031293}, - { 0.566344, 0.033314}}, - - { {-0.498696, 0.257660}, {-0.220424, 0.244041}, - { 0.031150, 0.241409}, { 0.285660, 0.245985}, - { 0.582670, 0.265629}}, - - { {-0.550617, 0.532263}, {-0.230399, 0.477255}, - { 0.032380, 0.469510}, { 0.299986, 0.483311}, - { 0.684740, 0.584043}} - }; + {{-0.524482, -0.437069}, + {-0.226237, -0.403994}, + {0.031876, -0.398446}, + {0.293917, -0.408218}, + {0.632438, -0.465028}}, + + {{-0.493496, -0.189173}, + {-0.219052, -0.179936}, + {0.030975, -0.178107}, + {0.283742, -0.181280}, + {0.574557, -0.194335}}, + + {{-0.488013, 0.032534}, + {-0.217537, 0.031077}, + {0.030781, 0.030781}, + {0.281635, 0.031293}, + {0.566344, 0.033314}}, + + {{-0.498696, 0.257660}, + {-0.220424, 0.244041}, + {0.031150, 0.241409}, + {0.285660, 0.245985}, + {0.582670, 0.265629}}, + + {{-0.550617, 0.532263}, + {-0.230399, 0.477255}, + {0.032380, 0.469510}, + {0.299986, 0.483311}, + {0.684740, 0.584043}}, + }; PolynomialCameraIntrinsics intrinsics; intrinsics.SetFocalLength(1300.0, 1300.0); intrinsics.SetPrincipalPoint(600.0, 500.0); intrinsics.SetRadialDistortion(-0.2, -0.1, -0.05); - double step_x = 1280.0 / (N - 1), - step_y = 1080.0 / (N - 1); + double step_x = 1280.0 / (N - 1), step_y = 1080.0 / (N - 1); for (int i = 0; i < N; i++) { for (int j = 0; j < N; j++) { - double distorted_x = j * step_x, - distorted_y = i * step_y; + double distorted_x = j * step_x, distorted_y = i * step_y; double normalized_x, normalized_y; - intrinsics.InvertIntrinsics(distorted_x, distorted_y, - &normalized_x, &normalized_y); + intrinsics.InvertIntrinsics( + distorted_x, distorted_y, &normalized_x, &normalized_y); EXPECT_NEAR(expected[i][j][0], normalized_x, 1e-6); EXPECT_NEAR(expected[i][j][1], normalized_y, 1e-6); @@ -190,10 +207,11 @@ TEST(PolynomialCameraIntrinsics, IdentityDistortBuffer) { FloatImage distorted_image(h, w); intrinsics.SetImageSize(w, h); intrinsics.SetFocalLength(10.0, 10.0); - intrinsics.SetPrincipalPoint((double) w / 2.0, (double) h / 2.0); + intrinsics.SetPrincipalPoint((double)w / 2.0, (double)h / 2.0); intrinsics.SetRadialDistortion(0.0, 0.0, 0.0); intrinsics.DistortBuffer(image.Data(), - image.Width(), image.Height(), + image.Width(), + image.Height(), 0.0, image.Depth(), distorted_image.Data()); @@ -221,10 +239,11 @@ TEST(PolynomialCameraIntrinsics, IdentityUndistortBuffer) { FloatImage distorted_image(h, w); intrinsics.SetImageSize(w, h); intrinsics.SetFocalLength(10.0, 10.0); - intrinsics.SetPrincipalPoint((double) w / 2.0, (double) h / 2.0); + intrinsics.SetPrincipalPoint((double)w / 2.0, (double)h / 2.0); intrinsics.SetRadialDistortion(0.0, 0.0, 0.0); intrinsics.UndistortBuffer(image.Data(), - image.Width(), image.Height(), + image.Width(), + image.Height(), 0.0, image.Depth(), distorted_image.Data()); diff --git a/intern/libmv/libmv/simple_pipeline/detect.cc b/intern/libmv/libmv/simple_pipeline/detect.cc index 46599a4c49e..0897c5598c6 100644 --- a/intern/libmv/libmv/simple_pipeline/detect.cc +++ b/intern/libmv/libmv/simple_pipeline/detect.cc @@ -22,14 +22,14 @@ ** ****************************************************************************/ -#include <stdlib.h> #include <memory.h> +#include <stdlib.h> #include <queue> #include "libmv/base/scoped_ptr.h" #include "libmv/image/array_nd.h" -#include "libmv/image/image_converter.h" #include "libmv/image/convolve.h" +#include "libmv/image/image_converter.h" #include "libmv/logging/logging.h" #include "libmv/simple_pipeline/detect.h" @@ -55,7 +55,7 @@ double kDefaultHarrisThreshold = 1e-5; class FeatureComparison { public: - bool operator() (const Feature &left, const Feature &right) const { + bool operator()(const Feature& left, const Feature& right) const { return right.score > left.score; } }; @@ -63,18 +63,17 @@ class FeatureComparison { // Filter the features so there are no features closer than // minimal distance to each other. // This is a naive implementation with O(n^2) asymptotic. -void FilterFeaturesByDistance(const vector<Feature> &all_features, +void FilterFeaturesByDistance(const vector<Feature>& all_features, int min_distance, - vector<Feature> *detected_features) { + vector<Feature>* detected_features) { const int min_distance_squared = min_distance * min_distance; // Use priority queue to sort the features by their score. // // Do this on copy of the input features to prevent possible // distortion in callee function behavior. - std::priority_queue<Feature, - std::vector<Feature>, - FeatureComparison> priority_features; + std::priority_queue<Feature, std::vector<Feature>, FeatureComparison> + priority_features; for (int i = 0; i < all_features.size(); i++) { priority_features.push(all_features.at(i)); @@ -85,7 +84,7 @@ void FilterFeaturesByDistance(const vector<Feature> &all_features, Feature a = priority_features.top(); for (int i = 0; i < detected_features->size(); i++) { - Feature &b = detected_features->at(i); + Feature& b = detected_features->at(i); if (Square(a.x - b.x) + Square(a.y - b.y) < min_distance_squared) { ok = false; break; @@ -100,9 +99,9 @@ void FilterFeaturesByDistance(const vector<Feature> &all_features, } } -void DetectFAST(const FloatImage &grayscale_image, - const DetectOptions &options, - vector<Feature> *detected_features) { +void DetectFAST(const FloatImage& grayscale_image, + const DetectOptions& options, + vector<Feature>* detected_features) { #ifndef LIBMV_NO_FAST_DETECTOR const int min_distance = options.min_distance; const int min_trackness = options.fast_min_trackness; @@ -111,12 +110,14 @@ void DetectFAST(const FloatImage &grayscale_image, const int height = grayscale_image.Width() - 2 * margin; const int stride = grayscale_image.Width(); - scoped_array<unsigned char> byte_image(FloatImageToUCharArray(grayscale_image)); + scoped_array<unsigned char> byte_image( + FloatImageToUCharArray(grayscale_image)); const int byte_image_offset = margin * stride + margin; - // TODO(MatthiasF): Support targetting a feature count (binary search trackness) + // TODO(MatthiasF): Support targetting a feature count (binary search + // trackness) int num_features; - xy *all = fast9_detect(byte_image.get() + byte_image_offset, + xy* all = fast9_detect(byte_image.get() + byte_image_offset, width, height, stride, @@ -126,13 +127,13 @@ void DetectFAST(const FloatImage &grayscale_image, free(all); return; } - int *scores = fast9_score(byte_image.get() + byte_image_offset, + int* scores = fast9_score(byte_image.get() + byte_image_offset, stride, all, num_features, min_trackness); // TODO(MatthiasF): merge with close feature suppression - xy *nonmax = nonmax_suppression(all, scores, num_features, &num_features); + xy* nonmax = nonmax_suppression(all, scores, num_features, &num_features); free(all); // Remove too close features // TODO(MatthiasF): A resolution independent parameter would be better than @@ -152,89 +153,104 @@ void DetectFAST(const FloatImage &grayscale_image, free(scores); free(nonmax); #else - (void) grayscale_image; // Ignored. - (void) options; // Ignored. - (void) detected_features; // Ignored. + (void)grayscale_image; // Ignored. + (void)options; // Ignored. + (void)detected_features; // Ignored. LOG(FATAL) << "FAST detector is disabled in this build."; #endif } #ifdef __SSE2__ -static unsigned int SAD(const ubyte* imageA, const ubyte* imageB, - int strideA, int strideB) { +static unsigned int SAD(const ubyte* imageA, + const ubyte* imageB, + int strideA, + int strideB) { __m128i a = _mm_setzero_si128(); for (int i = 0; i < 16; i++) { - a = _mm_adds_epu16(a, - _mm_sad_epu8(_mm_loadu_si128((__m128i*)(imageA+i*strideA)), - _mm_loadu_si128((__m128i*)(imageB+i*strideB)))); + a = _mm_adds_epu16( + a, + _mm_sad_epu8(_mm_loadu_si128((__m128i*)(imageA + i * strideA)), + _mm_loadu_si128((__m128i*)(imageB + i * strideB)))); } return _mm_extract_epi16(a, 0) + _mm_extract_epi16(a, 4); } #else -static unsigned int SAD(const ubyte* imageA, const ubyte* imageB, - int strideA, int strideB) { +static unsigned int SAD(const ubyte* imageA, + const ubyte* imageB, + int strideA, + int strideB) { unsigned int sad = 0; for (int i = 0; i < 16; i++) { for (int j = 0; j < 16; j++) { - sad += abs((int)imageA[i*strideA+j] - imageB[i*strideB+j]); + sad += abs((int)imageA[i * strideA + j] - imageB[i * strideB + j]); } } return sad; } #endif -void DetectMORAVEC(const FloatImage &grayscale_image, - const DetectOptions &options, - vector<Feature> *detected_features) { +void DetectMORAVEC(const FloatImage& grayscale_image, + const DetectOptions& options, + vector<Feature>* detected_features) { const int distance = options.min_distance; const int margin = options.margin; - const unsigned char *pattern = options.moravec_pattern; + const unsigned char* pattern = options.moravec_pattern; const int count = options.moravec_max_count; const int width = grayscale_image.Width() - 2 * margin; const int height = grayscale_image.Width() - 2 * margin; const int stride = grayscale_image.Width(); - scoped_array<unsigned char> byte_image(FloatImageToUCharArray(grayscale_image)); + scoped_array<unsigned char> byte_image( + FloatImageToUCharArray(grayscale_image)); unsigned short histogram[256]; memset(histogram, 0, sizeof(histogram)); - scoped_array<ubyte> scores(new ubyte[width*height]); - memset(scores.get(), 0, width*height); + scoped_array<ubyte> scores(new ubyte[width * height]); + memset(scores.get(), 0, width * height); const int r = 1; // radius for self similarity comparison - for (int y = distance; y < height-distance; y++) { - for (int x = distance; x < width-distance; x++) { - const ubyte* s = &byte_image[y*stride+x]; - int score = // low self-similarity with overlapping patterns - // OPTI: load pattern once + for (int y = distance; y < height - distance; y++) { + for (int x = distance; x < width - distance; x++) { + const ubyte* s = &byte_image[y * stride + x]; + // low self-similarity with overlapping patterns + // OPTI: load pattern once + // clang-format off + int score = SAD(s, s-r*stride-r, stride, stride)+SAD(s, s-r*stride, stride, stride)+SAD(s, s-r*stride+r, stride, stride)+ SAD(s, s -r, stride, stride)+ SAD(s, s +r, stride, stride)+ SAD(s, s+r*stride-r, stride, stride)+SAD(s, s+r*stride, stride, stride)+SAD(s, s+r*stride+r, stride, stride); + // clang-format on + score /= 256; // normalize - if (pattern) // find only features similar to pattern + if (pattern) // find only features similar to pattern score -= SAD(s, pattern, stride, 16); - if (score <= 16) continue; // filter very self-similar features + if (score <= 16) + continue; // filter very self-similar features score -= 16; // translate to score/histogram values - if (score>255) score=255; // clip - ubyte* c = &scores[y*width+x]; + if (score > 255) + score = 255; // clip + ubyte* c = &scores[y * width + x]; for (int i = -distance; i < 0; i++) { for (int j = -distance; j < distance; j++) { - int s = c[i*width+j]; - if (s == 0) continue; - if (s >= score) goto nonmax; - c[i*width+j] = 0; + int s = c[i * width + j]; + if (s == 0) + continue; + if (s >= score) + goto nonmax; + c[i * width + j] = 0; histogram[s]--; } } for (int i = 0, j = -distance; j < 0; j++) { - int s = c[i*width+j]; - if (s == 0) continue; - if (s >= score) goto nonmax; - c[i*width+j] = 0; + int s = c[i * width + j]; + if (s == 0) + continue; + if (s >= score) + goto nonmax; + c[i * width + j] = 0; histogram[s]--; } c[0] = score, histogram[score]++; - nonmax: - { } // Do nothing. + nonmax : {} // Do nothing. } } int min = 255, total = 0; @@ -254,18 +270,16 @@ void DetectMORAVEC(const FloatImage &grayscale_image, // Score calculation above uses top left corner of the // patch as the origin, here we need to convert this value // to a pattrn center by adding 8 pixels. - detected_features->push_back(Feature((float) x + 8.0f, - (float) y + 8.0f, - (float) s, - 16.0f)); + detected_features->push_back( + Feature((float)x + 8.0f, (float)y + 8.0f, (float)s, 16.0f)); } } } } -void DetectHarris(const FloatImage &grayscale_image, - const DetectOptions &options, - vector<Feature> *detected_features) { +void DetectHarris(const FloatImage& grayscale_image, + const DetectOptions& options, + vector<Feature>* detected_features) { const double alpha = 0.06; const double sigma = 0.9; @@ -281,9 +295,7 @@ void DetectHarris(const FloatImage &grayscale_image, MultiplyElements(gradient_y, gradient_y, &gradient_yy); MultiplyElements(gradient_x, gradient_y, &gradient_xy); - FloatImage gradient_xx_blurred, - gradient_yy_blurred, - gradient_xy_blurred; + FloatImage gradient_xx_blurred, gradient_yy_blurred, gradient_xy_blurred; ConvolveGaussian(gradient_xx, sigma, &gradient_xx_blurred); ConvolveGaussian(gradient_yy, sigma, &gradient_yy_blurred); ConvolveGaussian(gradient_xy, sigma, &gradient_xy_blurred); @@ -304,10 +316,8 @@ void DetectHarris(const FloatImage &grayscale_image, double traceA = A.trace(); double harris_function = detA - alpha * traceA * traceA; if (harris_function > threshold) { - all_features.push_back(Feature((float) x, - (float) y, - (float) harris_function, - 5.0f)); + all_features.push_back( + Feature((float)x, (float)y, (float)harris_function, 5.0f)); } } } @@ -318,17 +328,18 @@ void DetectHarris(const FloatImage &grayscale_image, } // namespace DetectOptions::DetectOptions() - : type(DetectOptions::HARRIS), - margin(0), - min_distance(120), - fast_min_trackness(kDefaultFastMinTrackness), - moravec_max_count(0), - moravec_pattern(NULL), - harris_threshold(kDefaultHarrisThreshold) {} - -void Detect(const FloatImage &image, - const DetectOptions &options, - vector<Feature> *detected_features) { + : type(DetectOptions::HARRIS), + margin(0), + min_distance(120), + fast_min_trackness(kDefaultFastMinTrackness), + moravec_max_count(0), + moravec_pattern(NULL), + harris_threshold(kDefaultHarrisThreshold) { +} + +void Detect(const FloatImage& image, + const DetectOptions& options, + vector<Feature>* detected_features) { // Currently all the detectors requires image to be grayscale. // Do it here to avoid code duplication. FloatImage grayscale_image; @@ -350,8 +361,7 @@ void Detect(const FloatImage &image, } } -std::ostream& operator <<(std::ostream &os, - const Feature &feature) { +std::ostream& operator<<(std::ostream& os, const Feature& feature) { os << "x: " << feature.x << ", y: " << feature.y; os << ", score: " << feature.score; os << ", size: " << feature.size; diff --git a/intern/libmv/libmv/simple_pipeline/detect.h b/intern/libmv/libmv/simple_pipeline/detect.h index 1035287bcf2..8ddf0025e4b 100644 --- a/intern/libmv/libmv/simple_pipeline/detect.h +++ b/intern/libmv/libmv/simple_pipeline/detect.h @@ -39,7 +39,7 @@ typedef unsigned char ubyte; struct Feature { Feature(float x, float y) : x(x), y(y) {} Feature(float x, float y, float score, float size) - : x(x), y(y), score(score), size(size) {} + : x(x), y(y), score(score), size(size) {} // Position of the feature in pixels from top-left corner. // Note: Libmv detector might eventually support subpixel precision. @@ -88,9 +88,9 @@ struct DetectOptions { // Find only features similar to this pattern. Only used by MORAVEC detector. // - // This is an image patch denoted in byte array with dimensions of 16px by 16px - // used to filter features by similarity to this patch. - unsigned char *moravec_pattern; + // This is an image patch denoted in byte array with dimensions of 16px by + // 16px used to filter features by similarity to this patch. + unsigned char* moravec_pattern; // Threshold value of the Harris function to add new featrue // to the result. @@ -101,12 +101,11 @@ struct DetectOptions { // // Image could have 1-4 channels, it'll be converted to a grayscale // by the detector function if needed. -void Detect(const FloatImage &image, - const DetectOptions &options, - vector<Feature> *detected_features); +void Detect(const FloatImage& image, + const DetectOptions& options, + vector<Feature>* detected_features); -std::ostream& operator <<(std::ostream &os, - const Feature &feature); +std::ostream& operator<<(std::ostream& os, const Feature& feature); } // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/detect_test.cc b/intern/libmv/libmv/simple_pipeline/detect_test.cc index b226ad96595..718598d04e1 100644 --- a/intern/libmv/libmv/simple_pipeline/detect_test.cc +++ b/intern/libmv/libmv/simple_pipeline/detect_test.cc @@ -20,14 +20,14 @@ #include "libmv/simple_pipeline/detect.h" -#include "testing/testing.h" #include "libmv/logging/logging.h" +#include "testing/testing.h" namespace libmv { namespace { -void PreformSinglePointTest(const DetectOptions &options) { +void PreformSinglePointTest(const DetectOptions& options) { // Prepare the image. FloatImage image(15, 15); image.fill(1.0); @@ -40,7 +40,7 @@ void PreformSinglePointTest(const DetectOptions &options) { // Check detected features matches our expectations. EXPECT_EQ(1, detected_features.size()); if (detected_features.size() == 1) { - Feature &feature = detected_features[0]; + Feature& feature = detected_features[0]; EXPECT_EQ(7, feature.x); EXPECT_EQ(7, feature.y); } @@ -83,8 +83,8 @@ void PreformCheckerBoardTest(const DetectOptions &options) { } #endif -void CheckExpectedFeatures(const vector<Feature> &detected_features, - const vector<Feature> &expected_features) { +void CheckExpectedFeatures(const vector<Feature>& detected_features, + const vector<Feature>& expected_features) { EXPECT_EQ(expected_features.size(), detected_features.size()); // That's unsafe to iterate over vectors when their lengths @@ -95,10 +95,10 @@ void CheckExpectedFeatures(const vector<Feature> &detected_features, } for (int i = 0; i < expected_features.size(); ++i) { - const Feature &extected_feature = expected_features[i]; + const Feature& extected_feature = expected_features[i]; bool found = false; for (int j = 0; j < detected_features.size(); ++j) { - const Feature &detected_feature = detected_features[j]; + const Feature& detected_feature = detected_features[j]; if (extected_feature.x == detected_feature.x && extected_feature.y == detected_feature.y) { found = true; @@ -109,15 +109,14 @@ void CheckExpectedFeatures(const vector<Feature> &detected_features, } } -void PreformSingleTriangleTest(const DetectOptions &options) { +void PreformSingleTriangleTest(const DetectOptions& options) { // Prepare the image. FloatImage image(15, 21); image.fill(1.0); int vertex_x = 10, vertex_y = 5; for (int i = 0; i < 6; ++i) { - int current_x = vertex_x - i, - current_y = vertex_y + i; + int current_x = vertex_x - i, current_y = vertex_y + i; for (int j = 0; j < i * 2 + 1; ++j, ++current_x) { image(current_y, current_x) = 0.0; } diff --git a/intern/libmv/libmv/simple_pipeline/distortion_models.cc b/intern/libmv/libmv/simple_pipeline/distortion_models.cc index f602234b630..4556e3ceaf9 100644 --- a/intern/libmv/libmv/simple_pipeline/distortion_models.cc +++ b/intern/libmv/libmv/simple_pipeline/distortion_models.cc @@ -41,25 +41,34 @@ struct InvertPolynomialIntrinsicsCostFunction { const double p2, const double image_x, const double image_y) - : focal_length_x_(focal_length_x), - focal_length_y_(focal_length_y), - principal_point_x_(principal_point_x), - principal_point_y_(principal_point_y), - k1_(k1), k2_(k2), k3_(k3), - p1_(p1), p2_(p2), - x_(image_x), y_(image_y) {} - - Vec2 operator()(const Vec2 &u) const { + : focal_length_x_(focal_length_x), + focal_length_y_(focal_length_y), + principal_point_x_(principal_point_x), + principal_point_y_(principal_point_y), + k1_(k1), + k2_(k2), + k3_(k3), + p1_(p1), + p2_(p2), + x_(image_x), + y_(image_y) {} + + Vec2 operator()(const Vec2& u) const { double xx, yy; ApplyPolynomialDistortionModel(focal_length_x_, focal_length_y_, principal_point_x_, principal_point_y_, - k1_, k2_, k3_, - p1_, p2_, - u(0), u(1), - &xx, &yy); + k1_, + k2_, + k3_, + p1_, + p2_, + u(0), + u(1), + &xx, + &yy); Vec2 fx; fx << (xx - x_), (yy - y_); @@ -87,23 +96,28 @@ struct InvertDivisionIntrinsicsCostFunction { const double k2, const double image_x, const double image_y) - : focal_length_x_(focal_length_x), - focal_length_y_(focal_length_y), - principal_point_x_(principal_point_x), - principal_point_y_(principal_point_y), - k1_(k1), k2_(k2), - x_(image_x), y_(image_y) {} - - Vec2 operator()(const Vec2 &u) const { + : focal_length_x_(focal_length_x), + focal_length_y_(focal_length_y), + principal_point_x_(principal_point_x), + principal_point_y_(principal_point_y), + k1_(k1), + k2_(k2), + x_(image_x), + y_(image_y) {} + + Vec2 operator()(const Vec2& u) const { double xx, yy; ApplyDivisionDistortionModel(focal_length_x_, focal_length_y_, principal_point_x_, principal_point_y_, - k1_, k2_, - u(0), u(1), - &xx, &yy); + k1_, + k2_, + u(0), + u(1), + &xx, + &yy); Vec2 fx; fx << (xx - x_), (yy - y_); @@ -134,25 +148,36 @@ struct InvertBrownIntrinsicsCostFunction { const double p2, const double image_x, const double image_y) - : focal_length_x_(focal_length_x), - focal_length_y_(focal_length_y), - principal_point_x_(principal_point_x), - principal_point_y_(principal_point_y), - k1_(k1), k2_(k2), k3_(k3), k4_(k4), - p1_(p1), p2_(p2), - x_(image_x), y_(image_y) {} - - Vec2 operator()(const Vec2 &u) const { + : focal_length_x_(focal_length_x), + focal_length_y_(focal_length_y), + principal_point_x_(principal_point_x), + principal_point_y_(principal_point_y), + k1_(k1), + k2_(k2), + k3_(k3), + k4_(k4), + p1_(p1), + p2_(p2), + x_(image_x), + y_(image_y) {} + + Vec2 operator()(const Vec2& u) const { double xx, yy; ApplyBrownDistortionModel(focal_length_x_, focal_length_y_, principal_point_x_, principal_point_y_, - k1_, k2_, k3_, k4_, - p1_, p2_, - u(0), u(1), - &xx, &yy); + k1_, + k2_, + k3_, + k4_, + p1_, + p2_, + u(0), + u(1), + &xx, + &yy); Vec2 fx; fx << (xx - x_), (yy - y_); @@ -180,8 +205,8 @@ void InvertPolynomialDistortionModel(const double focal_length_x, const double p2, const double image_x, const double image_y, - double *normalized_x, - double *normalized_y) { + double* normalized_x, + double* normalized_y) { // Compute the initial guess. For a camera with no distortion, this will also // be the final answer; the LM iteration will terminate immediately. Vec2 normalized; @@ -194,13 +219,17 @@ void InvertPolynomialDistortionModel(const double focal_length_x, focal_length_y, principal_point_x, principal_point_y, - k1, k2, k3, - p1, p2, - image_x, image_y); + k1, + k2, + k3, + p1, + p2, + image_x, + image_y); Solver::SolverParameters params; Solver solver(intrinsics_cost); - /*Solver::Results results =*/ solver.minimize(params, &normalized); + /*Solver::Results results =*/solver.minimize(params, &normalized); // TODO(keir): Better error handling. @@ -216,8 +245,8 @@ void InvertDivisionDistortionModel(const double focal_length_x, const double k2, const double image_x, const double image_y, - double *normalized_x, - double *normalized_y) { + double* normalized_x, + double* normalized_y) { // Compute the initial guess. For a camera with no distortion, this will also // be the final answer; the LM iteration will terminate immediately. Vec2 normalized; @@ -231,12 +260,14 @@ void InvertDivisionDistortionModel(const double focal_length_x, focal_length_y, principal_point_x, principal_point_y, - k1, k2, - image_x, image_y); + k1, + k2, + image_x, + image_y); Solver::SolverParameters params; Solver solver(intrinsics_cost); - /*Solver::Results results =*/ solver.minimize(params, &normalized); + /*Solver::Results results =*/solver.minimize(params, &normalized); // TODO(keir): Better error handling. @@ -256,8 +287,8 @@ void InvertBrownDistortionModel(const double focal_length_x, const double p2, const double image_x, const double image_y, - double *normalized_x, - double *normalized_y) { + double* normalized_x, + double* normalized_y) { // Compute the initial guess. For a camera with no distortion, this will also // be the final answer; the LM iteration will terminate immediately. Vec2 normalized; @@ -270,13 +301,18 @@ void InvertBrownDistortionModel(const double focal_length_x, focal_length_y, principal_point_x, principal_point_y, - k1, k2, k3, k4, - p1, p2, - image_x, image_y); + k1, + k2, + k3, + k4, + p1, + p2, + image_x, + image_y); Solver::SolverParameters params; Solver solver(intrinsics_cost); - /*Solver::Results results =*/ solver.minimize(params, &normalized); + /*Solver::Results results =*/solver.minimize(params, &normalized); // TODO(keir): Better error handling. @@ -299,31 +335,36 @@ struct ApplyNukeIntrinsicsCostFunction { const double k2, const double expected_normalized_x, const double expected_normalized_y) - : focal_length_x_(focal_length_x), - focal_length_y_(focal_length_y), - principal_point_x_(principal_point_x), - principal_point_y_(principal_point_y), - image_width_(image_width), - image_height_(image_height), - k1_(k1), k2_(k2), - expected_normalized_x_(expected_normalized_x), - expected_normalized_y_(expected_normalized_y) {} - - Vec2 operator()(const Vec2 &image_coordinate) const { + : focal_length_x_(focal_length_x), + focal_length_y_(focal_length_y), + principal_point_x_(principal_point_x), + principal_point_y_(principal_point_y), + image_width_(image_width), + image_height_(image_height), + k1_(k1), + k2_(k2), + expected_normalized_x_(expected_normalized_x), + expected_normalized_y_(expected_normalized_y) {} + + Vec2 operator()(const Vec2& image_coordinate) const { double actual_normalized_x, actual_normalized_y; InvertNukeDistortionModel(focal_length_x_, focal_length_y_, principal_point_x_, principal_point_y_, - image_width_, image_height_, - k1_, k2_, - image_coordinate(0), image_coordinate(1), - &actual_normalized_x, &actual_normalized_y); + image_width_, + image_height_, + k1_, + k2_, + image_coordinate(0), + image_coordinate(1), + &actual_normalized_x, + &actual_normalized_y); Vec2 fx; fx << (actual_normalized_x - expected_normalized_x_), - (actual_normalized_y - expected_normalized_y_); + (actual_normalized_y - expected_normalized_y_); return fx; } double focal_length_x_; @@ -346,8 +387,8 @@ void ApplyNukeDistortionModel(const double focal_length_x, const double k2, const double normalized_x, const double normalized_y, - double *image_x, - double *image_y) { + double* image_x, + double* image_y) { // Compute the initial guess. For a camera with no distortion, this will also // be the final answer; the LM iteration will terminate immediately. Vec2 image; @@ -363,12 +404,14 @@ void ApplyNukeDistortionModel(const double focal_length_x, principal_point_y, image_width, image_height, - k1, k2, - normalized_x, normalized_y); + k1, + k2, + normalized_x, + normalized_y); Solver::SolverParameters params; Solver solver(intrinsics_cost); - /*Solver::Results results =*/ solver.minimize(params, &image); + /*Solver::Results results =*/solver.minimize(params, &image); // TODO(keir): Better error handling. diff --git a/intern/libmv/libmv/simple_pipeline/distortion_models.h b/intern/libmv/libmv/simple_pipeline/distortion_models.h index 51300477956..5fe9fee8d54 100644 --- a/intern/libmv/libmv/simple_pipeline/distortion_models.h +++ b/intern/libmv/libmv/simple_pipeline/distortion_models.h @@ -46,37 +46,37 @@ void InvertPolynomialDistortionModel(const double focal_length_x, const double p2, const double image_x, const double image_y, - double *normalized_x, - double *normalized_y); + double* normalized_x, + double* normalized_y); // Apply camera intrinsics to the normalized point to get image coordinates. // This applies the radial lens distortion to a point which is in normalized // camera coordinates (i.e. the principal point is at (0, 0)) to get image // coordinates in pixels. Templated for use with autodifferentiation. template <typename T> -inline void ApplyPolynomialDistortionModel(const T &focal_length_x, - const T &focal_length_y, - const T &principal_point_x, - const T &principal_point_y, - const T &k1, - const T &k2, - const T &k3, - const T &p1, - const T &p2, - const T &normalized_x, - const T &normalized_y, - T *image_x, - T *image_y) { +inline void ApplyPolynomialDistortionModel(const T& focal_length_x, + const T& focal_length_y, + const T& principal_point_x, + const T& principal_point_y, + const T& k1, + const T& k2, + const T& k3, + const T& p1, + const T& p2, + const T& normalized_x, + const T& normalized_y, + T* image_x, + T* image_y) { T x = normalized_x; T y = normalized_y; // Apply distortion to the normalized points to get (xd, yd). - T r2 = x*x + y*y; + T r2 = x * x + y * y; T r4 = r2 * r2; T r6 = r4 * r2; - T r_coeff = (T(1) + k1*r2 + k2*r4 + k3*r6); - T xd = x * r_coeff + T(2)*p1*x*y + p2*(r2 + T(2)*x*x); - T yd = y * r_coeff + T(2)*p2*x*y + p1*(r2 + T(2)*y*y); + T r_coeff = (T(1) + k1 * r2 + k2 * r4 + k3 * r6); + T xd = x * r_coeff + T(2) * p1 * x * y + p2 * (r2 + T(2) * x * x); + T yd = y * r_coeff + T(2) * p2 * x * y + p1 * (r2 + T(2) * y * y); // Apply focal length and principal point to get the final image coordinates. *image_x = focal_length_x * xd + principal_point_x; @@ -96,8 +96,8 @@ void InvertDivisionDistortionModel(const double focal_length_x, const double k2, const double image_x, const double image_y, - double *normalized_x, - double *normalized_y); + double* normalized_x, + double* normalized_y); // Apply camera intrinsics to the normalized point to get image coordinates. // This applies the radial lens distortion to a point which is in normalized @@ -106,20 +106,19 @@ void InvertDivisionDistortionModel(const double focal_length_x, // // Uses division distortion model. template <typename T> -inline void ApplyDivisionDistortionModel(const T &focal_length_x, - const T &focal_length_y, - const T &principal_point_x, - const T &principal_point_y, - const T &k1, - const T &k2, - const T &normalized_x, - const T &normalized_y, - T *image_x, - T *image_y) { - +inline void ApplyDivisionDistortionModel(const T& focal_length_x, + const T& focal_length_y, + const T& principal_point_x, + const T& principal_point_y, + const T& k1, + const T& k2, + const T& normalized_x, + const T& normalized_y, + T* image_x, + T* image_y) { T x = normalized_x; T y = normalized_y; - T r2 = x*x + y*y; + T r2 = x * x + y * y; T r4 = r2 * r2; T xd = x / (T(1) + k1 * r2 + k2 * r4); @@ -136,18 +135,18 @@ inline void ApplyDivisionDistortionModel(const T &focal_length_x, // // Uses Nuke distortion model. template <typename T> -void InvertNukeDistortionModel(const T &focal_length_x, - const T &focal_length_y, - const T &principal_point_x, - const T &principal_point_y, +void InvertNukeDistortionModel(const T& focal_length_x, + const T& focal_length_y, + const T& principal_point_x, + const T& principal_point_y, const int image_width, const int image_height, - const T &k1, - const T &k2, - const T &image_x, - const T &image_y, - T *normalized_x, - T *normalized_y) { + const T& k1, + const T& k2, + const T& image_x, + const T& image_y, + T* normalized_x, + T* normalized_y) { // According to the documentation: // // xu = xd / (1 + k0 * rd^2 + k1 * rd^4) @@ -174,9 +173,9 @@ void InvertNukeDistortionModel(const T &focal_length_x, const T xd = (image_x - principal_point_x) / max_half_image_size; const T yd = (image_y - principal_point_y) / max_half_image_size; - T rd2 = xd*xd + yd*yd; + T rd2 = xd * xd + yd * yd; T rd4 = rd2 * rd2; - T r_coeff = T(1) / (T(1) + k1*rd2 + k2*rd4); + T r_coeff = T(1) / (T(1) + k1 * rd2 + k2 * rd4); T xu = xd * r_coeff; T yu = yd * r_coeff; @@ -200,8 +199,8 @@ void ApplyNukeDistortionModel(const double focal_length_x, const double k2, const double normalized_x, const double normalized_y, - double *image_x, - double *image_y); + double* image_x, + double* image_y); // Invert camera intrinsics on the image point to get normalized coordinates. // This inverts the radial lens distortion to a point which is in image pixel @@ -218,24 +217,24 @@ void InvertBrownDistortionModel(const double focal_length_x, const double p2, const double image_x, const double image_y, - double *normalized_x, - double *normalized_y); + double* normalized_x, + double* normalized_y); template <typename T> -inline void ApplyBrownDistortionModel(const T &focal_length_x, - const T &focal_length_y, - const T &principal_point_x, - const T &principal_point_y, - const T &k1, - const T &k2, - const T &k3, - const T &k4, - const T &p1, - const T &p2, - const T &normalized_x, - const T &normalized_y, - T *image_x, - T *image_y) { +inline void ApplyBrownDistortionModel(const T& focal_length_x, + const T& focal_length_y, + const T& principal_point_x, + const T& principal_point_y, + const T& k1, + const T& k2, + const T& k3, + const T& k4, + const T& p1, + const T& p2, + const T& normalized_x, + const T& normalized_y, + T* image_x, + T* image_y) { T x = normalized_x; T y = normalized_y; @@ -253,8 +252,8 @@ inline void ApplyBrownDistortionModel(const T &focal_length_x, // Apply focal length and principal point to get the final image coordinates. *image_x = focal_length_x * xd + principal_point_x; *image_y = focal_length_y * yd + principal_point_y; -} // namespace libmv +} // namespace libmv -} +} // namespace libmv #endif // LIBMV_SIMPLE_PIPELINE_DISTORTION_MODELS_H_ diff --git a/intern/libmv/libmv/simple_pipeline/initialize_reconstruction.cc b/intern/libmv/libmv/simple_pipeline/initialize_reconstruction.cc index 7a086c375d5..10ad0929007 100644 --- a/intern/libmv/libmv/simple_pipeline/initialize_reconstruction.cc +++ b/intern/libmv/libmv/simple_pipeline/initialize_reconstruction.cc @@ -32,8 +32,9 @@ namespace libmv { namespace { -void GetImagesInMarkers(const vector<Marker> &markers, - int *image1, int *image2) { +void GetImagesInMarkers(const vector<Marker>& markers, + int* image1, + int* image2) { if (markers.size() < 2) { return; } @@ -50,10 +51,11 @@ void GetImagesInMarkers(const vector<Marker> &markers, } // namespace -bool EuclideanReconstructTwoFrames(const vector<Marker> &markers, - EuclideanReconstruction *reconstruction) { +bool EuclideanReconstructTwoFrames(const vector<Marker>& markers, + EuclideanReconstruction* reconstruction) { if (markers.size() < 16) { - LG << "Not enough markers to initialize from two frames: " << markers.size(); + LG << "Not enough markers to initialize from two frames: " + << markers.size(); return false; } @@ -76,10 +78,8 @@ bool EuclideanReconstructTwoFrames(const vector<Marker> &markers, Mat3 R; Vec3 t; Mat3 K = Mat3::Identity(); - if (!MotionFromEssentialAndCorrespondence(E, - K, x1.col(0), - K, x2.col(0), - &R, &t)) { + if (!MotionFromEssentialAndCorrespondence( + E, K, x1.col(0), K, x2.col(0), &R, &t)) { LG << "Failed to compute R and t from E and K."; return false; } @@ -88,14 +88,14 @@ bool EuclideanReconstructTwoFrames(const vector<Marker> &markers, reconstruction->InsertCamera(image1, Mat3::Identity(), Vec3::Zero()); reconstruction->InsertCamera(image2, R, t); - LG << "From two frame reconstruction got:\nR:\n" << R - << "\nt:" << t.transpose(); + LG << "From two frame reconstruction got:\nR:\n" + << R << "\nt:" << t.transpose(); return true; } namespace { -Mat3 DecodeF(const Vec9 &encoded_F) { +Mat3 DecodeF(const Vec9& encoded_F) { // Decode F and force it to be rank 2. Map<const Mat3> full_rank_F(encoded_F.data(), 3, 3); Eigen::JacobiSVD<Mat3> svd(full_rank_F, @@ -110,22 +110,22 @@ Mat3 DecodeF(const Vec9 &encoded_F) { // doing a full SVD of F at each iteration. This uses sampson error. struct FundamentalSampsonCostFunction { public: - typedef Vec FMatrixType; + typedef Vec FMatrixType; typedef Vec9 XMatrixType; // Assumes markers are ordered by track. - explicit FundamentalSampsonCostFunction(const vector<Marker> &markers) - : markers(markers) {} + explicit FundamentalSampsonCostFunction(const vector<Marker>& markers) + : markers(markers) {} - Vec operator()(const Vec9 &encoded_F) const { + Vec operator()(const Vec9& encoded_F) const { // Decode F and force it to be rank 2. Mat3 F = DecodeF(encoded_F); Vec residuals(markers.size() / 2); residuals.setZero(); for (int i = 0; i < markers.size() / 2; ++i) { - const Marker &marker1 = markers[2*i + 0]; - const Marker &marker2 = markers[2*i + 1]; + const Marker& marker1 = markers[2 * i + 0]; + const Marker& marker2 = markers[2 * i + 1]; CHECK_EQ(marker1.track, marker2.track); Vec2 x1(marker1.x, marker1.y); Vec2 x2(marker2.x, marker2.y); @@ -134,13 +134,13 @@ struct FundamentalSampsonCostFunction { } return residuals; } - const vector<Marker> &markers; + const vector<Marker>& markers; }; } // namespace -bool ProjectiveReconstructTwoFrames(const vector<Marker> &markers, - ProjectiveReconstruction *reconstruction) { +bool ProjectiveReconstructTwoFrames(const vector<Marker>& markers, + ProjectiveReconstruction* reconstruction) { if (markers.size() < 16) { return false; } diff --git a/intern/libmv/libmv/simple_pipeline/initialize_reconstruction.h b/intern/libmv/libmv/simple_pipeline/initialize_reconstruction.h index 32cd4285190..354db14971f 100644 --- a/intern/libmv/libmv/simple_pipeline/initialize_reconstruction.h +++ b/intern/libmv/libmv/simple_pipeline/initialize_reconstruction.h @@ -37,18 +37,19 @@ class ProjectiveReconstruction; tracks visible in both frames. The pose estimation of the camera for these frames will be inserted into \a *reconstruction. - \note The two frames need to have both enough parallax and enough common tracks - for accurate reconstruction. At least 8 tracks are suggested. - \note The origin of the coordinate system is defined to be the camera of - the first keyframe. - \note This assumes a calibrated reconstruction, e.g. the markers are - already corrected for camera intrinsics and radial distortion. + \note The two frames need to have both enough parallax and enough common + tracks for accurate reconstruction. At least 8 tracks are suggested. + \note The origin of the coordinate system is defined to be the camera of the + first keyframe. + \note This assumes a calibrated reconstruction, e.g. the + markers are already corrected for camera intrinsics and radial + distortion. \note This assumes an outlier-free set of markers. \sa EuclideanResect, EuclideanIntersect, EuclideanBundle */ -bool EuclideanReconstructTwoFrames(const vector<Marker> &markers, - EuclideanReconstruction *reconstruction); +bool EuclideanReconstructTwoFrames(const vector<Marker>& markers, + EuclideanReconstruction* reconstruction); /*! Initialize the \link ProjectiveReconstruction reconstruction \endlink using @@ -58,17 +59,17 @@ bool EuclideanReconstructTwoFrames(const vector<Marker> &markers, tracks visible in both frames. An estimate of the projection matrices for the two frames will get added to the reconstruction. - \note The two frames need to have both enough parallax and enough common tracks - for accurate reconstruction. At least 8 tracks are suggested. - \note The origin of the coordinate system is defined to be the camera of - the first keyframe. + \note The two frames need to have both enough parallax and enough common + tracks for accurate reconstruction. At least 8 tracks are suggested. + \note The origin of the coordinate system is defined to be the camera of the + first keyframe. \note This assumes the markers are already corrected for radial distortion. \note This assumes an outlier-free set of markers. \sa ProjectiveResect, ProjectiveIntersect, ProjectiveBundle */ -bool ProjectiveReconstructTwoFrames(const vector<Marker> &markers, - ProjectiveReconstruction *reconstruction); +bool ProjectiveReconstructTwoFrames(const vector<Marker>& markers, + ProjectiveReconstruction* reconstruction); } // namespace libmv #endif // LIBMV_SIMPLE_PIPELINE_INITIALIZE_RECONSTRUCTION_H diff --git a/intern/libmv/libmv/simple_pipeline/intersect.cc b/intern/libmv/libmv/simple_pipeline/intersect.cc index ddb713684a4..86efd26f778 100644 --- a/intern/libmv/libmv/simple_pipeline/intersect.cc +++ b/intern/libmv/libmv/simple_pipeline/intersect.cc @@ -22,11 +22,11 @@ #include "libmv/base/vector.h" #include "libmv/logging/logging.h" +#include "libmv/multiview/nviewtriangulation.h" #include "libmv/multiview/projection.h" #include "libmv/multiview/triangulation.h" -#include "libmv/multiview/nviewtriangulation.h" -#include "libmv/numeric/numeric.h" #include "libmv/numeric/levenberg_marquardt.h" +#include "libmv/numeric/numeric.h" #include "libmv/simple_pipeline/reconstruction.h" #include "libmv/simple_pipeline/tracks.h" @@ -38,12 +38,12 @@ namespace { class EuclideanIntersectCostFunctor { public: - EuclideanIntersectCostFunctor(const Marker &marker, - const EuclideanCamera &camera) + EuclideanIntersectCostFunctor(const Marker& marker, + const EuclideanCamera& camera) : marker_(marker), camera_(camera) {} - template<typename T> - bool operator()(const T *X, T *residuals) const { + template <typename T> + bool operator()(const T* X, T* residuals) const { typedef Eigen::Matrix<T, 3, 3> Mat3; typedef Eigen::Matrix<T, 3, 1> Vec3; @@ -60,14 +60,14 @@ class EuclideanIntersectCostFunctor { return true; } - const Marker &marker_; - const EuclideanCamera &camera_; + const Marker& marker_; + const EuclideanCamera& camera_; }; } // namespace -bool EuclideanIntersect(const vector<Marker> &markers, - EuclideanReconstruction *reconstruction) { +bool EuclideanIntersect(const vector<Marker>& markers, + EuclideanReconstruction* reconstruction) { if (markers.size() < 2) { return false; } @@ -78,7 +78,7 @@ bool EuclideanIntersect(const vector<Marker> &markers, vector<Mat34> cameras; Mat34 P; for (int i = 0; i < markers.size(); ++i) { - EuclideanCamera *camera = reconstruction->CameraForImage(markers[i].image); + EuclideanCamera* camera = reconstruction->CameraForImage(markers[i].image); P_From_KRt(K, camera->R, camera->t, &P); cameras.push_back(P); } @@ -103,19 +103,19 @@ bool EuclideanIntersect(const vector<Marker> &markers, // Add residual blocks to the problem. int num_residuals = 0; for (int i = 0; i < markers.size(); ++i) { - const Marker &marker = markers[i]; + const Marker& marker = markers[i]; if (marker.weight != 0.0) { - const EuclideanCamera &camera = + const EuclideanCamera& camera = *reconstruction->CameraForImage(marker.image); problem.AddResidualBlock( - new ceres::AutoDiffCostFunction< - EuclideanIntersectCostFunctor, - 2, /* num_residuals */ - 3>(new EuclideanIntersectCostFunctor(marker, camera)), + new ceres::AutoDiffCostFunction<EuclideanIntersectCostFunctor, + 2, /* num_residuals */ + 3>( + new EuclideanIntersectCostFunctor(marker, camera)), NULL, &X(0)); - num_residuals++; + num_residuals++; } } @@ -126,9 +126,9 @@ bool EuclideanIntersect(const vector<Marker> &markers, if (!num_residuals) { LG << "Skipping running minimizer with zero residuals"; - // We still add 3D point for the track regardless it was - // optimized or not. If track is a constant zero it'll use - // algebraic intersection result as a 3D coordinate. + // We still add 3D point for the track regardless it was + // optimized or not. If track is a constant zero it'll use + // algebraic intersection result as a 3D coordinate. Vec3 point = X.head<3>(); reconstruction->InsertPoint(markers[0].track, point); @@ -152,12 +152,12 @@ bool EuclideanIntersect(const vector<Marker> &markers, // Try projecting the point; make sure it's in front of everyone. for (int i = 0; i < cameras.size(); ++i) { - const EuclideanCamera &camera = + const EuclideanCamera& camera = *reconstruction->CameraForImage(markers[i].image); Vec3 x = camera.R * X + camera.t; if (x(2) < 0) { - LOG(ERROR) << "POINT BEHIND CAMERA " << markers[i].image - << ": " << x.transpose(); + LOG(ERROR) << "POINT BEHIND CAMERA " << markers[i].image << ": " + << x.transpose(); return false; } } @@ -173,35 +173,35 @@ namespace { struct ProjectiveIntersectCostFunction { public: - typedef Vec FMatrixType; + typedef Vec FMatrixType; typedef Vec4 XMatrixType; ProjectiveIntersectCostFunction( - const vector<Marker> &markers, - const ProjectiveReconstruction &reconstruction) - : markers(markers), reconstruction(reconstruction) {} + const vector<Marker>& markers, + const ProjectiveReconstruction& reconstruction) + : markers(markers), reconstruction(reconstruction) {} - Vec operator()(const Vec4 &X) const { + Vec operator()(const Vec4& X) const { Vec residuals(2 * markers.size()); residuals.setZero(); for (int i = 0; i < markers.size(); ++i) { - const ProjectiveCamera &camera = + const ProjectiveCamera& camera = *reconstruction.CameraForImage(markers[i].image); Vec3 projected = camera.P * X; projected /= projected(2); - residuals[2*i + 0] = projected(0) - markers[i].x; - residuals[2*i + 1] = projected(1) - markers[i].y; + residuals[2 * i + 0] = projected(0) - markers[i].x; + residuals[2 * i + 1] = projected(1) - markers[i].y; } return residuals; } - const vector<Marker> &markers; - const ProjectiveReconstruction &reconstruction; + const vector<Marker>& markers; + const ProjectiveReconstruction& reconstruction; }; } // namespace -bool ProjectiveIntersect(const vector<Marker> &markers, - ProjectiveReconstruction *reconstruction) { +bool ProjectiveIntersect(const vector<Marker>& markers, + ProjectiveReconstruction* reconstruction) { if (markers.size() < 2) { return false; } @@ -209,7 +209,7 @@ bool ProjectiveIntersect(const vector<Marker> &markers, // Get the cameras to use for the intersection. vector<Mat34> cameras; for (int i = 0; i < markers.size(); ++i) { - ProjectiveCamera *camera = reconstruction->CameraForImage(markers[i].image); + ProjectiveCamera* camera = reconstruction->CameraForImage(markers[i].image); cameras.push_back(camera->P); } @@ -232,16 +232,16 @@ bool ProjectiveIntersect(const vector<Marker> &markers, Solver solver(triangulate_cost); Solver::Results results = solver.minimize(params, &X); - (void) results; // TODO(keir): Ensure results are good. + (void)results; // TODO(keir): Ensure results are good. // Try projecting the point; make sure it's in front of everyone. for (int i = 0; i < cameras.size(); ++i) { - const ProjectiveCamera &camera = + const ProjectiveCamera& camera = *reconstruction->CameraForImage(markers[i].image); Vec3 x = camera.P * X; if (x(2) < 0) { - LOG(ERROR) << "POINT BEHIND CAMERA " << markers[i].image - << ": " << x.transpose(); + LOG(ERROR) << "POINT BEHIND CAMERA " << markers[i].image << ": " + << x.transpose(); } } diff --git a/intern/libmv/libmv/simple_pipeline/intersect.h b/intern/libmv/libmv/simple_pipeline/intersect.h index 15d6f998557..aff3ffe66e2 100644 --- a/intern/libmv/libmv/simple_pipeline/intersect.h +++ b/intern/libmv/libmv/simple_pipeline/intersect.h @@ -22,8 +22,8 @@ #define LIBMV_SIMPLE_PIPELINE_INTERSECT_H #include "libmv/base/vector.h" -#include "libmv/simple_pipeline/tracks.h" #include "libmv/simple_pipeline/reconstruction.h" +#include "libmv/simple_pipeline/tracks.h" namespace libmv { @@ -38,7 +38,8 @@ namespace libmv { \a markers should contain all \link Marker markers \endlink belonging to tracks visible in all frames. \a reconstruction should contain the cameras for all frames. - The new \link Point points \endlink will be inserted in \a reconstruction. + The new \link Point points \endlink will be inserted in \a + reconstruction. \note This assumes a calibrated reconstruction, e.g. the markers are already corrected for camera intrinsics and radial distortion. @@ -46,8 +47,8 @@ namespace libmv { \sa EuclideanResect */ -bool EuclideanIntersect(const vector<Marker> &markers, - EuclideanReconstruction *reconstruction); +bool EuclideanIntersect(const vector<Marker>& markers, + EuclideanReconstruction* reconstruction); /*! Estimate the homogeneous coordinates of a track by intersecting rays. @@ -60,7 +61,8 @@ bool EuclideanIntersect(const vector<Marker> &markers, \a markers should contain all \link Marker markers \endlink belonging to tracks visible in all frames. \a reconstruction should contain the cameras for all frames. - The new \link Point points \endlink will be inserted in \a reconstruction. + The new \link Point points \endlink will be inserted in \a + reconstruction. \note This assumes that radial distortion is already corrected for, but does not assume that e.g. focal length and principal point are @@ -69,8 +71,8 @@ bool EuclideanIntersect(const vector<Marker> &markers, \sa Resect */ -bool ProjectiveIntersect(const vector<Marker> &markers, - ProjectiveReconstruction *reconstruction); +bool ProjectiveIntersect(const vector<Marker>& markers, + ProjectiveReconstruction* reconstruction); } // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/intersect_test.cc b/intern/libmv/libmv/simple_pipeline/intersect_test.cc index dd4fdc789af..447cc095cb0 100644 --- a/intern/libmv/libmv/simple_pipeline/intersect_test.cc +++ b/intern/libmv/libmv/simple_pipeline/intersect_test.cc @@ -22,10 +22,10 @@ #include <iostream> -#include "testing/testing.h" +#include "libmv/logging/logging.h" #include "libmv/multiview/projection.h" #include "libmv/numeric/numeric.h" -#include "libmv/logging/logging.h" +#include "testing/testing.h" namespace libmv { @@ -40,13 +40,15 @@ TEST(Intersect, EuclideanIntersect) { // 0, 0, 1; Mat3 R1 = RotationAroundZ(-0.1); Mat3 R2 = RotationAroundX(-0.1); - Vec3 t1; t1 << 1, 1, 10; - Vec3 t2; t2 << -2, -1, 10; + Vec3 t1; + t1 << 1, 1, 10; + Vec3 t2; + t2 << -2, -1, 10; Mat34 P1, P2; P_From_KRt(K1, R1, t1, &P1); P_From_KRt(K2, R2, t2, &P2); - //Mat3 F; FundamentalFromProjections(P1, P2, &F); + // Mat3 F; FundamentalFromProjections(P1, P2, &F); Mat3X X; X.resize(3, 30); @@ -68,9 +70,9 @@ TEST(Intersect, EuclideanIntersect) { reconstruction.InsertCamera(2, R2, t2); vector<Marker> markers; - Marker a = { 1, 0, x1.x(), x1.y(), 1.0 }; + Marker a = {1, 0, x1.x(), x1.y(), 1.0}; markers.push_back(a); - Marker b = { 2, 0, x2.x(), x2.y(), 1.0 }; + Marker b = {2, 0, x2.x(), x2.y(), 1.0}; markers.push_back(b); EuclideanIntersect(markers, &reconstruction); @@ -78,4 +80,4 @@ TEST(Intersect, EuclideanIntersect) { EXPECT_NEAR(0, DistanceLInfinity(estimated, expected), 1e-8); } } -} // namespace +} // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/keyframe_selection.cc b/intern/libmv/libmv/simple_pipeline/keyframe_selection.cc index 241b5600505..5526d730651 100644 --- a/intern/libmv/libmv/simple_pipeline/keyframe_selection.cc +++ b/intern/libmv/libmv/simple_pipeline/keyframe_selection.cc @@ -20,20 +20,20 @@ #include "libmv/simple_pipeline/keyframe_selection.h" -#include "libmv/numeric/numeric.h" #include "ceres/ceres.h" #include "libmv/logging/logging.h" -#include "libmv/multiview/homography.h" #include "libmv/multiview/fundamental.h" -#include "libmv/simple_pipeline/intersect.h" +#include "libmv/multiview/homography.h" +#include "libmv/numeric/numeric.h" #include "libmv/simple_pipeline/bundle.h" +#include "libmv/simple_pipeline/intersect.h" #include <Eigen/Eigenvalues> namespace libmv { namespace { -Mat3 IntrinsicsNormalizationMatrix(const CameraIntrinsics &intrinsics) { +Mat3 IntrinsicsNormalizationMatrix(const CameraIntrinsics& intrinsics) { Mat3 T = Mat3::Identity(), S = Mat3::Identity(); T(0, 2) = -intrinsics.principal_point_x(); @@ -56,7 +56,7 @@ Mat3 IntrinsicsNormalizationMatrix(const CameraIntrinsics &intrinsics) { // (k = 7 for a fundamental matrix or 8 for a homography) // r is the dimension of the data // (r = 4 for 2D correspondences between two frames) -double GRIC(const Vec &e, int d, int k, int r) { +double GRIC(const Vec& e, int d, int k, int r) { int n = e.rows(); double lambda1 = log(static_cast<double>(r)); double lambda2 = log(static_cast<double>(r * n)); @@ -89,7 +89,7 @@ double GRIC(const Vec &e, int d, int k, int r) { // // TODO(keir): Consider moving this into the numeric code, since this is not // related to keyframe selection. -Mat PseudoInverseWithClampedEigenvalues(const Mat &matrix, +Mat PseudoInverseWithClampedEigenvalues(const Mat& matrix, int num_eigenvalues_to_clamp) { Eigen::EigenSolver<Mat> eigen_solver(matrix); Mat D = eigen_solver.pseudoEigenvalueMatrix(); @@ -112,27 +112,24 @@ Mat PseudoInverseWithClampedEigenvalues(const Mat &matrix, return V * D * V.inverse(); } -void FilterZeroWeightMarkersFromTracks(const Tracks &tracks, - Tracks *filtered_tracks) { +void FilterZeroWeightMarkersFromTracks(const Tracks& tracks, + Tracks* filtered_tracks) { vector<Marker> all_markers = tracks.AllMarkers(); for (int i = 0; i < all_markers.size(); ++i) { - Marker &marker = all_markers[i]; + Marker& marker = all_markers[i]; if (marker.weight != 0.0) { - filtered_tracks->Insert(marker.image, - marker.track, - marker.x, - marker.y, - marker.weight); + filtered_tracks->Insert( + marker.image, marker.track, marker.x, marker.y, marker.weight); } } } } // namespace -void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, - const CameraIntrinsics &intrinsics, - vector<int> &keyframes) { +void SelectKeyframesBasedOnGRICAndVariance(const Tracks& _tracks, + const CameraIntrinsics& intrinsics, + vector<int>& keyframes) { // Mirza Tahir Ahmed, Matthew N. Dailey // Robust key frame extraction for 3D reconstruction from video streams // @@ -172,23 +169,21 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, candidate_image <= max_image; candidate_image++) { // Conjunction of all markers from both keyframes - vector<Marker> all_markers = - filtered_tracks.MarkersInBothImages(current_keyframe, - candidate_image); + vector<Marker> all_markers = filtered_tracks.MarkersInBothImages( + current_keyframe, candidate_image); // Match keypoints between frames current_keyframe and candidate_image vector<Marker> tracked_markers = - filtered_tracks.MarkersForTracksInBothImages(current_keyframe, - candidate_image); + filtered_tracks.MarkersForTracksInBothImages(current_keyframe, + candidate_image); // Correspondences in normalized space Mat x1, x2; CoordinatesForMarkersInImage(tracked_markers, current_keyframe, &x1); CoordinatesForMarkersInImage(tracked_markers, candidate_image, &x2); - LG << "Found " << x1.cols() - << " correspondences between " << current_keyframe - << " and " << candidate_image; + LG << "Found " << x1.cols() << " correspondences between " + << current_keyframe << " and " << candidate_image; // Not enough points to construct fundamental matrix if (x1.cols() < 8 || x2.cols() < 8) @@ -199,9 +194,8 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, int Tf = all_markers.size(); double Rc = static_cast<double>(Tc) / Tf; - LG << "Correspondence between " << current_keyframe - << " and " << candidate_image - << ": " << Rc; + LG << "Correspondence between " << current_keyframe << " and " + << candidate_image << ": " << Rc; if (Rc < Tmin || Rc > Tmax) continue; @@ -210,19 +204,15 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, // Estimate homography using default options. EstimateHomographyOptions estimate_homography_options; - EstimateHomography2DFromCorrespondences(x1, - x2, - estimate_homography_options, - &H); + EstimateHomography2DFromCorrespondences( + x1, x2, estimate_homography_options, &H); // Convert homography to original pixel space. H = N_inverse * H * N; EstimateFundamentalOptions estimate_fundamental_options; - EstimateFundamentalFromCorrespondences(x1, - x2, - estimate_fundamental_options, - &F); + EstimateFundamentalFromCorrespondences( + x1, x2, estimate_fundamental_options, &F); // Convert fundamental to original pixel space. F = N_inverse * F * N; @@ -238,11 +228,11 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, for (int i = 0; i < x1.cols(); i++) { Vec2 current_x1, current_x2; - intrinsics.NormalizedToImageSpace(x1(0, i), x1(1, i), - ¤t_x1(0), ¤t_x1(1)); + intrinsics.NormalizedToImageSpace( + x1(0, i), x1(1, i), ¤t_x1(0), ¤t_x1(1)); - intrinsics.NormalizedToImageSpace(x2(0, i), x2(1, i), - ¤t_x2(0), ¤t_x2(1)); + intrinsics.NormalizedToImageSpace( + x2(0, i), x2(1, i), ¤t_x2(0), ¤t_x2(1)); H_e(i) = SymmetricGeometricDistance(H, current_x1, current_x2); F_e(i) = SymmetricEpipolarDistance(F, current_x1, current_x2); @@ -255,10 +245,8 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, double GRIC_H = GRIC(H_e, 2, 8, 4); double GRIC_F = GRIC(F_e, 3, 7, 4); - LG << "GRIC values for frames " << current_keyframe - << " and " << candidate_image - << ", H-GRIC: " << GRIC_H - << ", F-GRIC: " << GRIC_F; + LG << "GRIC values for frames " << current_keyframe << " and " + << candidate_image << ", H-GRIC: " << GRIC_H << ", F-GRIC: " << GRIC_F; if (GRIC_H <= GRIC_F) continue; @@ -295,23 +283,19 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, Vec3 t; Mat3 K = Mat3::Identity(); - if (!MotionFromEssentialAndCorrespondence(E, - K, x1.col(0), - K, x2.col(0), - &R, &t)) { + if (!MotionFromEssentialAndCorrespondence( + E, K, x1.col(0), K, x2.col(0), &R, &t)) { LG << "Failed to compute R and t from E and K"; continue; } - LG << "Camera transform between frames " << current_keyframe - << " and " << candidate_image - << ":\nR:\n" << R - << "\nt:" << t.transpose(); + LG << "Camera transform between frames " << current_keyframe << " and " + << candidate_image << ":\nR:\n" + << R << "\nt:" << t.transpose(); // First camera is identity, second one is relative to it - reconstruction.InsertCamera(current_keyframe, - Mat3::Identity(), - Vec3::Zero()); + reconstruction.InsertCamera( + current_keyframe, Mat3::Identity(), Vec3::Zero()); reconstruction.InsertCamera(candidate_image, R, t); // Reconstruct 3D points @@ -349,7 +333,7 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, } double success_intersects_factor = - (double) intersects_success / intersects_total; + (double)intersects_success / intersects_total; if (success_intersects_factor < success_intersects_factor_best) { LG << "Skip keyframe candidate because of " @@ -372,7 +356,7 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, &empty_intrinsics, &evaluation); - Mat &jacobian = evaluation.jacobian; + Mat& jacobian = evaluation.jacobian; Mat JT_J = jacobian.transpose() * jacobian; // There are 7 degrees of freedom, so clamp them out. @@ -380,10 +364,10 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, Mat temp_derived = JT_J * JT_J_inv * JT_J; bool is_inversed = (temp_derived - JT_J).cwiseAbs2().sum() < - 1e-4 * std::min(temp_derived.cwiseAbs2().sum(), - JT_J.cwiseAbs2().sum()); + 1e-4 * std::min(temp_derived.cwiseAbs2().sum(), + JT_J.cwiseAbs2().sum()); - LG << "Check on inversed: " << (is_inversed ? "true" : "false" ) + LG << "Check on inversed: " << (is_inversed ? "true" : "false") << ", det(JT_J): " << JT_J.determinant(); if (!is_inversed) { @@ -400,8 +384,7 @@ void SelectKeyframesBasedOnGRICAndVariance(const Tracks &_tracks, double Sc = static_cast<double>(I + A) / Square(3 * I) * Sigma_P.trace(); - LG << "Expected estimation error between " - << current_keyframe << " and " + LG << "Expected estimation error between " << current_keyframe << " and " << candidate_image << ": " << Sc; // Pairing with a lower Sc indicates a better choice diff --git a/intern/libmv/libmv/simple_pipeline/keyframe_selection.h b/intern/libmv/libmv/simple_pipeline/keyframe_selection.h index 25253af32fe..a1b3910abd4 100644 --- a/intern/libmv/libmv/simple_pipeline/keyframe_selection.h +++ b/intern/libmv/libmv/simple_pipeline/keyframe_selection.h @@ -22,8 +22,8 @@ #define LIBMV_SIMPLE_PIPELINE_KEYFRAME_SELECTION_H_ #include "libmv/base/vector.h" -#include "libmv/simple_pipeline/tracks.h" #include "libmv/simple_pipeline/camera_intrinsics.h" +#include "libmv/simple_pipeline/tracks.h" namespace libmv { @@ -43,10 +43,9 @@ namespace libmv { // \param intrinsics: is camera intrinsics. // \param keyframes: will contain all images number which are considered // good to be used for reconstruction. -void SelectKeyframesBasedOnGRICAndVariance( - const Tracks &tracks, - const CameraIntrinsics &intrinsics, - vector<int> &keyframes); +void SelectKeyframesBasedOnGRICAndVariance(const Tracks& tracks, + const CameraIntrinsics& intrinsics, + vector<int>& keyframes); } // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/keyframe_selection_test.cc b/intern/libmv/libmv/simple_pipeline/keyframe_selection_test.cc index 9d88362cc88..983349c0c5a 100644 --- a/intern/libmv/libmv/simple_pipeline/keyframe_selection_test.cc +++ b/intern/libmv/libmv/simple_pipeline/keyframe_selection_test.cc @@ -1,15 +1,15 @@ // Copyright (c) 2011 libmv authors. -// +// // Permission is hereby granted, free of charge, to any person obtaining a copy // of this software and associated documentation files (the "Software"), to // deal in the Software without restriction, including without limitation the // rights to use, copy, modify, merge, publish, distribute, sublicense, and/or // sell copies of the Software, and to permit persons to whom the Software is // furnished to do so, subject to the following conditions: -// +// // The above copyright notice and this permission notice shall be included in // all copies or substantial portions of the Software. -// +// // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR // IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, // FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE @@ -20,9 +20,9 @@ #include "libmv/simple_pipeline/keyframe_selection.h" -#include "testing/testing.h" -#include "libmv/simple_pipeline/camera_intrinsics.h" #include "libmv/logging/logging.h" +#include "libmv/simple_pipeline/camera_intrinsics.h" +#include "testing/testing.h" namespace libmv { @@ -30,7 +30,7 @@ namespace libmv { // Should not be keyframe TEST(KeyframeSelection, SyntheticNeighborFrame) { PolynomialCameraIntrinsics intrinsics; - intrinsics.SetFocalLength(900.0,900.0); + intrinsics.SetFocalLength(900.0, 900.0); intrinsics.SetPrincipalPoint(640.0, 540.0); intrinsics.SetRadialDistortion(0.0, 0.0, 0.0); @@ -66,25 +66,56 @@ TEST(KeyframeSelection, FabrikEingangNeighborFrames) { intrinsics.SetPrincipalPoint(960.000, 544.000); intrinsics.SetRadialDistortion(0.0, 0.0, 0.0); - Marker markers[] = { - {1, 0, 737.599983, 646.397594, 1.0}, {2, 0, 737.906628, 648.113327, 1.0}, {1, 1, 863.045425, 646.081905, 1.0}, - {2, 1, 863.339767, 647.650040, 1.0}, {1, 2, 736.959972, 574.080151, 1.0}, {2, 2, 737.217350, 575.604900, 1.0}, - {1, 3, 864.097424, 573.374908, 1.0}, {2, 3, 864.383469, 574.900307, 1.0}, {1, 4, 789.429073, 631.677521, 1.0}, - {2, 4, 789.893131, 633.124451, 1.0}, {1, 5, 791.051960, 573.442028, 1.0}, {2, 5, 791.336575, 575.088890, 1.0}, - {1, 6, 738.973961, 485.130308, 1.0}, {2, 6, 739.435501, 486.734207, 1.0}, {1, 7, 862.403240, 514.866074, 1.0}, - {2, 7, 862.660618, 516.413261, 1.0}, {1, 8, 802.240162, 485.759838, 1.0}, {2, 8, 802.602253, 487.432899, 1.0}, - {1, 9, 754.340630, 500.624559, 1.0}, {2, 9, 754.559956, 502.079920, 1.0}, {1, 10, 849.398689, 484.480545, 1.0}, - {2, 10, 849.599934, 486.079937, 1.0}, {1, 11, 788.803768, 515.924391, 1.0}, {2, 11, 789.119911, 517.439932, 1.0}, - {1, 12, 838.733940, 558.212688, 1.0}, {2, 12, 839.039898, 559.679916, 1.0}, {1, 13, 760.014782, 575.194466, 1.0}, - {2, 13, 760.319881, 576.639904, 1.0}, {1, 14, 765.321636, 616.015957, 1.0}, {2, 14, 765.759945, 617.599915, 1.0}, - {1, 15, 800.963230, 660.032082, 1.0}, {2, 15, 801.279945, 661.759876, 1.0}, {1, 16, 846.321087, 602.313053, 1.0}, - {2, 16, 846.719913, 603.839878, 1.0}, {1, 17, 864.288311, 616.790524, 1.0}, {2, 17, 864.639931, 618.239918, 1.0}, - {1, 18, 800.006790, 602.573425, 1.0}, {2, 18, 800.319958, 604.159912, 1.0}, {1, 19, 739.026890, 617.944138, 1.0}, - {2, 19, 739.199924, 619.519924, 1.0}, {1, 20, 801.987419, 544.134888, 1.0}, {2, 20, 802.239933, 545.599911, 1.0}, - {1, 21, 753.619823, 542.961300, 1.0}, {2, 21, 753.919945, 544.639874, 1.0}, {1, 22, 787.921257, 499.910206, 1.0}, - {2, 22, 788.159924, 501.439917, 1.0}, {1, 23, 839.095459, 529.287903, 1.0}, {2, 23, 839.359932, 530.879934, 1.0}, - {1, 24, 811.760330, 630.732269, 1.0}, {2, 24, 812.159901, 632.319859, 1.0} - }; + Marker markers[] = {{1, 0, 737.599983, 646.397594, 1.0}, + {2, 0, 737.906628, 648.113327, 1.0}, + {1, 1, 863.045425, 646.081905, 1.0}, + {2, 1, 863.339767, 647.650040, 1.0}, + {1, 2, 736.959972, 574.080151, 1.0}, + {2, 2, 737.217350, 575.604900, 1.0}, + {1, 3, 864.097424, 573.374908, 1.0}, + {2, 3, 864.383469, 574.900307, 1.0}, + {1, 4, 789.429073, 631.677521, 1.0}, + {2, 4, 789.893131, 633.124451, 1.0}, + {1, 5, 791.051960, 573.442028, 1.0}, + {2, 5, 791.336575, 575.088890, 1.0}, + {1, 6, 738.973961, 485.130308, 1.0}, + {2, 6, 739.435501, 486.734207, 1.0}, + {1, 7, 862.403240, 514.866074, 1.0}, + {2, 7, 862.660618, 516.413261, 1.0}, + {1, 8, 802.240162, 485.759838, 1.0}, + {2, 8, 802.602253, 487.432899, 1.0}, + {1, 9, 754.340630, 500.624559, 1.0}, + {2, 9, 754.559956, 502.079920, 1.0}, + {1, 10, 849.398689, 484.480545, 1.0}, + {2, 10, 849.599934, 486.079937, 1.0}, + {1, 11, 788.803768, 515.924391, 1.0}, + {2, 11, 789.119911, 517.439932, 1.0}, + {1, 12, 838.733940, 558.212688, 1.0}, + {2, 12, 839.039898, 559.679916, 1.0}, + {1, 13, 760.014782, 575.194466, 1.0}, + {2, 13, 760.319881, 576.639904, 1.0}, + {1, 14, 765.321636, 616.015957, 1.0}, + {2, 14, 765.759945, 617.599915, 1.0}, + {1, 15, 800.963230, 660.032082, 1.0}, + {2, 15, 801.279945, 661.759876, 1.0}, + {1, 16, 846.321087, 602.313053, 1.0}, + {2, 16, 846.719913, 603.839878, 1.0}, + {1, 17, 864.288311, 616.790524, 1.0}, + {2, 17, 864.639931, 618.239918, 1.0}, + {1, 18, 800.006790, 602.573425, 1.0}, + {2, 18, 800.319958, 604.159912, 1.0}, + {1, 19, 739.026890, 617.944138, 1.0}, + {2, 19, 739.199924, 619.519924, 1.0}, + {1, 20, 801.987419, 544.134888, 1.0}, + {2, 20, 802.239933, 545.599911, 1.0}, + {1, 21, 753.619823, 542.961300, 1.0}, + {2, 21, 753.919945, 544.639874, 1.0}, + {1, 22, 787.921257, 499.910206, 1.0}, + {2, 22, 788.159924, 501.439917, 1.0}, + {1, 23, 839.095459, 529.287903, 1.0}, + {2, 23, 839.359932, 530.879934, 1.0}, + {1, 24, 811.760330, 630.732269, 1.0}, + {2, 24, 812.159901, 632.319859, 1.0}}; int num_markers = sizeof(markers) / sizeof(Marker); Tracks tracks; @@ -108,18 +139,34 @@ TEST(KeyframeSelection, FabrikEingangFarFrames) { intrinsics.SetPrincipalPoint(960.000, 544.000); intrinsics.SetRadialDistortion(0.0, 0.0, 0.0); - Marker markers[] = { - {1, 0, 369.459200, 619.315258, 1.0}, {2, 0, 279.677496, 722.086842, 1.0}, {1, 1, 376.831970, 370.278397, 1.0}, - {2, 1, 221.695247, 460.065418, 1.0}, {1, 2, 1209.139023, 567.705605, 1.0}, {2, 2, 1080.760117, 659.230083, 1.0}, - {1, 3, 1643.495750, 903.620453, 1.0}, {2, 3, 1618.405037, 1015.374908, 1.0}, {1, 4, 1494.849815, 425.302460, 1.0}, - {2, 4, 1457.467575, 514.727587, 1.0}, {1, 5, 1794.637299, 328.728609, 1.0}, {2, 5, 1742.161446, 408.988636, 1.0}, - {1, 6, 1672.822723, 102.240358, 1.0}, {2, 6, 1539.287224, 153.536892, 1.0}, {1, 7, 1550.843925, 53.424943, 1.0}, - {2, 7, 1385.579109, 96.450085, 1.0}, {1, 8, 852.953281, 465.399578, 1.0}, {2, 8, 779.404564, 560.091843, 1.0}, - {1, 9, 906.853752, 299.827040, 1.0}, {2, 9, 786.923218, 385.570770, 1.0}, {1, 10, 406.322966, 87.556041, 1.0}, - {2, 10, 140.339413, 150.877481, 1.0}, {1, 11, 254.811573, 851.296478, 1.0}, {2, 11, 94.478302, 969.350189, 1.0}, - {1, 12, 729.087868, 806.092758, 1.0}, {2, 12, 606.212139, 919.876560, 1.0}, {1, 13, 1525.719452, 920.398083, 1.0}, - {2, 13, 1495.579720, 1031.971218, 1.0} - }; + Marker markers[] = {{1, 0, 369.459200, 619.315258, 1.0}, + {2, 0, 279.677496, 722.086842, 1.0}, + {1, 1, 376.831970, 370.278397, 1.0}, + {2, 1, 221.695247, 460.065418, 1.0}, + {1, 2, 1209.139023, 567.705605, 1.0}, + {2, 2, 1080.760117, 659.230083, 1.0}, + {1, 3, 1643.495750, 903.620453, 1.0}, + {2, 3, 1618.405037, 1015.374908, 1.0}, + {1, 4, 1494.849815, 425.302460, 1.0}, + {2, 4, 1457.467575, 514.727587, 1.0}, + {1, 5, 1794.637299, 328.728609, 1.0}, + {2, 5, 1742.161446, 408.988636, 1.0}, + {1, 6, 1672.822723, 102.240358, 1.0}, + {2, 6, 1539.287224, 153.536892, 1.0}, + {1, 7, 1550.843925, 53.424943, 1.0}, + {2, 7, 1385.579109, 96.450085, 1.0}, + {1, 8, 852.953281, 465.399578, 1.0}, + {2, 8, 779.404564, 560.091843, 1.0}, + {1, 9, 906.853752, 299.827040, 1.0}, + {2, 9, 786.923218, 385.570770, 1.0}, + {1, 10, 406.322966, 87.556041, 1.0}, + {2, 10, 140.339413, 150.877481, 1.0}, + {1, 11, 254.811573, 851.296478, 1.0}, + {2, 11, 94.478302, 969.350189, 1.0}, + {1, 12, 729.087868, 806.092758, 1.0}, + {2, 12, 606.212139, 919.876560, 1.0}, + {1, 13, 1525.719452, 920.398083, 1.0}, + {2, 13, 1495.579720, 1031.971218, 1.0}}; int num_markers = sizeof(markers) / sizeof(Marker); Tracks tracks; @@ -144,17 +191,35 @@ TEST(KeyframeSelection, CopterManualKeyFrames) { intrinsics.SetRadialDistortion(-0.08590, 0.0, 0.0); Marker markers[] = { - {1, 0, 645.792694, 403.115931, 1.0}, {2, 0, 630.641174, 307.996409, 1.0}, {1, 1, 783.469086, 403.904328, 1.0}, - {2, 1, 766.001129, 308.998225, 1.0}, {1, 2, 650.000000, 160.000001, 1.0}, {1, 3, 785.225906, 158.619039, 1.0}, - {2, 3, 767.526474, 70.449695, 1.0}, {1, 4, 290.640526, 382.335634, 1.0}, {2, 4, 273.001728, 86.993319, 1.0}, - {1, 5, 291.162739, 410.602684, 1.0}, {2, 5, 273.287849, 111.937487, 1.0}, {1, 6, 136.919317, 349.895797, 1.0}, - {1, 7, 490.844345, 47.572222, 1.0}, {1, 8, 454.406433, 488.935761, 1.0}, {1, 9, 378.655815, 618.522248, 1.0}, - {2, 9, 357.061806, 372.265077, 1.0}, {1, 10, 496.011391, 372.668824, 1.0}, {2, 10, 477.979164, 222.986112, 1.0}, - {1, 11, 680.060272, 256.103625, 1.0}, {2, 11, 670.587540, 204.830453, 1.0}, {1, 12, 1070.817108, 218.775322, 1.0}, - {2, 12, 1046.129913, 128.969783, 1.0}, {1, 14, 242.516403, 596.048512, 1.0}, {2, 14, 224.182606, 248.272154, 1.0}, - {1, 15, 613.936272, 287.519073, 1.0}, {2, 15, 600.467644, 196.085722, 1.0}, {1, 31, 844.637451, 256.354315, 1.0}, + {1, 0, 645.792694, 403.115931, 1.0}, + {2, 0, 630.641174, 307.996409, 1.0}, + {1, 1, 783.469086, 403.904328, 1.0}, + {2, 1, 766.001129, 308.998225, 1.0}, + {1, 2, 650.000000, 160.000001, 1.0}, + {1, 3, 785.225906, 158.619039, 1.0}, + {2, 3, 767.526474, 70.449695, 1.0}, + {1, 4, 290.640526, 382.335634, 1.0}, + {2, 4, 273.001728, 86.993319, 1.0}, + {1, 5, 291.162739, 410.602684, 1.0}, + {2, 5, 273.287849, 111.937487, 1.0}, + {1, 6, 136.919317, 349.895797, 1.0}, + {1, 7, 490.844345, 47.572222, 1.0}, + {1, 8, 454.406433, 488.935761, 1.0}, + {1, 9, 378.655815, 618.522248, 1.0}, + {2, 9, 357.061806, 372.265077, 1.0}, + {1, 10, 496.011391, 372.668824, 1.0}, + {2, 10, 477.979164, 222.986112, 1.0}, + {1, 11, 680.060272, 256.103625, 1.0}, + {2, 11, 670.587540, 204.830453, 1.0}, + {1, 12, 1070.817108, 218.775322, 1.0}, + {2, 12, 1046.129913, 128.969783, 1.0}, + {1, 14, 242.516403, 596.048512, 1.0}, + {2, 14, 224.182606, 248.272154, 1.0}, + {1, 15, 613.936272, 287.519073, 1.0}, + {2, 15, 600.467644, 196.085722, 1.0}, + {1, 31, 844.637451, 256.354315, 1.0}, {2, 31, 823.200150, 165.714952, 1.0}, - }; + }; int num_markers = sizeof(markers) / sizeof(Marker); Tracks tracks; @@ -180,52 +245,140 @@ TEST(KeyframeSelection, ElevatorManualKeyframesFrames) { intrinsics.SetRadialDistortion(-0.034, 0.0, 0.0); Marker markers[] = { - {1, 2, 1139.861412, 1034.634984, 1.0}, {2, 2, 1143.512192, 1065.355718, 1.0}, {1, 3, 1760.821953, 644.658036, 1.0}, - {2, 3, 1770.901108, 697.899928, 1.0}, {1, 4, 858.071823, 1068.520746, 1.0}, {1, 6, 1633.952408, 797.050145, 1.0}, - {2, 6, 1642.508469, 849.157140, 1.0}, {1, 8, 1716.695824, 451.805491, 1.0}, {2, 8, 1726.513939, 502.095687, 1.0}, - {1, 9, 269.577627, 724.986935, 1.0}, {2, 9, 269.424820, 764.154246, 1.0}, {1, 10, 1891.321907, 706.948843, 1.0}, - {2, 10, 1903.338547, 766.068377, 1.0}, {1, 12, 1806.227074, 956.089604, 1.0}, {2, 12, 1816.619568, 1013.767376, 1.0}, - {1, 14, 269.544153, 1002.333570, 1.0}, {2, 14, 269.367542, 1043.509254, 1.0}, {1, 15, 1402.772141, 281.392962, 1.0}, - {2, 15, 1409.089165, 318.731629, 1.0}, {1, 16, 195.877233, 919.454341, 1.0}, {2, 16, 192.531109, 997.367899, 1.0}, - {1, 17, 1789.584045, 120.036661, 1.0}, {2, 17, 1800.391846, 167.822964, 1.0}, {1, 18, 999.363213, 765.004807, 1.0}, - {2, 18, 1002.345772, 790.560122, 1.0}, {1, 19, 647.342491, 1044.805727, 1.0}, {2, 19, 649.328041, 1058.682940, 1.0}, - {1, 20, 1365.486832, 440.901829, 1.0}, {2, 20, 1371.413040, 477.888730, 1.0}, {1, 21, 1787.125282, 301.431606, 1.0}, - {2, 21, 1798.527260, 355.224531, 1.0}, {1, 22, 1257.805824, 932.797258, 1.0}, {2, 22, 1263.017578, 969.376774, 1.0}, - {1, 23, 961.969528, 843.148112, 1.0}, {2, 23, 964.869461, 868.587620, 1.0}, {1, 24, 158.076110, 1052.643592, 1.0}, - {1, 25, 1072.884521, 1005.296981, 1.0}, {2, 25, 1076.091156, 1032.776856, 1.0}, {1, 26, 1107.656937, 526.577228, 1.0}, - {2, 26, 1111.618423, 555.524454, 1.0}, {1, 27, 1416.410751, 529.857581, 1.0}, {2, 27, 1422.663574, 570.025957, 1.0}, - {1, 28, 1498.673630, 1005.453086, 1.0}, {2, 28, 1505.381813, 1051.827149, 1.0}, {1, 29, 1428.647804, 652.473629, 1.0}, - {2, 29, 1434.898224, 692.715390, 1.0}, {1, 30, 1332.318764, 503.673599, 1.0}, {2, 30, 1338.000069, 540.507967, 1.0}, - {1, 32, 1358.642693, 709.837904, 1.0}, {2, 32, 1364.231529, 748.678265, 1.0}, {1, 33, 1850.911560, 460.475668, 1.0}, - {2, 33, 1862.221413, 512.797347, 1.0}, {1, 34, 1226.117821, 607.053959, 1.0}, {2, 34, 1230.736084, 641.091449, 1.0}, - {1, 35, 619.598236, 523.341744, 1.0}, {2, 35, 621.601124, 554.453287, 1.0}, {1, 36, 956.591492, 958.223183, 1.0}, - {2, 36, 959.289265, 983.289263, 1.0}, {1, 37, 1249.922218, 419.095856, 1.0}, {2, 37, 1255.005913, 452.556177, 1.0}, - {1, 39, 1300.528450, 386.251166, 1.0}, {2, 39, 1305.957413, 420.185595, 1.0}, {1, 40, 1128.689919, 972.558346, 1.0}, - {2, 40, 1132.413712, 1003.984737, 1.0}, {1, 41, 503.304749, 1053.504388, 1.0}, {2, 41, 505.019703, 1069.175613, 1.0}, - {1, 42, 1197.352982, 472.681564, 1.0}, {2, 42, 1201.910706, 503.459880, 1.0}, {1, 43, 1794.391022, 383.911400, 1.0}, - {2, 43, 1805.324135, 436.116468, 1.0}, {1, 44, 789.641418, 1058.045647, 1.0}, {1, 45, 1376.575241, 928.714979, 1.0}, - {2, 45, 1381.995850, 969.511957, 1.0}, {1, 46, 1598.023567, 93.975592, 1.0}, {2, 46, 1606.937141, 136.827035, 1.0}, - {1, 47, 1455.550232, 762.128685, 1.0}, {2, 47, 1462.014313, 805.164878, 1.0}, {1, 48, 1357.123489, 354.460326, 1.0}, - {2, 48, 1363.071899, 390.363121, 1.0}, {1, 49, 939.792652, 781.549895, 1.0}, {2, 49, 942.802620, 806.164012, 1.0}, - {1, 50, 1380.251083, 805.948620, 1.0}, {2, 50, 1385.637932, 845.592098, 1.0}, {1, 51, 1021.769943, 1049.802361, 1.0}, - {1, 52, 1065.634918, 608.099055, 1.0}, {2, 52, 1069.142189, 635.361736, 1.0}, {1, 53, 624.324188, 463.202863, 1.0}, - {2, 53, 626.395454, 494.994088, 1.0}, {1, 54, 1451.459885, 881.557624, 1.0}, {2, 54, 1457.679634, 924.345531, 1.0}, - {1, 55, 1201.885986, 1057.079022, 1.0}, {1, 56, 581.157532, 947.661438, 1.0}, {2, 56, 583.242359, 960.831449, 1.0}, - {1, 58, 513.593102, 954.175858, 1.0}, {2, 58, 515.470047, 971.309574, 1.0}, {1, 59, 928.069038, 901.774421, 1.0}, - {2, 59, 930.847950, 925.613744, 1.0}, {1, 60, 1065.860023, 740.395389, 1.0}, {2, 60, 1069.484253, 768.971086, 1.0}, - {1, 61, 990.479393, 906.264632, 1.0}, {2, 61, 993.217506, 933.088803, 1.0}, {1, 62, 1776.196747, 776.278453, 1.0}, - {2, 62, 1786.292496, 831.136880, 1.0}, {1, 63, 834.454365, 1012.449725, 1.0}, {2, 63, 836.868324, 1033.451807, 1.0}, - {1, 64, 1355.190697, 869.184809, 1.0}, {2, 64, 1360.736618, 909.773347, 1.0}, {1, 65, 702.072487, 897.519686, 1.0}, - {2, 65, 704.203377, 911.931131, 1.0}, {1, 66, 1214.022903, 856.199934, 1.0}, {2, 66, 1218.109016, 890.753052, 1.0}, - {1, 67, 327.676048, 236.814036, 1.0}, {2, 67, 328.335285, 277.251878, 1.0}, {1, 68, 289.064083, 454.793912, 1.0}, - {2, 68, 288.651924, 498.882444, 1.0}, {1, 69, 1626.240692, 278.374350, 1.0}, {2, 69, 1634.131508, 315.853672, 1.0}, - {1, 70, 1245.375710, 734.862142, 1.0}, {2, 70, 1250.047417, 769.670885, 1.0}, {1, 71, 497.015305, 510.718904, 1.0}, - {2, 71, 498.682308, 541.070201, 1.0}, {1, 72, 1280.542030, 153.939185, 1.0}, {2, 72, 1286.993637, 198.436196, 1.0}, - {1, 73, 1534.748840, 138.601043, 1.0}, {2, 73, 1542.961349, 180.170819, 1.0}, {1, 74, 1477.412682, 200.608061, 1.0}, - {2, 74, 1484.683914, 240.413260, 1.0}, {1, 76, 450.637321, 407.279642, 1.0}, {2, 76, 451.695642, 441.666291, 1.0}, - {1, 78, 246.981239, 220.786298, 1.0}, {2, 78, 244.524879, 290.016564, 1.0}, {1, 79, 36.696489, 420.023407, 1.0}, + {1, 2, 1139.861412, 1034.634984, 1.0}, + {2, 2, 1143.512192, 1065.355718, 1.0}, + {1, 3, 1760.821953, 644.658036, 1.0}, + {2, 3, 1770.901108, 697.899928, 1.0}, + {1, 4, 858.071823, 1068.520746, 1.0}, + {1, 6, 1633.952408, 797.050145, 1.0}, + {2, 6, 1642.508469, 849.157140, 1.0}, + {1, 8, 1716.695824, 451.805491, 1.0}, + {2, 8, 1726.513939, 502.095687, 1.0}, + {1, 9, 269.577627, 724.986935, 1.0}, + {2, 9, 269.424820, 764.154246, 1.0}, + {1, 10, 1891.321907, 706.948843, 1.0}, + {2, 10, 1903.338547, 766.068377, 1.0}, + {1, 12, 1806.227074, 956.089604, 1.0}, + {2, 12, 1816.619568, 1013.767376, 1.0}, + {1, 14, 269.544153, 1002.333570, 1.0}, + {2, 14, 269.367542, 1043.509254, 1.0}, + {1, 15, 1402.772141, 281.392962, 1.0}, + {2, 15, 1409.089165, 318.731629, 1.0}, + {1, 16, 195.877233, 919.454341, 1.0}, + {2, 16, 192.531109, 997.367899, 1.0}, + {1, 17, 1789.584045, 120.036661, 1.0}, + {2, 17, 1800.391846, 167.822964, 1.0}, + {1, 18, 999.363213, 765.004807, 1.0}, + {2, 18, 1002.345772, 790.560122, 1.0}, + {1, 19, 647.342491, 1044.805727, 1.0}, + {2, 19, 649.328041, 1058.682940, 1.0}, + {1, 20, 1365.486832, 440.901829, 1.0}, + {2, 20, 1371.413040, 477.888730, 1.0}, + {1, 21, 1787.125282, 301.431606, 1.0}, + {2, 21, 1798.527260, 355.224531, 1.0}, + {1, 22, 1257.805824, 932.797258, 1.0}, + {2, 22, 1263.017578, 969.376774, 1.0}, + {1, 23, 961.969528, 843.148112, 1.0}, + {2, 23, 964.869461, 868.587620, 1.0}, + {1, 24, 158.076110, 1052.643592, 1.0}, + {1, 25, 1072.884521, 1005.296981, 1.0}, + {2, 25, 1076.091156, 1032.776856, 1.0}, + {1, 26, 1107.656937, 526.577228, 1.0}, + {2, 26, 1111.618423, 555.524454, 1.0}, + {1, 27, 1416.410751, 529.857581, 1.0}, + {2, 27, 1422.663574, 570.025957, 1.0}, + {1, 28, 1498.673630, 1005.453086, 1.0}, + {2, 28, 1505.381813, 1051.827149, 1.0}, + {1, 29, 1428.647804, 652.473629, 1.0}, + {2, 29, 1434.898224, 692.715390, 1.0}, + {1, 30, 1332.318764, 503.673599, 1.0}, + {2, 30, 1338.000069, 540.507967, 1.0}, + {1, 32, 1358.642693, 709.837904, 1.0}, + {2, 32, 1364.231529, 748.678265, 1.0}, + {1, 33, 1850.911560, 460.475668, 1.0}, + {2, 33, 1862.221413, 512.797347, 1.0}, + {1, 34, 1226.117821, 607.053959, 1.0}, + {2, 34, 1230.736084, 641.091449, 1.0}, + {1, 35, 619.598236, 523.341744, 1.0}, + {2, 35, 621.601124, 554.453287, 1.0}, + {1, 36, 956.591492, 958.223183, 1.0}, + {2, 36, 959.289265, 983.289263, 1.0}, + {1, 37, 1249.922218, 419.095856, 1.0}, + {2, 37, 1255.005913, 452.556177, 1.0}, + {1, 39, 1300.528450, 386.251166, 1.0}, + {2, 39, 1305.957413, 420.185595, 1.0}, + {1, 40, 1128.689919, 972.558346, 1.0}, + {2, 40, 1132.413712, 1003.984737, 1.0}, + {1, 41, 503.304749, 1053.504388, 1.0}, + {2, 41, 505.019703, 1069.175613, 1.0}, + {1, 42, 1197.352982, 472.681564, 1.0}, + {2, 42, 1201.910706, 503.459880, 1.0}, + {1, 43, 1794.391022, 383.911400, 1.0}, + {2, 43, 1805.324135, 436.116468, 1.0}, + {1, 44, 789.641418, 1058.045647, 1.0}, + {1, 45, 1376.575241, 928.714979, 1.0}, + {2, 45, 1381.995850, 969.511957, 1.0}, + {1, 46, 1598.023567, 93.975592, 1.0}, + {2, 46, 1606.937141, 136.827035, 1.0}, + {1, 47, 1455.550232, 762.128685, 1.0}, + {2, 47, 1462.014313, 805.164878, 1.0}, + {1, 48, 1357.123489, 354.460326, 1.0}, + {2, 48, 1363.071899, 390.363121, 1.0}, + {1, 49, 939.792652, 781.549895, 1.0}, + {2, 49, 942.802620, 806.164012, 1.0}, + {1, 50, 1380.251083, 805.948620, 1.0}, + {2, 50, 1385.637932, 845.592098, 1.0}, + {1, 51, 1021.769943, 1049.802361, 1.0}, + {1, 52, 1065.634918, 608.099055, 1.0}, + {2, 52, 1069.142189, 635.361736, 1.0}, + {1, 53, 624.324188, 463.202863, 1.0}, + {2, 53, 626.395454, 494.994088, 1.0}, + {1, 54, 1451.459885, 881.557624, 1.0}, + {2, 54, 1457.679634, 924.345531, 1.0}, + {1, 55, 1201.885986, 1057.079022, 1.0}, + {1, 56, 581.157532, 947.661438, 1.0}, + {2, 56, 583.242359, 960.831449, 1.0}, + {1, 58, 513.593102, 954.175858, 1.0}, + {2, 58, 515.470047, 971.309574, 1.0}, + {1, 59, 928.069038, 901.774421, 1.0}, + {2, 59, 930.847950, 925.613744, 1.0}, + {1, 60, 1065.860023, 740.395389, 1.0}, + {2, 60, 1069.484253, 768.971086, 1.0}, + {1, 61, 990.479393, 906.264632, 1.0}, + {2, 61, 993.217506, 933.088803, 1.0}, + {1, 62, 1776.196747, 776.278453, 1.0}, + {2, 62, 1786.292496, 831.136880, 1.0}, + {1, 63, 834.454365, 1012.449725, 1.0}, + {2, 63, 836.868324, 1033.451807, 1.0}, + {1, 64, 1355.190697, 869.184809, 1.0}, + {2, 64, 1360.736618, 909.773347, 1.0}, + {1, 65, 702.072487, 897.519686, 1.0}, + {2, 65, 704.203377, 911.931131, 1.0}, + {1, 66, 1214.022903, 856.199934, 1.0}, + {2, 66, 1218.109016, 890.753052, 1.0}, + {1, 67, 327.676048, 236.814036, 1.0}, + {2, 67, 328.335285, 277.251878, 1.0}, + {1, 68, 289.064083, 454.793912, 1.0}, + {2, 68, 288.651924, 498.882444, 1.0}, + {1, 69, 1626.240692, 278.374350, 1.0}, + {2, 69, 1634.131508, 315.853672, 1.0}, + {1, 70, 1245.375710, 734.862142, 1.0}, + {2, 70, 1250.047417, 769.670885, 1.0}, + {1, 71, 497.015305, 510.718904, 1.0}, + {2, 71, 498.682308, 541.070201, 1.0}, + {1, 72, 1280.542030, 153.939185, 1.0}, + {2, 72, 1286.993637, 198.436196, 1.0}, + {1, 73, 1534.748840, 138.601043, 1.0}, + {2, 73, 1542.961349, 180.170819, 1.0}, + {1, 74, 1477.412682, 200.608061, 1.0}, + {2, 74, 1484.683914, 240.413260, 1.0}, + {1, 76, 450.637321, 407.279642, 1.0}, + {2, 76, 451.695642, 441.666291, 1.0}, + {1, 78, 246.981239, 220.786298, 1.0}, + {2, 78, 244.524879, 290.016564, 1.0}, + {1, 79, 36.696489, 420.023407, 1.0}, {2, 79, 21.364746, 591.245492, 1.0}, - }; + }; int num_markers = sizeof(markers) / sizeof(Marker); Tracks tracks; @@ -249,41 +402,110 @@ TEST(KeyframeSelection, ElevatorReconstructionVarianceTest) { intrinsics.SetRadialDistortion(-0.034, 0.0, 0.0); Marker markers[] = { - {1, 0, 182.999997, 1047.000010, 1.0}, {2, 0, 181.475730, 1052.091079, 1.0}, {3, 0, 181.741562, 1057.893341, 1.0}, - {4, 0, 183.190498, 1068.310440, 1.0}, {1, 1, 271.000013, 666.000009, 1.0}, {2, 1, 270.596180, 668.665760, 1.0}, - {3, 1, 270.523510, 671.559069, 1.0}, {4, 1, 271.856518, 676.818151, 1.0}, {5, 1, 268.989000, 727.051570, 1.0}, - {1, 2, 264.999990, 1018.000031, 1.0}, {2, 2, 264.020061, 1021.157591, 1.0}, {3, 2, 264.606056, 1024.823506, 1.0}, - {4, 2, 266.200933, 1031.168690, 1.0}, {1, 3, 270.000000, 938.000014, 1.0}, {2, 3, 269.022617, 941.153390, 1.0}, - {3, 3, 269.605579, 944.454954, 1.0}, {4, 3, 271.281366, 949.452167, 1.0}, {5, 3, 268.963480, 1004.417453, 1.0}, - {1, 4, 200.999994, 799.000003, 1.0}, {2, 4, 199.841366, 803.891838, 1.0}, {3, 4, 200.262208, 809.323246, 1.0}, - {4, 4, 201.456513, 819.271195, 1.0}, {5, 4, 195.026493, 924.363234, 1.0}, {1, 5, 1775.000038, 49.999998, 1.0}, - {2, 5, 1775.255127, 53.718264, 1.0}, {3, 5, 1776.449890, 55.951670, 1.0}, {4, 5, 1778.815727, 61.923309, 1.0}, - {5, 5, 1790.274124, 123.074923, 1.0}, {1, 6, 164.000001, 927.999988, 1.0}, {2, 6, 162.665462, 933.169527, 1.0}, - {3, 6, 163.067923, 938.577182, 1.0}, {4, 6, 164.370360, 948.840945, 1.0}, {5, 6, 157.199407, 1057.762341, 1.0}, - {1, 7, 618.000011, 477.999998, 1.0}, {2, 7, 617.583504, 480.124243, 1.0}, {3, 7, 618.356495, 482.441897, 1.0}, - {4, 7, 619.792500, 486.428132, 1.0}, {5, 7, 619.546051, 525.222627, 1.0}, {1, 8, 499.999981, 1036.999984, 1.0}, - {2, 8, 499.080162, 1038.720160, 1.0}, {3, 8, 499.949398, 1039.014344, 1.0}, {4, 8, 501.828003, 1041.286647, 1.0}, - {5, 8, 502.777576, 1055.196369, 1.0}, {1, 9, 1587.000046, 31.999999, 1.0}, {2, 9, 1586.988373, 34.635853, 1.0}, - {3, 9, 1588.155899, 37.444186, 1.0}, {4, 9, 1589.973106, 42.492081, 1.0}, {5, 9, 1598.683205, 96.526332, 1.0}, - {1, 10, 622.999992, 416.999999, 1.0}, {2, 10, 622.449017, 419.233485, 1.0}, {3, 10, 623.283234, 421.500703, 1.0}, - {4, 10, 624.620132, 425.537406, 1.0}, {5, 10, 624.290829, 465.078338, 1.0}, {1, 11, 577.999992, 931.999998, 1.0}, - {2, 11, 577.042294, 932.872703, 1.0}, {3, 11, 577.832451, 934.045451, 1.0}, {4, 11, 579.729137, 935.735435, 1.0}, - {5, 11, 580.691242, 948.396256, 1.0}, {1, 12, 510.999985, 931.999998, 1.0}, {2, 12, 510.111237, 933.152146, 1.0}, - {3, 12, 510.797081, 934.454219, 1.0}, {4, 12, 512.647362, 936.595910, 1.0}, {5, 12, 513.247204, 955.144157, 1.0}, - {1, 13, 330.459995, 177.059993, 1.0}, {2, 13, 329.876347, 179.615586, 1.0}, {3, 13, 330.681696, 182.757810, 1.0}, - {4, 13, 331.345053, 187.903853, 1.0}, {5, 13, 327.824135, 239.611639, 1.0}, {1, 14, 291.813097, 388.516195, 1.0}, - {2, 14, 290.984058, 391.382725, 1.0}, {3, 14, 291.526737, 394.778595, 1.0}, {4, 14, 292.763815, 400.310973, 1.0}, - {5, 14, 288.714552, 457.548015, 1.0}, {1, 15, 496.491680, 466.534005, 1.0}, {2, 15, 495.909519, 468.518561, 1.0}, - {3, 15, 496.588383, 470.853596, 1.0}, {4, 15, 497.976780, 474.731458, 1.0}, {5, 15, 496.998882, 512.568694, 1.0}, - {1, 16, 1273.000031, 89.000000, 1.0}, {2, 16, 1272.951965, 92.003637, 1.0}, {3, 16, 1273.934784, 94.972191, 1.0}, - {4, 16, 1275.493584, 100.139952, 1.0}, {5, 16, 1281.003571, 156.880163, 1.0}, {1, 17, 1524.713173, 78.852922, 1.0}, - {2, 17, 1524.782066, 81.427142, 1.0}, {3, 17, 1525.759048, 84.057939, 1.0}, {4, 17, 1527.579689, 88.966550, 1.0}, - {5, 17, 1535.262451, 141.186054, 1.0}, {1, 18, 1509.425011, 94.371824, 1.0}, {1, 19, 451.000013, 357.000003, 1.0}, - {2, 19, 450.354881, 359.312410, 1.0}, {3, 19, 451.107473, 361.837088, 1.0}, {4, 19, 452.186537, 366.318061, 1.0}, - {5, 19, 450.507660, 409.257599, 1.0}, {1, 20, 254.004936, 114.784185, 1.0}, {2, 20, 253.291512, 119.288486, 1.0}, - {3, 20, 253.745584, 124.114957, 1.0}, {4, 20, 254.453287, 132.795120, 1.0}, {5, 20, 246.772242, 225.165337, 1.0}, - {1, 21, 65.262880, 147.889409, 1.0}, {2, 21, 63.634465, 157.656807, 1.0}, {3, 21, 63.306799, 169.067053, 1.0}, - {4, 21, 62.462311, 189.724241, 1.0}, {5, 21, 35.396615, 430.308380, 1.0}, + {1, 0, 182.999997, 1047.000010, 1.0}, + {2, 0, 181.475730, 1052.091079, 1.0}, + {3, 0, 181.741562, 1057.893341, 1.0}, + {4, 0, 183.190498, 1068.310440, 1.0}, + {1, 1, 271.000013, 666.000009, 1.0}, + {2, 1, 270.596180, 668.665760, 1.0}, + {3, 1, 270.523510, 671.559069, 1.0}, + {4, 1, 271.856518, 676.818151, 1.0}, + {5, 1, 268.989000, 727.051570, 1.0}, + {1, 2, 264.999990, 1018.000031, 1.0}, + {2, 2, 264.020061, 1021.157591, 1.0}, + {3, 2, 264.606056, 1024.823506, 1.0}, + {4, 2, 266.200933, 1031.168690, 1.0}, + {1, 3, 270.000000, 938.000014, 1.0}, + {2, 3, 269.022617, 941.153390, 1.0}, + {3, 3, 269.605579, 944.454954, 1.0}, + {4, 3, 271.281366, 949.452167, 1.0}, + {5, 3, 268.963480, 1004.417453, 1.0}, + {1, 4, 200.999994, 799.000003, 1.0}, + {2, 4, 199.841366, 803.891838, 1.0}, + {3, 4, 200.262208, 809.323246, 1.0}, + {4, 4, 201.456513, 819.271195, 1.0}, + {5, 4, 195.026493, 924.363234, 1.0}, + {1, 5, 1775.000038, 49.999998, 1.0}, + {2, 5, 1775.255127, 53.718264, 1.0}, + {3, 5, 1776.449890, 55.951670, 1.0}, + {4, 5, 1778.815727, 61.923309, 1.0}, + {5, 5, 1790.274124, 123.074923, 1.0}, + {1, 6, 164.000001, 927.999988, 1.0}, + {2, 6, 162.665462, 933.169527, 1.0}, + {3, 6, 163.067923, 938.577182, 1.0}, + {4, 6, 164.370360, 948.840945, 1.0}, + {5, 6, 157.199407, 1057.762341, 1.0}, + {1, 7, 618.000011, 477.999998, 1.0}, + {2, 7, 617.583504, 480.124243, 1.0}, + {3, 7, 618.356495, 482.441897, 1.0}, + {4, 7, 619.792500, 486.428132, 1.0}, + {5, 7, 619.546051, 525.222627, 1.0}, + {1, 8, 499.999981, 1036.999984, 1.0}, + {2, 8, 499.080162, 1038.720160, 1.0}, + {3, 8, 499.949398, 1039.014344, 1.0}, + {4, 8, 501.828003, 1041.286647, 1.0}, + {5, 8, 502.777576, 1055.196369, 1.0}, + {1, 9, 1587.000046, 31.999999, 1.0}, + {2, 9, 1586.988373, 34.635853, 1.0}, + {3, 9, 1588.155899, 37.444186, 1.0}, + {4, 9, 1589.973106, 42.492081, 1.0}, + {5, 9, 1598.683205, 96.526332, 1.0}, + {1, 10, 622.999992, 416.999999, 1.0}, + {2, 10, 622.449017, 419.233485, 1.0}, + {3, 10, 623.283234, 421.500703, 1.0}, + {4, 10, 624.620132, 425.537406, 1.0}, + {5, 10, 624.290829, 465.078338, 1.0}, + {1, 11, 577.999992, 931.999998, 1.0}, + {2, 11, 577.042294, 932.872703, 1.0}, + {3, 11, 577.832451, 934.045451, 1.0}, + {4, 11, 579.729137, 935.735435, 1.0}, + {5, 11, 580.691242, 948.396256, 1.0}, + {1, 12, 510.999985, 931.999998, 1.0}, + {2, 12, 510.111237, 933.152146, 1.0}, + {3, 12, 510.797081, 934.454219, 1.0}, + {4, 12, 512.647362, 936.595910, 1.0}, + {5, 12, 513.247204, 955.144157, 1.0}, + {1, 13, 330.459995, 177.059993, 1.0}, + {2, 13, 329.876347, 179.615586, 1.0}, + {3, 13, 330.681696, 182.757810, 1.0}, + {4, 13, 331.345053, 187.903853, 1.0}, + {5, 13, 327.824135, 239.611639, 1.0}, + {1, 14, 291.813097, 388.516195, 1.0}, + {2, 14, 290.984058, 391.382725, 1.0}, + {3, 14, 291.526737, 394.778595, 1.0}, + {4, 14, 292.763815, 400.310973, 1.0}, + {5, 14, 288.714552, 457.548015, 1.0}, + {1, 15, 496.491680, 466.534005, 1.0}, + {2, 15, 495.909519, 468.518561, 1.0}, + {3, 15, 496.588383, 470.853596, 1.0}, + {4, 15, 497.976780, 474.731458, 1.0}, + {5, 15, 496.998882, 512.568694, 1.0}, + {1, 16, 1273.000031, 89.000000, 1.0}, + {2, 16, 1272.951965, 92.003637, 1.0}, + {3, 16, 1273.934784, 94.972191, 1.0}, + {4, 16, 1275.493584, 100.139952, 1.0}, + {5, 16, 1281.003571, 156.880163, 1.0}, + {1, 17, 1524.713173, 78.852922, 1.0}, + {2, 17, 1524.782066, 81.427142, 1.0}, + {3, 17, 1525.759048, 84.057939, 1.0}, + {4, 17, 1527.579689, 88.966550, 1.0}, + {5, 17, 1535.262451, 141.186054, 1.0}, + {1, 18, 1509.425011, 94.371824, 1.0}, + {1, 19, 451.000013, 357.000003, 1.0}, + {2, 19, 450.354881, 359.312410, 1.0}, + {3, 19, 451.107473, 361.837088, 1.0}, + {4, 19, 452.186537, 366.318061, 1.0}, + {5, 19, 450.507660, 409.257599, 1.0}, + {1, 20, 254.004936, 114.784185, 1.0}, + {2, 20, 253.291512, 119.288486, 1.0}, + {3, 20, 253.745584, 124.114957, 1.0}, + {4, 20, 254.453287, 132.795120, 1.0}, + {5, 20, 246.772242, 225.165337, 1.0}, + {1, 21, 65.262880, 147.889409, 1.0}, + {2, 21, 63.634465, 157.656807, 1.0}, + {3, 21, 63.306799, 169.067053, 1.0}, + {4, 21, 62.462311, 189.724241, 1.0}, + {5, 21, 35.396615, 430.308380, 1.0}, }; int num_markers = sizeof(markers) / sizeof(Marker); @@ -304,4 +526,4 @@ TEST(KeyframeSelection, ElevatorReconstructionVarianceTest) { } } -} // namespace libmv +} // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/modal_solver.cc b/intern/libmv/libmv/simple_pipeline/modal_solver.cc index 687c328b004..845b299e31e 100644 --- a/intern/libmv/libmv/simple_pipeline/modal_solver.cc +++ b/intern/libmv/libmv/simple_pipeline/modal_solver.cc @@ -34,7 +34,7 @@ namespace libmv { namespace { -void ProjectMarkerOnSphere(const Marker &marker, Vec3 &X) { +void ProjectMarkerOnSphere(const Marker& marker, Vec3& X) { X(0) = marker.x; X(1) = marker.y; X(2) = 1.0; @@ -42,12 +42,14 @@ void ProjectMarkerOnSphere(const Marker &marker, Vec3 &X) { X *= 5.0 / X.norm(); } -void ModalSolverLogProgress(ProgressUpdateCallback *update_callback, - double progress) { +void ModalSolverLogProgress(ProgressUpdateCallback* update_callback, + double progress) { if (update_callback) { char message[256]; - snprintf(message, sizeof(message), "Solving progress %d%%", + snprintf(message, + sizeof(message), + "Solving progress %d%%", (int)(progress * 100)); update_callback->invoke(progress, message); @@ -58,25 +60,27 @@ struct ModalReprojectionError { ModalReprojectionError(double observed_x, double observed_y, const double weight, - const Vec3 &bundle) - : observed_x_(observed_x), observed_y_(observed_y), - weight_(weight), bundle_(bundle) { } + const Vec3& bundle) + : observed_x_(observed_x), + observed_y_(observed_y), + weight_(weight), + bundle_(bundle) {} // TODO(keir): This should support bundling focal length as well. template <typename T> bool operator()(const T* quaternion, T* residuals) const { // Convert bundle position from double to T. - T X[3] = { T(bundle_(0)), T(bundle_(1)), T(bundle_(2)) }; + T X[3] = {T(bundle_(0)), T(bundle_(1)), T(bundle_(2))}; // Compute the point position in camera coordinates: x = RX. T x[3]; // This flips the sense of the quaternion, to adhere to Blender conventions. T quaternion_inverse[4] = { - quaternion[0], - -quaternion[1], - -quaternion[2], - -quaternion[3], + quaternion[0], + -quaternion[1], + -quaternion[2], + -quaternion[3], }; ceres::QuaternionRotatePoint(quaternion_inverse, X, x); @@ -99,9 +103,9 @@ struct ModalReprojectionError { }; } // namespace -void ModalSolver(const Tracks &tracks, - EuclideanReconstruction *reconstruction, - ProgressUpdateCallback *update_callback) { +void ModalSolver(const Tracks& tracks, + EuclideanReconstruction* reconstruction, + ProgressUpdateCallback* update_callback) { int max_image = tracks.MaxImage(); int max_track = tracks.MaxTrack(); @@ -116,7 +120,7 @@ void ModalSolver(const Tracks &tracks, for (int image = 0; image <= max_image; ++image) { vector<Marker> all_markers = tracks.MarkersInImage(image); - ModalSolverLogProgress(update_callback, (float) image / max_image); + ModalSolverLogProgress(update_callback, (float)image / max_image); // Skip empty images without doing anything. if (all_markers.size() == 0) { @@ -133,8 +137,8 @@ void ModalSolver(const Tracks &tracks, // 3D positions. Mat x1, x2; for (int i = 0; i < all_markers.size(); ++i) { - Marker &marker = all_markers[i]; - EuclideanPoint *point = reconstruction->PointForTrack(marker.track); + Marker& marker = all_markers[i]; + EuclideanPoint* point = reconstruction->PointForTrack(marker.track); if (point) { Vec3 X; ProjectMarkerOnSphere(marker, X); @@ -168,8 +172,7 @@ void ModalSolver(const Tracks &tracks, ceres::AngleAxisToQuaternion(&angle_axis(0), &quaternion(0)); - LG << "Analytically computed quaternion " - << quaternion.transpose(); + LG << "Analytically computed quaternion " << quaternion.transpose(); } // STEP 2: Refine rotation with Ceres. @@ -181,17 +184,15 @@ void ModalSolver(const Tracks &tracks, int num_residuals = 0; for (int i = 0; i < all_markers.size(); ++i) { - Marker &marker = all_markers[i]; - EuclideanPoint *point = reconstruction->PointForTrack(marker.track); + Marker& marker = all_markers[i]; + EuclideanPoint* point = reconstruction->PointForTrack(marker.track); if (point && marker.weight != 0.0) { - problem.AddResidualBlock(new ceres::AutoDiffCostFunction< - ModalReprojectionError, - 2, /* num_residuals */ - 4>(new ModalReprojectionError(marker.x, - marker.y, - marker.weight, - point->X)), + problem.AddResidualBlock( + new ceres::AutoDiffCostFunction<ModalReprojectionError, + 2, /* num_residuals */ + 4>(new ModalReprojectionError( + marker.x, marker.y, marker.weight, point->X)), NULL, &quaternion(0)); num_residuals++; diff --git a/intern/libmv/libmv/simple_pipeline/modal_solver.h b/intern/libmv/libmv/simple_pipeline/modal_solver.h index 9801fd21d81..f7ce394b4b2 100644 --- a/intern/libmv/libmv/simple_pipeline/modal_solver.h +++ b/intern/libmv/libmv/simple_pipeline/modal_solver.h @@ -21,9 +21,9 @@ #ifndef LIBMV_SIMPLE_PIPELINE_MODAL_SOLVER_H_ #define LIBMV_SIMPLE_PIPELINE_MODAL_SOLVER_H_ -#include "libmv/simple_pipeline/tracks.h" -#include "libmv/simple_pipeline/reconstruction.h" #include "libmv/simple_pipeline/callbacks.h" +#include "libmv/simple_pipeline/reconstruction.h" +#include "libmv/simple_pipeline/tracks.h" namespace libmv { @@ -39,9 +39,9 @@ namespace libmv { Reconstructed cameras and projected bundles would be added to reconstruction object. */ -void ModalSolver(const Tracks &tracks, - EuclideanReconstruction *reconstruction, - ProgressUpdateCallback *update_callback = NULL); +void ModalSolver(const Tracks& tracks, + EuclideanReconstruction* reconstruction, + ProgressUpdateCallback* update_callback = NULL); } // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/modal_solver_test.cc b/intern/libmv/libmv/simple_pipeline/modal_solver_test.cc index b4cae8defb2..0acf978e6f5 100644 --- a/intern/libmv/libmv/simple_pipeline/modal_solver_test.cc +++ b/intern/libmv/libmv/simple_pipeline/modal_solver_test.cc @@ -20,10 +20,10 @@ #include "libmv/simple_pipeline/modal_solver.h" -#include "testing/testing.h" #include "libmv/logging/logging.h" #include "libmv/simple_pipeline/bundle.h" #include "libmv/simple_pipeline/camera_intrinsics.h" +#include "testing/testing.h" #include <stdio.h> @@ -38,14 +38,21 @@ TEST(ModalSolver, SyntheticCubeSceneMotion) { intrinsics.SetRadialDistortion(0.0, 0.0, 0.0); Marker markers[] = { - {1, 0, 212.172775, 354.713538, 1.0}, {2, 0, 773.468399, 358.735306, 1.0}, - {1, 1, 62.415197, 287.905354, 1.0}, {2, 1, 619.103336, 324.402537, 1.0}, - {1, 2, 206.847939, 237.567925, 1.0}, {2, 2, 737.496986, 247.881383, 1.0}, - {1, 3, 351.743889, 316.415906, 1.0}, {2, 3, 908.779621, 290.703617, 1.0}, - {1, 4, 232.941413, 54.265443, 1.0}, {2, 4, 719.444847, 63.062531, 1.0}, - {1, 5, 96.391611, 119.283537, 1.0}, {2, 5, 611.413136, 160.890715, 1.0}, - {1, 6, 363.444958, 150.838144, 1.0}, {2, 6, 876.374531, 114.916206, 1.0}, - }; + {1, 0, 212.172775, 354.713538, 1.0}, + {2, 0, 773.468399, 358.735306, 1.0}, + {1, 1, 62.415197, 287.905354, 1.0}, + {2, 1, 619.103336, 324.402537, 1.0}, + {1, 2, 206.847939, 237.567925, 1.0}, + {2, 2, 737.496986, 247.881383, 1.0}, + {1, 3, 351.743889, 316.415906, 1.0}, + {2, 3, 908.779621, 290.703617, 1.0}, + {1, 4, 232.941413, 54.265443, 1.0}, + {2, 4, 719.444847, 63.062531, 1.0}, + {1, 5, 96.391611, 119.283537, 1.0}, + {2, 5, 611.413136, 160.890715, 1.0}, + {1, 6, 363.444958, 150.838144, 1.0}, + {2, 6, 876.374531, 114.916206, 1.0}, + }; int num_markers = sizeof(markers) / sizeof(Marker); Tracks tracks; @@ -65,12 +72,14 @@ TEST(ModalSolver, SyntheticCubeSceneMotion) { NULL); Mat3 expected_rotation; + // clang-format off expected_rotation << 0.98215101743472, 0.17798354937546, 0.06083777694542, -0.16875283983360, 0.97665300495333, -0.13293376908719, -0.08307742172243, 0.12029448893171, 0.98925597189636; + // clang-format on - Mat3 &first_camera_R = reconstruction.CameraForImage(1)->R; - Mat3 &second_camera_R = reconstruction.CameraForImage(2)->R; + Mat3& first_camera_R = reconstruction.CameraForImage(1)->R; + Mat3& second_camera_R = reconstruction.CameraForImage(2)->R; EXPECT_TRUE(Mat3::Identity().isApprox(first_camera_R, kTolerance)); EXPECT_TRUE(expected_rotation.isApprox(second_camera_R, kTolerance)); diff --git a/intern/libmv/libmv/simple_pipeline/packed_intrinsics.h b/intern/libmv/libmv/simple_pipeline/packed_intrinsics.h index cbea599fccd..79fa3ab8379 100644 --- a/intern/libmv/libmv/simple_pipeline/packed_intrinsics.h +++ b/intern/libmv/libmv/simple_pipeline/packed_intrinsics.h @@ -40,7 +40,7 @@ class PackedIntrinsics { OFFSET_FOCAL_LENGTH, OFFSET_PRINCIPAL_POINT_X, OFFSET_PRINCIPAL_POINT_Y, - + // Distortion model coefficients. OFFSET_K1, OFFSET_K2, @@ -48,7 +48,7 @@ class PackedIntrinsics { OFFSET_K4, OFFSET_P1, OFFSET_P2, - + // Number of parameters which are to be stored in the block. NUM_PARAMETERS, }; @@ -66,12 +66,12 @@ class PackedIntrinsics { // point. #define DEFINE_PARAMETER(parameter_name) \ - void Set ## parameter_name(double value) { \ - SetParameter(OFFSET_ ## parameter_name, value); \ - } \ - double Get ## parameter_name() const { \ - return GetParameter(OFFSET_ ## parameter_name); \ + void Set##parameter_name(double value) { \ + SetParameter(OFFSET_##parameter_name, value); \ } \ + double Get##parameter_name() const { \ + return GetParameter(OFFSET_##parameter_name); \ + } DEFINE_PARAMETER(K1) DEFINE_PARAMETER(K2) @@ -94,11 +94,11 @@ class PackedIntrinsics { // All intrinsics parameters packed into a single block. // Use OFFSET_FOO indexes to access corresponding values. - array<double, NUM_PARAMETERS> parameters_; + array<double, NUM_PARAMETERS> parameters_; // Indexed by parameter offset, set to truth if the value of the parameter is // explicitly specified. - array<bool, NUM_PARAMETERS> known_parameters_; + array<bool, NUM_PARAMETERS> known_parameters_; }; } // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/pipeline.cc b/intern/libmv/libmv/simple_pipeline/pipeline.cc index 728601f3732..5d52aeb7406 100644 --- a/intern/libmv/libmv/simple_pipeline/pipeline.cc +++ b/intern/libmv/libmv/simple_pipeline/pipeline.cc @@ -24,11 +24,11 @@ #include "libmv/logging/logging.h" #include "libmv/simple_pipeline/bundle.h" +#include "libmv/simple_pipeline/camera_intrinsics.h" #include "libmv/simple_pipeline/intersect.h" -#include "libmv/simple_pipeline/resect.h" #include "libmv/simple_pipeline/reconstruction.h" +#include "libmv/simple_pipeline/resect.h" #include "libmv/simple_pipeline/tracks.h" -#include "libmv/simple_pipeline/camera_intrinsics.h" #ifdef _MSC_VER # define snprintf _snprintf @@ -46,24 +46,25 @@ struct EuclideanPipelineRoutines { typedef EuclideanCamera Camera; typedef EuclideanPoint Point; - static void Bundle(const Tracks &tracks, - EuclideanReconstruction *reconstruction) { + static void Bundle(const Tracks& tracks, + EuclideanReconstruction* reconstruction) { EuclideanBundle(tracks, reconstruction); } - static bool Resect(const vector<Marker> &markers, - EuclideanReconstruction *reconstruction, bool final_pass) { + static bool Resect(const vector<Marker>& markers, + EuclideanReconstruction* reconstruction, + bool final_pass) { return EuclideanResect(markers, reconstruction, final_pass); } - static bool Intersect(const vector<Marker> &markers, - EuclideanReconstruction *reconstruction) { + static bool Intersect(const vector<Marker>& markers, + EuclideanReconstruction* reconstruction) { return EuclideanIntersect(markers, reconstruction); } - static Marker ProjectMarker(const EuclideanPoint &point, - const EuclideanCamera &camera, - const CameraIntrinsics &intrinsics) { + static Marker ProjectMarker(const EuclideanPoint& point, + const EuclideanCamera& camera, + const CameraIntrinsics& intrinsics) { Vec3 projected = camera.R * point.X + camera.t; projected /= projected(2); @@ -84,26 +85,27 @@ struct ProjectivePipelineRoutines { typedef ProjectiveCamera Camera; typedef ProjectivePoint Point; - static void Bundle(const Tracks &tracks, - ProjectiveReconstruction *reconstruction) { + static void Bundle(const Tracks& tracks, + ProjectiveReconstruction* reconstruction) { ProjectiveBundle(tracks, reconstruction); } - static bool Resect(const vector<Marker> &markers, - ProjectiveReconstruction *reconstruction, bool final_pass) { - (void) final_pass; // Ignored. + static bool Resect(const vector<Marker>& markers, + ProjectiveReconstruction* reconstruction, + bool final_pass) { + (void)final_pass; // Ignored. return ProjectiveResect(markers, reconstruction); } - static bool Intersect(const vector<Marker> &markers, - ProjectiveReconstruction *reconstruction) { + static bool Intersect(const vector<Marker>& markers, + ProjectiveReconstruction* reconstruction) { return ProjectiveIntersect(markers, reconstruction); } - static Marker ProjectMarker(const ProjectivePoint &point, - const ProjectiveCamera &camera, - const CameraIntrinsics &intrinsics) { + static Marker ProjectMarker(const ProjectivePoint& point, + const ProjectiveCamera& camera, + const CameraIntrinsics& intrinsics) { Vec3 projected = camera.P * point.X; projected /= projected(2); @@ -122,28 +124,33 @@ struct ProjectivePipelineRoutines { } // namespace static void CompleteReconstructionLogProgress( - ProgressUpdateCallback *update_callback, + ProgressUpdateCallback* update_callback, double progress, - const char *step = NULL) { + const char* step = NULL) { if (update_callback) { char message[256]; if (step) - snprintf(message, sizeof(message), "Completing solution %d%% | %s", - (int)(progress*100), step); + snprintf(message, + sizeof(message), + "Completing solution %d%% | %s", + (int)(progress * 100), + step); else - snprintf(message, sizeof(message), "Completing solution %d%%", - (int)(progress*100)); + snprintf(message, + sizeof(message), + "Completing solution %d%%", + (int)(progress * 100)); update_callback->invoke(progress, message); } } -template<typename PipelineRoutines> +template <typename PipelineRoutines> void InternalCompleteReconstruction( - const Tracks &tracks, - typename PipelineRoutines::Reconstruction *reconstruction, - ProgressUpdateCallback *update_callback = NULL) { + const Tracks& tracks, + typename PipelineRoutines::Reconstruction* reconstruction, + ProgressUpdateCallback* update_callback = NULL) { int max_track = tracks.MaxTrack(); int max_image = tracks.MaxImage(); int num_resects = -1; @@ -173,7 +180,7 @@ void InternalCompleteReconstruction( << " reconstructed markers for track " << track; if (reconstructed_markers.size() >= 2) { CompleteReconstructionLogProgress(update_callback, - (double)tot_resects/(max_image)); + (double)tot_resects / (max_image)); if (PipelineRoutines::Intersect(reconstructed_markers, reconstruction)) { num_intersects++; @@ -184,9 +191,8 @@ void InternalCompleteReconstruction( } } if (num_intersects) { - CompleteReconstructionLogProgress(update_callback, - (double)tot_resects/(max_image), - "Bundling..."); + CompleteReconstructionLogProgress( + update_callback, (double)tot_resects / (max_image), "Bundling..."); PipelineRoutines::Bundle(tracks, reconstruction); LG << "Ran Bundle() after intersections."; } @@ -212,9 +218,9 @@ void InternalCompleteReconstruction( << " reconstructed markers for image " << image; if (reconstructed_markers.size() >= 5) { CompleteReconstructionLogProgress(update_callback, - (double)tot_resects/(max_image)); - if (PipelineRoutines::Resect(reconstructed_markers, - reconstruction, false)) { + (double)tot_resects / (max_image)); + if (PipelineRoutines::Resect( + reconstructed_markers, reconstruction, false)) { num_resects++; tot_resects++; LG << "Ran Resect() for image " << image; @@ -224,9 +230,8 @@ void InternalCompleteReconstruction( } } if (num_resects) { - CompleteReconstructionLogProgress(update_callback, - (double)tot_resects/(max_image), - "Bundling..."); + CompleteReconstructionLogProgress( + update_callback, (double)tot_resects / (max_image), "Bundling..."); PipelineRoutines::Bundle(tracks, reconstruction); } LG << "Did " << num_resects << " resects."; @@ -249,9 +254,9 @@ void InternalCompleteReconstruction( } if (reconstructed_markers.size() >= 5) { CompleteReconstructionLogProgress(update_callback, - (double)tot_resects/(max_image)); - if (PipelineRoutines::Resect(reconstructed_markers, - reconstruction, true)) { + (double)tot_resects / (max_image)); + if (PipelineRoutines::Resect( + reconstructed_markers, reconstruction, true)) { num_resects++; LG << "Ran final Resect() for image " << image; } else { @@ -260,27 +265,26 @@ void InternalCompleteReconstruction( } } if (num_resects) { - CompleteReconstructionLogProgress(update_callback, - (double)tot_resects/(max_image), - "Bundling..."); + CompleteReconstructionLogProgress( + update_callback, (double)tot_resects / (max_image), "Bundling..."); PipelineRoutines::Bundle(tracks, reconstruction); } } -template<typename PipelineRoutines> +template <typename PipelineRoutines> double InternalReprojectionError( - const Tracks &image_tracks, - const typename PipelineRoutines::Reconstruction &reconstruction, - const CameraIntrinsics &intrinsics) { + const Tracks& image_tracks, + const typename PipelineRoutines::Reconstruction& reconstruction, + const CameraIntrinsics& intrinsics) { int num_skipped = 0; int num_reprojected = 0; double total_error = 0.0; vector<Marker> markers = image_tracks.AllMarkers(); for (int i = 0; i < markers.size(); ++i) { double weight = markers[i].weight; - const typename PipelineRoutines::Camera *camera = + const typename PipelineRoutines::Camera* camera = reconstruction.CameraForImage(markers[i].image); - const typename PipelineRoutines::Point *point = + const typename PipelineRoutines::Point* point = reconstruction.PointForTrack(markers[i].track); if (!camera || !point || weight == 0.0) { num_skipped++; @@ -295,24 +299,25 @@ double InternalReprojectionError( const int N = 100; char line[N]; - snprintf(line, N, - "image %-3d track %-3d " - "x %7.1f y %7.1f " - "rx %7.1f ry %7.1f " - "ex %7.1f ey %7.1f" - " e %7.1f", - markers[i].image, - markers[i].track, - markers[i].x, - markers[i].y, - reprojected_marker.x, - reprojected_marker.y, - ex, - ey, - sqrt(ex*ex + ey*ey)); + snprintf(line, + N, + "image %-3d track %-3d " + "x %7.1f y %7.1f " + "rx %7.1f ry %7.1f " + "ex %7.1f ey %7.1f" + " e %7.1f", + markers[i].image, + markers[i].track, + markers[i].x, + markers[i].y, + reprojected_marker.x, + reprojected_marker.y, + ex, + ey, + sqrt(ex * ex + ey * ey)); VLOG(1) << line; - total_error += sqrt(ex*ex + ey*ey); + total_error += sqrt(ex * ex + ey * ey); } LG << "Skipped " << num_skipped << " markers."; LG << "Reprojected " << num_reprojected << " markers."; @@ -321,46 +326,41 @@ double InternalReprojectionError( return total_error / num_reprojected; } -double EuclideanReprojectionError(const Tracks &image_tracks, - const EuclideanReconstruction &reconstruction, - const CameraIntrinsics &intrinsics) { - return InternalReprojectionError<EuclideanPipelineRoutines>(image_tracks, - reconstruction, - intrinsics); +double EuclideanReprojectionError(const Tracks& image_tracks, + const EuclideanReconstruction& reconstruction, + const CameraIntrinsics& intrinsics) { + return InternalReprojectionError<EuclideanPipelineRoutines>( + image_tracks, reconstruction, intrinsics); } double ProjectiveReprojectionError( - const Tracks &image_tracks, - const ProjectiveReconstruction &reconstruction, - const CameraIntrinsics &intrinsics) { - return InternalReprojectionError<ProjectivePipelineRoutines>(image_tracks, - reconstruction, - intrinsics); + const Tracks& image_tracks, + const ProjectiveReconstruction& reconstruction, + const CameraIntrinsics& intrinsics) { + return InternalReprojectionError<ProjectivePipelineRoutines>( + image_tracks, reconstruction, intrinsics); } -void EuclideanCompleteReconstruction(const Tracks &tracks, - EuclideanReconstruction *reconstruction, - ProgressUpdateCallback *update_callback) { - InternalCompleteReconstruction<EuclideanPipelineRoutines>(tracks, - reconstruction, - update_callback); +void EuclideanCompleteReconstruction(const Tracks& tracks, + EuclideanReconstruction* reconstruction, + ProgressUpdateCallback* update_callback) { + InternalCompleteReconstruction<EuclideanPipelineRoutines>( + tracks, reconstruction, update_callback); } -void ProjectiveCompleteReconstruction(const Tracks &tracks, - ProjectiveReconstruction *reconstruction) { +void ProjectiveCompleteReconstruction( + const Tracks& tracks, ProjectiveReconstruction* reconstruction) { InternalCompleteReconstruction<ProjectivePipelineRoutines>(tracks, reconstruction); } -void InvertIntrinsicsForTracks(const Tracks &raw_tracks, - const CameraIntrinsics &camera_intrinsics, - Tracks *calibrated_tracks) { +void InvertIntrinsicsForTracks(const Tracks& raw_tracks, + const CameraIntrinsics& camera_intrinsics, + Tracks* calibrated_tracks) { vector<Marker> markers = raw_tracks.AllMarkers(); for (int i = 0; i < markers.size(); ++i) { - camera_intrinsics.InvertIntrinsics(markers[i].x, - markers[i].y, - &(markers[i].x), - &(markers[i].y)); + camera_intrinsics.InvertIntrinsics( + markers[i].x, markers[i].y, &(markers[i].x), &(markers[i].y)); } *calibrated_tracks = Tracks(markers); } diff --git a/intern/libmv/libmv/simple_pipeline/pipeline.h b/intern/libmv/libmv/simple_pipeline/pipeline.h index 4d1bd00c51f..d6b43536d46 100644 --- a/intern/libmv/libmv/simple_pipeline/pipeline.h +++ b/intern/libmv/libmv/simple_pipeline/pipeline.h @@ -22,8 +22,8 @@ #define LIBMV_SIMPLE_PIPELINE_PIPELINE_H_ #include "libmv/simple_pipeline/callbacks.h" -#include "libmv/simple_pipeline/tracks.h" #include "libmv/simple_pipeline/reconstruction.h" +#include "libmv/simple_pipeline/tracks.h" namespace libmv { @@ -47,9 +47,9 @@ namespace libmv { \sa EuclideanResect, EuclideanIntersect, EuclideanBundle */ void EuclideanCompleteReconstruction( - const Tracks &tracks, - EuclideanReconstruction *reconstruction, - ProgressUpdateCallback *update_callback = NULL); + const Tracks& tracks, + EuclideanReconstruction* reconstruction, + ProgressUpdateCallback* update_callback = NULL); /*! Estimate camera matrices and homogeneous 3D coordinates for all frames and @@ -71,27 +71,26 @@ void EuclideanCompleteReconstruction( \sa ProjectiveResect, ProjectiveIntersect, ProjectiveBundle */ -void ProjectiveCompleteReconstruction(const Tracks &tracks, - ProjectiveReconstruction *reconstruction); - +void ProjectiveCompleteReconstruction(const Tracks& tracks, + ProjectiveReconstruction* reconstruction); class CameraIntrinsics; // TODO(keir): Decide if we want these in the public API, and if so, what the // appropriate include file is. -double EuclideanReprojectionError(const Tracks &image_tracks, - const EuclideanReconstruction &reconstruction, - const CameraIntrinsics &intrinsics); +double EuclideanReprojectionError(const Tracks& image_tracks, + const EuclideanReconstruction& reconstruction, + const CameraIntrinsics& intrinsics); double ProjectiveReprojectionError( - const Tracks &image_tracks, - const ProjectiveReconstruction &reconstruction, - const CameraIntrinsics &intrinsics); + const Tracks& image_tracks, + const ProjectiveReconstruction& reconstruction, + const CameraIntrinsics& intrinsics); -void InvertIntrinsicsForTracks(const Tracks &raw_tracks, - const CameraIntrinsics &camera_intrinsics, - Tracks *calibrated_tracks); +void InvertIntrinsicsForTracks(const Tracks& raw_tracks, + const CameraIntrinsics& camera_intrinsics, + Tracks* calibrated_tracks); } // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/reconstruction.cc b/intern/libmv/libmv/simple_pipeline/reconstruction.cc index 851eedb5bb1..584f7440caf 100644 --- a/intern/libmv/libmv/simple_pipeline/reconstruction.cc +++ b/intern/libmv/libmv/simple_pipeline/reconstruction.cc @@ -19,20 +19,21 @@ // IN THE SOFTWARE. #include "libmv/simple_pipeline/reconstruction.h" -#include "libmv/numeric/numeric.h" #include "libmv/logging/logging.h" +#include "libmv/numeric/numeric.h" namespace libmv { -EuclideanReconstruction::EuclideanReconstruction() {} +EuclideanReconstruction::EuclideanReconstruction() { +} EuclideanReconstruction::EuclideanReconstruction( - const EuclideanReconstruction &other) { + const EuclideanReconstruction& other) { image_to_cameras_map_ = other.image_to_cameras_map_; points_ = other.points_; } -EuclideanReconstruction &EuclideanReconstruction::operator=( - const EuclideanReconstruction &other) { +EuclideanReconstruction& EuclideanReconstruction::operator=( + const EuclideanReconstruction& other) { if (&other != this) { image_to_cameras_map_ = other.image_to_cameras_map_; points_ = other.points_; @@ -41,9 +42,9 @@ EuclideanReconstruction &EuclideanReconstruction::operator=( } void EuclideanReconstruction::InsertCamera(int image, - const Mat3 &R, - const Vec3 &t) { - LG << "InsertCamera " << image << ":\nR:\n"<< R << "\nt:\n" << t; + const Mat3& R, + const Vec3& t) { + LG << "InsertCamera " << image << ":\nR:\n" << R << "\nt:\n" << t; EuclideanCamera camera; camera.image = image; @@ -53,7 +54,7 @@ void EuclideanReconstruction::InsertCamera(int image, image_to_cameras_map_.insert(make_pair(image, camera)); } -void EuclideanReconstruction::InsertPoint(int track, const Vec3 &X) { +void EuclideanReconstruction::InsertPoint(int track, const Vec3& X) { LG << "InsertPoint " << track << ":\n" << X; if (track >= points_.size()) { points_.resize(track + 1); @@ -62,13 +63,12 @@ void EuclideanReconstruction::InsertPoint(int track, const Vec3 &X) { points_[track].X = X; } -EuclideanCamera *EuclideanReconstruction::CameraForImage(int image) { - return const_cast<EuclideanCamera *>( - static_cast<const EuclideanReconstruction *>( - this)->CameraForImage(image)); +EuclideanCamera* EuclideanReconstruction::CameraForImage(int image) { + return const_cast<EuclideanCamera*>( + static_cast<const EuclideanReconstruction*>(this)->CameraForImage(image)); } -const EuclideanCamera *EuclideanReconstruction::CameraForImage( +const EuclideanCamera* EuclideanReconstruction::CameraForImage( int image) const { ImageToCameraMap::const_iterator it = image_to_cameras_map_.find(image); if (it == image_to_cameras_map_.end()) { @@ -86,16 +86,16 @@ vector<EuclideanCamera> EuclideanReconstruction::AllCameras() const { return cameras; } -EuclideanPoint *EuclideanReconstruction::PointForTrack(int track) { - return const_cast<EuclideanPoint *>( - static_cast<const EuclideanReconstruction *>(this)->PointForTrack(track)); +EuclideanPoint* EuclideanReconstruction::PointForTrack(int track) { + return const_cast<EuclideanPoint*>( + static_cast<const EuclideanReconstruction*>(this)->PointForTrack(track)); } -const EuclideanPoint *EuclideanReconstruction::PointForTrack(int track) const { +const EuclideanPoint* EuclideanReconstruction::PointForTrack(int track) const { if (track < 0 || track >= points_.size()) { return NULL; } - const EuclideanPoint *point = &points_[track]; + const EuclideanPoint* point = &points_[track]; if (point->track == -1) { return NULL; } @@ -112,8 +112,8 @@ vector<EuclideanPoint> EuclideanReconstruction::AllPoints() const { return points; } -void ProjectiveReconstruction::InsertCamera(int image, const Mat34 &P) { - LG << "InsertCamera " << image << ":\nP:\n"<< P; +void ProjectiveReconstruction::InsertCamera(int image, const Mat34& P) { + LG << "InsertCamera " << image << ":\nP:\n" << P; ProjectiveCamera camera; camera.image = image; @@ -122,7 +122,7 @@ void ProjectiveReconstruction::InsertCamera(int image, const Mat34 &P) { image_to_cameras_map_.insert(make_pair(image, camera)); } -void ProjectiveReconstruction::InsertPoint(int track, const Vec4 &X) { +void ProjectiveReconstruction::InsertPoint(int track, const Vec4& X) { LG << "InsertPoint " << track << ":\n" << X; if (track >= points_.size()) { points_.resize(track + 1); @@ -131,17 +131,17 @@ void ProjectiveReconstruction::InsertPoint(int track, const Vec4 &X) { points_[track].X = X; } -ProjectiveCamera *ProjectiveReconstruction::CameraForImage(int image) { - return const_cast<ProjectiveCamera *>( - static_cast<const ProjectiveReconstruction *>( - this)->CameraForImage(image)); +ProjectiveCamera* ProjectiveReconstruction::CameraForImage(int image) { + return const_cast<ProjectiveCamera*>( + static_cast<const ProjectiveReconstruction*>(this)->CameraForImage( + image)); } -const ProjectiveCamera *ProjectiveReconstruction::CameraForImage( +const ProjectiveCamera* ProjectiveReconstruction::CameraForImage( int image) const { ImageToCameraMap::const_iterator it = image_to_cameras_map_.find(image); if (it == image_to_cameras_map_.end()) { - return NULL; + return NULL; } return &it->second; } @@ -155,16 +155,17 @@ vector<ProjectiveCamera> ProjectiveReconstruction::AllCameras() const { return cameras; } -ProjectivePoint *ProjectiveReconstruction::PointForTrack(int track) { - return const_cast<ProjectivePoint *>( - static_cast<const ProjectiveReconstruction *>(this)->PointForTrack(track)); +ProjectivePoint* ProjectiveReconstruction::PointForTrack(int track) { + return const_cast<ProjectivePoint*>( + static_cast<const ProjectiveReconstruction*>(this)->PointForTrack(track)); } -const ProjectivePoint *ProjectiveReconstruction::PointForTrack(int track) const { +const ProjectivePoint* ProjectiveReconstruction::PointForTrack( + int track) const { if (track < 0 || track >= points_.size()) { return NULL; } - const ProjectivePoint *point = &points_[track]; + const ProjectivePoint* point = &points_[track]; if (point->track == -1) { return NULL; } diff --git a/intern/libmv/libmv/simple_pipeline/reconstruction.h b/intern/libmv/libmv/simple_pipeline/reconstruction.h index 544aeac042e..56b2ba34c91 100644 --- a/intern/libmv/libmv/simple_pipeline/reconstruction.h +++ b/intern/libmv/libmv/simple_pipeline/reconstruction.h @@ -21,14 +21,15 @@ #ifndef LIBMV_SIMPLE_PIPELINE_RECONSTRUCTION_H_ #define LIBMV_SIMPLE_PIPELINE_RECONSTRUCTION_H_ -#include "libmv/base/vector.h" #include "libmv/base/map.h" +#include "libmv/base/vector.h" #include "libmv/numeric/numeric.h" namespace libmv { /*! - A EuclideanCamera is the location and rotation of the camera viewing \a image. + A EuclideanCamera is the location and rotation of the camera viewing \a + image. \a image identify which image from \link Tracks this camera represents. \a R is a 3x3 matrix representing the rotation of the camera. @@ -38,7 +39,7 @@ namespace libmv { */ struct EuclideanCamera { EuclideanCamera() : image(-1) {} - EuclideanCamera(const EuclideanCamera &c) : image(c.image), R(c.R), t(c.t) {} + EuclideanCamera(const EuclideanCamera& c) : image(c.image), R(c.R), t(c.t) {} int image; Mat3 R; @@ -55,7 +56,7 @@ struct EuclideanCamera { */ struct EuclideanPoint { EuclideanPoint() : track(-1) {} - EuclideanPoint(const EuclideanPoint &p) : track(p.track), X(p.X) {} + EuclideanPoint(const EuclideanPoint& p) : track(p.track), X(p.X) {} int track; Vec3 X; }; @@ -78,9 +79,9 @@ class EuclideanReconstruction { EuclideanReconstruction(); /// Copy constructor. - EuclideanReconstruction(const EuclideanReconstruction &other); + EuclideanReconstruction(const EuclideanReconstruction& other); - EuclideanReconstruction &operator=(const EuclideanReconstruction &other); + EuclideanReconstruction& operator=(const EuclideanReconstruction& other); /*! Insert a camera into the set. If there is already a camera for the given @@ -92,7 +93,7 @@ class EuclideanReconstruction { \note You should use the same \a image identifier as in \link Tracks. */ - void InsertCamera(int image, const Mat3 &R, const Vec3 &t); + void InsertCamera(int image, const Mat3& R, const Vec3& t); /*! Insert a point into the reconstruction. If there is already a point for @@ -104,18 +105,18 @@ class EuclideanReconstruction { \note You should use the same \a track identifier as in \link Tracks. */ - void InsertPoint(int track, const Vec3 &X); + void InsertPoint(int track, const Vec3& X); /// Returns a pointer to the camera corresponding to \a image. - EuclideanCamera *CameraForImage(int image); - const EuclideanCamera *CameraForImage(int image) const; + EuclideanCamera* CameraForImage(int image); + const EuclideanCamera* CameraForImage(int image) const; /// Returns all cameras. vector<EuclideanCamera> AllCameras() const; /// Returns a pointer to the point corresponding to \a track. - EuclideanPoint *PointForTrack(int track); - const EuclideanPoint *PointForTrack(int track) const; + EuclideanPoint* PointForTrack(int track); + const EuclideanPoint* PointForTrack(int track) const; /// Returns all points. vector<EuclideanPoint> AllPoints() const; @@ -139,7 +140,7 @@ class EuclideanReconstruction { */ struct ProjectiveCamera { ProjectiveCamera() : image(-1) {} - ProjectiveCamera(const ProjectiveCamera &c) : image(c.image), P(c.P) {} + ProjectiveCamera(const ProjectiveCamera& c) : image(c.image), P(c.P) {} int image; Mat34 P; @@ -155,7 +156,7 @@ struct ProjectiveCamera { */ struct ProjectivePoint { ProjectivePoint() : track(-1) {} - ProjectivePoint(const ProjectivePoint &p) : track(p.track), X(p.X) {} + ProjectivePoint(const ProjectivePoint& p) : track(p.track), X(p.X) {} int track; Vec4 X; }; @@ -184,7 +185,7 @@ class ProjectiveReconstruction { \note You should use the same \a image identifier as in \link Tracks. */ - void InsertCamera(int image, const Mat34 &P); + void InsertCamera(int image, const Mat34& P); /*! Insert a point into the reconstruction. If there is already a point for @@ -196,18 +197,18 @@ class ProjectiveReconstruction { \note You should use the same \a track identifier as in \link Tracks. */ - void InsertPoint(int track, const Vec4 &X); + void InsertPoint(int track, const Vec4& X); /// Returns a pointer to the camera corresponding to \a image. - ProjectiveCamera *CameraForImage(int image); - const ProjectiveCamera *CameraForImage(int image) const; + ProjectiveCamera* CameraForImage(int image); + const ProjectiveCamera* CameraForImage(int image) const; /// Returns all cameras. vector<ProjectiveCamera> AllCameras() const; /// Returns a pointer to the point corresponding to \a track. - ProjectivePoint *PointForTrack(int track); - const ProjectivePoint *PointForTrack(int track) const; + ProjectivePoint* PointForTrack(int track); + const ProjectivePoint* PointForTrack(int track) const; /// Returns all points. vector<ProjectivePoint> AllPoints() const; diff --git a/intern/libmv/libmv/simple_pipeline/reconstruction_scale.cc b/intern/libmv/libmv/simple_pipeline/reconstruction_scale.cc index 40ac23be7a2..04fbb536d31 100644 --- a/intern/libmv/libmv/simple_pipeline/reconstruction_scale.cc +++ b/intern/libmv/libmv/simple_pipeline/reconstruction_scale.cc @@ -23,7 +23,7 @@ namespace libmv { -void EuclideanScaleToUnity(EuclideanReconstruction *reconstruction) { +void EuclideanScaleToUnity(EuclideanReconstruction* reconstruction) { vector<EuclideanCamera> all_cameras = reconstruction->AllCameras(); vector<EuclideanPoint> all_points = reconstruction->AllPoints(); @@ -53,14 +53,14 @@ void EuclideanScaleToUnity(EuclideanReconstruction *reconstruction) { // Rescale cameras positions. for (int i = 0; i < all_cameras.size(); ++i) { int image = all_cameras[i].image; - EuclideanCamera *camera = reconstruction->CameraForImage(image); + EuclideanCamera* camera = reconstruction->CameraForImage(image); camera->t = camera->t * scale_factor; } // Rescale points positions. for (int i = 0; i < all_points.size(); ++i) { int track = all_points[i].track; - EuclideanPoint *point = reconstruction->PointForTrack(track); + EuclideanPoint* point = reconstruction->PointForTrack(track); point->X = point->X * scale_factor; } } diff --git a/intern/libmv/libmv/simple_pipeline/reconstruction_scale.h b/intern/libmv/libmv/simple_pipeline/reconstruction_scale.h index f2349ff5146..c164878ee25 100644 --- a/intern/libmv/libmv/simple_pipeline/reconstruction_scale.h +++ b/intern/libmv/libmv/simple_pipeline/reconstruction_scale.h @@ -29,7 +29,7 @@ namespace libmv { Scale euclidean reconstruction in a way variance of camera centers equals to one. */ -void EuclideanScaleToUnity(EuclideanReconstruction *reconstruction); +void EuclideanScaleToUnity(EuclideanReconstruction* reconstruction); } // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/resect.cc b/intern/libmv/libmv/simple_pipeline/resect.cc index e73fc44df2a..b5736767edd 100644 --- a/intern/libmv/libmv/simple_pipeline/resect.cc +++ b/intern/libmv/libmv/simple_pipeline/resect.cc @@ -25,17 +25,17 @@ #include "libmv/base/vector.h" #include "libmv/logging/logging.h" #include "libmv/multiview/euclidean_resection.h" -#include "libmv/multiview/resection.h" #include "libmv/multiview/projection.h" -#include "libmv/numeric/numeric.h" +#include "libmv/multiview/resection.h" #include "libmv/numeric/levenberg_marquardt.h" +#include "libmv/numeric/numeric.h" #include "libmv/simple_pipeline/reconstruction.h" #include "libmv/simple_pipeline/tracks.h" namespace libmv { namespace { -Mat2X PointMatrixFromMarkers(const vector<Marker> &markers) { +Mat2X PointMatrixFromMarkers(const vector<Marker>& markers) { Mat2X points(2, markers.size()); for (int i = 0; i < markers.size(); ++i) { points(0, i) = markers[i].x; @@ -53,19 +53,19 @@ Mat2X PointMatrixFromMarkers(const vector<Marker> &markers) { // axis to rotate around and the magnitude is the amount of the rotation. struct EuclideanResectCostFunction { public: - typedef Vec FMatrixType; + typedef Vec FMatrixType; typedef Vec6 XMatrixType; - EuclideanResectCostFunction(const vector<Marker> &markers, - const EuclideanReconstruction &reconstruction, - const Mat3 &initial_R) - : markers(markers), - reconstruction(reconstruction), - initial_R(initial_R) {} + EuclideanResectCostFunction(const vector<Marker>& markers, + const EuclideanReconstruction& reconstruction, + const Mat3& initial_R) + : markers(markers), + reconstruction(reconstruction), + initial_R(initial_R) {} // dRt has dR (delta R) encoded as a euler vector in the first 3 parameters, // followed by t in the next 3 parameters. - Vec operator()(const Vec6 &dRt) const { + Vec operator()(const Vec6& dRt) const { // Unpack R, t from dRt. Mat3 R = RotationFromEulerVector(dRt.head<3>()) * initial_R; Vec3 t = dRt.tail<3>(); @@ -74,25 +74,26 @@ struct EuclideanResectCostFunction { Vec residuals(2 * markers.size()); residuals.setZero(); for (int i = 0; i < markers.size(); ++i) { - const EuclideanPoint &point = + const EuclideanPoint& point = *reconstruction.PointForTrack(markers[i].track); Vec3 projected = R * point.X + t; projected /= projected(2); - residuals[2*i + 0] = projected(0) - markers[i].x; - residuals[2*i + 1] = projected(1) - markers[i].y; + residuals[2 * i + 0] = projected(0) - markers[i].x; + residuals[2 * i + 1] = projected(1) - markers[i].y; } return residuals; } - const vector<Marker> &markers; - const EuclideanReconstruction &reconstruction; - const Mat3 &initial_R; + const vector<Marker>& markers; + const EuclideanReconstruction& reconstruction; + const Mat3& initial_R; }; } // namespace -bool EuclideanResect(const vector<Marker> &markers, - EuclideanReconstruction *reconstruction, bool final_pass) { +bool EuclideanResect(const vector<Marker>& markers, + EuclideanReconstruction* reconstruction, + bool final_pass) { if (markers.size() < 5) { return false; } @@ -106,9 +107,9 @@ bool EuclideanResect(const vector<Marker> &markers, Mat3 R; Vec3 t; - if (0 || !euclidean_resection::EuclideanResection( - points_2d, points_3d, &R, &t, - euclidean_resection::RESECTION_EPNP)) { + if (0 || + !euclidean_resection::EuclideanResection( + points_2d, points_3d, &R, &t, euclidean_resection::RESECTION_EPNP)) { // printf("Resection for image %d failed\n", markers[0].image); LG << "Resection for image " << markers[0].image << " failed;" << " trying fallback projective resection."; @@ -116,7 +117,8 @@ bool EuclideanResect(const vector<Marker> &markers, LG << "No fallback; failing resection for " << markers[0].image; return false; - if (!final_pass) return false; + if (!final_pass) + return false; // Euclidean resection failed. Fall back to projective resection, which is // less reliable but better conditioned when there are many points. Mat34 P; @@ -173,7 +175,9 @@ bool EuclideanResect(const vector<Marker> &markers, t = dRt.tail<3>(); LG << "Resection for image " << markers[0].image << " got:\n" - << "R:\n" << R << "\nt:\n" << t; + << "R:\n" + << R << "\nt:\n" + << t; reconstruction->InsertCamera(markers[0].image, R, t); return true; } @@ -186,15 +190,14 @@ namespace { // freedom drift. struct ProjectiveResectCostFunction { public: - typedef Vec FMatrixType; + typedef Vec FMatrixType; typedef Vec12 XMatrixType; - ProjectiveResectCostFunction(const vector<Marker> &markers, - const ProjectiveReconstruction &reconstruction) - : markers(markers), - reconstruction(reconstruction) {} + ProjectiveResectCostFunction(const vector<Marker>& markers, + const ProjectiveReconstruction& reconstruction) + : markers(markers), reconstruction(reconstruction) {} - Vec operator()(const Vec12 &vector_P) const { + Vec operator()(const Vec12& vector_P) const { // Unpack P from vector_P. Map<const Mat34> P(vector_P.data(), 3, 4); @@ -202,24 +205,24 @@ struct ProjectiveResectCostFunction { Vec residuals(2 * markers.size()); residuals.setZero(); for (int i = 0; i < markers.size(); ++i) { - const ProjectivePoint &point = + const ProjectivePoint& point = *reconstruction.PointForTrack(markers[i].track); Vec3 projected = P * point.X; projected /= projected(2); - residuals[2*i + 0] = projected(0) - markers[i].x; - residuals[2*i + 1] = projected(1) - markers[i].y; + residuals[2 * i + 0] = projected(0) - markers[i].x; + residuals[2 * i + 1] = projected(1) - markers[i].y; } return residuals; } - const vector<Marker> &markers; - const ProjectiveReconstruction &reconstruction; + const vector<Marker>& markers; + const ProjectiveReconstruction& reconstruction; }; } // namespace -bool ProjectiveResect(const vector<Marker> &markers, - ProjectiveReconstruction *reconstruction) { +bool ProjectiveResect(const vector<Marker>& markers, + ProjectiveReconstruction* reconstruction) { if (markers.size() < 5) { return false; } @@ -263,7 +266,8 @@ bool ProjectiveResect(const vector<Marker> &markers, P = Map<Mat34>(vector_P.data(), 3, 4); LG << "Resection for image " << markers[0].image << " got:\n" - << "P:\n" << P; + << "P:\n" + << P; reconstruction->InsertCamera(markers[0].image, P); return true; } diff --git a/intern/libmv/libmv/simple_pipeline/resect.h b/intern/libmv/libmv/simple_pipeline/resect.h index f13d2e2d425..13c3d66bd37 100644 --- a/intern/libmv/libmv/simple_pipeline/resect.h +++ b/intern/libmv/libmv/simple_pipeline/resect.h @@ -22,8 +22,8 @@ #define LIBMV_SIMPLE_PIPELINE_RESECT_H #include "libmv/base/vector.h" -#include "libmv/simple_pipeline/tracks.h" #include "libmv/simple_pipeline/reconstruction.h" +#include "libmv/simple_pipeline/tracks.h" namespace libmv { @@ -51,8 +51,9 @@ namespace libmv { \sa EuclideanIntersect, EuclideanReconstructTwoFrames */ -bool EuclideanResect(const vector<Marker> &markers, - EuclideanReconstruction *reconstruction, bool final_pass); +bool EuclideanResect(const vector<Marker>& markers, + EuclideanReconstruction* reconstruction, + bool final_pass); /*! Estimate the projective pose of a camera from 2D to 3D correspondences. @@ -78,8 +79,8 @@ bool EuclideanResect(const vector<Marker> &markers, \sa ProjectiveIntersect, ProjectiveReconstructTwoFrames */ -bool ProjectiveResect(const vector<Marker> &markers, - ProjectiveReconstruction *reconstruction); +bool ProjectiveResect(const vector<Marker>& markers, + ProjectiveReconstruction* reconstruction); } // namespace libmv diff --git a/intern/libmv/libmv/simple_pipeline/resect_test.cc b/intern/libmv/libmv/simple_pipeline/resect_test.cc index 811edd282d8..ecf3f9b673d 100644 --- a/intern/libmv/libmv/simple_pipeline/resect_test.cc +++ b/intern/libmv/libmv/simple_pipeline/resect_test.cc @@ -153,7 +153,7 @@ TEST(EuclideanResection, Points4KnownImagePointsRandomTranslationRotation) { // not precise enough with only 4 points. // // TODO(jmichot): Reenable this test when there is nonlinear refinement. -#if 0 +# if 0 R_output.setIdentity(); T_output.setZero(); @@ -163,7 +163,7 @@ TEST(EuclideanResection, Points4KnownImagePointsRandomTranslationRotation) { EXPECT_MATRIX_NEAR(T_output, T_expected, 1e-5); EXPECT_MATRIX_NEAR(R_output, R_expected, 1e-7);*/ -#endif +# endif } // TODO(jmichot): Reduce the code duplication here with the code above. diff --git a/intern/libmv/libmv/simple_pipeline/tracks.cc b/intern/libmv/libmv/simple_pipeline/tracks.cc index d5d009708ba..66243807a4b 100644 --- a/intern/libmv/libmv/simple_pipeline/tracks.cc +++ b/intern/libmv/libmv/simple_pipeline/tracks.cc @@ -21,31 +21,31 @@ #include "libmv/simple_pipeline/tracks.h" #include <algorithm> -#include <vector> #include <iterator> +#include <vector> #include "libmv/numeric/numeric.h" namespace libmv { -Tracks::Tracks(const Tracks &other) { +Tracks::Tracks(const Tracks& other) { markers_ = other.markers_; } -Tracks::Tracks(const vector<Marker> &markers) : markers_(markers) {} +Tracks::Tracks(const vector<Marker>& markers) : markers_(markers) { +} void Tracks::Insert(int image, int track, double x, double y, double weight) { // TODO(keir): Wow, this is quadratic for repeated insertions. Fix this by // adding a smarter data structure like a set<>. for (int i = 0; i < markers_.size(); ++i) { - if (markers_[i].image == image && - markers_[i].track == track) { + if (markers_[i].image == image && markers_[i].track == track) { markers_[i].x = x; markers_[i].y = y; return; } } - Marker marker = { image, track, x, y, weight }; + Marker marker = {image, track, x, y, weight}; markers_.push_back(marker); } @@ -101,15 +101,17 @@ vector<Marker> Tracks::MarkersForTracksInBothImages(int image1, std::sort(image2_tracks.begin(), image2_tracks.end()); std::vector<int> intersection; - std::set_intersection(image1_tracks.begin(), image1_tracks.end(), - image2_tracks.begin(), image2_tracks.end(), + std::set_intersection(image1_tracks.begin(), + image1_tracks.end(), + image2_tracks.begin(), + image2_tracks.end(), std::back_inserter(intersection)); vector<Marker> markers; for (int i = 0; i < markers_.size(); ++i) { if ((markers_[i].image == image1 || markers_[i].image == image2) && - std::binary_search(intersection.begin(), intersection.end(), - markers_[i].track)) { + std::binary_search( + intersection.begin(), intersection.end(), markers_[i].track)) { markers.push_back(markers_[i]); } } @@ -122,7 +124,7 @@ Marker Tracks::MarkerInImageForTrack(int image, int track) const { return markers_[i]; } } - Marker null = { -1, -1, -1, -1, 0.0 }; + Marker null = {-1, -1, -1, -1, 0.0}; return null; } @@ -168,12 +170,12 @@ int Tracks::NumMarkers() const { return markers_.size(); } -void CoordinatesForMarkersInImage(const vector<Marker> &markers, +void CoordinatesForMarkersInImage(const vector<Marker>& markers, int image, - Mat *coordinates) { + Mat* coordinates) { vector<Vec2> coords; for (int i = 0; i < markers.size(); ++i) { - const Marker &marker = markers[i]; + const Marker& marker = markers[i]; if (markers[i].image == image) { coords.push_back(Vec2(marker.x, marker.y)); } diff --git a/intern/libmv/libmv/simple_pipeline/tracks.h b/intern/libmv/libmv/simple_pipeline/tracks.h index 752d2790a1c..c3df3a223d8 100644 --- a/intern/libmv/libmv/simple_pipeline/tracks.h +++ b/intern/libmv/libmv/simple_pipeline/tracks.h @@ -36,7 +36,8 @@ namespace libmv { \a weight is used by bundle adjustment and weight means how much the track affects on a final solution. - \note Markers are typically aggregated with the help of the \link Tracks class. + \note Markers are typically aggregated with the help of the \link Tracks + class. \sa Tracks */ @@ -56,19 +57,20 @@ struct Marker { images, which must get created before any 3D reconstruction can take place. The container has several fast lookups for queries typically needed for - structure from motion algorithms, such as \link MarkersForTracksInBothImages(). + structure from motion algorithms, such as \link + MarkersForTracksInBothImages(). \sa Marker */ class Tracks { public: - Tracks() { } + Tracks() {} // Copy constructor for a tracks object. - Tracks(const Tracks &other); + Tracks(const Tracks& other); /// Construct a new tracks object using the given markers to start. - explicit Tracks(const vector<Marker> &markers); + explicit Tracks(const vector<Marker>& markers); /*! Inserts a marker into the set. If there is already a marker for the given @@ -129,9 +131,9 @@ class Tracks { vector<Marker> markers_; }; -void CoordinatesForMarkersInImage(const vector<Marker> &markers, +void CoordinatesForMarkersInImage(const vector<Marker>& markers, int image, - Mat *coordinates); + Mat* coordinates); } // namespace libmv diff --git a/intern/libmv/libmv/threading/threading.h b/intern/libmv/libmv/threading/threading.h index f23bf6f172c..da625e02424 100644 --- a/intern/libmv/libmv/threading/threading.h +++ b/intern/libmv/libmv/threading/threading.h @@ -31,7 +31,7 @@ namespace libmv { #if COMPILER_SUPPORTS_CXX11 -using mutex = std::mutex; +using mutex = std::mutex; using scoped_lock = std::unique_lock<std::mutex>; using condition_variable = std::condition_variable; #else diff --git a/intern/libmv/libmv/tracking/brute_region_tracker.cc b/intern/libmv/libmv/tracking/brute_region_tracker.cc index 85aecb7f633..7007fb9440b 100644 --- a/intern/libmv/libmv/tracking/brute_region_tracker.cc +++ b/intern/libmv/libmv/tracking/brute_region_tracker.cc @@ -25,31 +25,30 @@ #endif #include "libmv/base/aligned_malloc.h" -#include "libmv/image/image.h" #include "libmv/image/convolve.h" #include "libmv/image/correlation.h" +#include "libmv/image/image.h" #include "libmv/image/sample.h" #include "libmv/logging/logging.h" namespace libmv { namespace { -bool RegionIsInBounds(const FloatImage &image1, - double x, double y, +bool RegionIsInBounds(const FloatImage& image1, + double x, + double y, int half_window_size) { // Check the minimum coordinates. int min_x = floor(x) - half_window_size - 1; int min_y = floor(y) - half_window_size - 1; - if (min_x < 0.0 || - min_y < 0.0) { + if (min_x < 0.0 || min_y < 0.0) { return false; } // Check the maximum coordinates. int max_x = ceil(x) + half_window_size + 1; int max_y = ceil(y) + half_window_size + 1; - if (max_x > image1.cols() || - max_y > image1.rows()) { + if (max_x > image1.cols() || max_y > image1.rows()) { return false; } @@ -69,14 +68,15 @@ bool RegionIsInBounds(const FloatImage &image1, // and "b", since the SSE load instructionst will pull in memory past the end // of the arrays if their size is not a multiple of 16. inline static __m128i SumOfAbsoluteDifferencesContiguousSSE( - const unsigned char *a, // aligned - const unsigned char *b, // not aligned + const unsigned char* a, // aligned + const unsigned char* b, // not aligned unsigned int size, __m128i sad) { // Do the bulk of the work as 16-way integer operations. for (unsigned int j = 0; j < size / 16; j++) { - sad = _mm_add_epi32(sad, _mm_sad_epu8( _mm_load_si128 ((__m128i*)(a + 16 * j)), - _mm_loadu_si128((__m128i*)(b + 16 * j)))); + sad = _mm_add_epi32(sad, + _mm_sad_epu8(_mm_load_si128((__m128i*)(a + 16 * j)), + _mm_loadu_si128((__m128i*)(b + 16 * j)))); } // Handle the trailing end. // TODO(keir): Benchmark to verify that the below SSE is a win compared to a @@ -90,32 +90,63 @@ inline static __m128i SumOfAbsoluteDifferencesContiguousSSE( unsigned int remainder = size % 16u; if (remainder) { unsigned int j = size / 16; - __m128i a_trail = _mm_load_si128 ((__m128i*)(a + 16 * j)); + __m128i a_trail = _mm_load_si128((__m128i*)(a + 16 * j)); __m128i b_trail = _mm_loadu_si128((__m128i*)(b + 16 * j)); __m128i mask; switch (remainder) { -#define X 0xff - case 1: mask = _mm_setr_epi8(X, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); break; - case 2: mask = _mm_setr_epi8(X, X, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); break; - case 3: mask = _mm_setr_epi8(X, X, X, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); break; - case 4: mask = _mm_setr_epi8(X, X, X, X, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); break; - case 5: mask = _mm_setr_epi8(X, X, X, X, X, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); break; - case 6: mask = _mm_setr_epi8(X, X, X, X, X, X, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); break; - case 7: mask = _mm_setr_epi8(X, X, X, X, X, X, X, 0, 0, 0, 0, 0, 0, 0, 0, 0); break; - case 8: mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, 0, 0, 0, 0, 0, 0, 0, 0); break; - case 9: mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, 0, 0, 0, 0, 0, 0, 0); break; - case 10: mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, X, 0, 0, 0, 0, 0, 0); break; - case 11: mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, X, X, 0, 0, 0, 0, 0); break; - case 12: mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, X, X, X, 0, 0, 0, 0); break; - case 13: mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, X, X, X, X, 0, 0, 0); break; - case 14: mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, X, X, X, X, X, 0, 0); break; - case 15: mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, X, X, X, X, X, X, 0); break; +# define X 0xff + case 1: + mask = _mm_setr_epi8(X, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); + break; + case 2: + mask = _mm_setr_epi8(X, X, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); + break; + case 3: + mask = _mm_setr_epi8(X, X, X, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); + break; + case 4: + mask = _mm_setr_epi8(X, X, X, X, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); + break; + case 5: + mask = _mm_setr_epi8(X, X, X, X, X, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); + break; + case 6: + mask = _mm_setr_epi8(X, X, X, X, X, X, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); + break; + case 7: + mask = _mm_setr_epi8(X, X, X, X, X, X, X, 0, 0, 0, 0, 0, 0, 0, 0, 0); + break; + case 8: + mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, 0, 0, 0, 0, 0, 0, 0, 0); + break; + case 9: + mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, 0, 0, 0, 0, 0, 0, 0); + break; + case 10: + mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, X, 0, 0, 0, 0, 0, 0); + break; + case 11: + mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, X, X, 0, 0, 0, 0, 0); + break; + case 12: + mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, X, X, X, 0, 0, 0, 0); + break; + case 13: + mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, X, X, X, X, 0, 0, 0); + break; + case 14: + mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, X, X, X, X, X, 0, 0); + break; + case 15: + mask = _mm_setr_epi8(X, X, X, X, X, X, X, X, X, X, X, X, X, X, X, 0); + break; // To silence compiler warning. default: mask = _mm_setzero_si128(); break; -#undef X +# undef X } - sad = _mm_add_epi32(sad, _mm_sad_epu8(_mm_and_si128(mask, a_trail), - _mm_and_si128(mask, b_trail))); + sad = _mm_add_epi32(sad, + _mm_sad_epu8(_mm_and_si128(mask, a_trail), + _mm_and_si128(mask, b_trail))); } return sad; } @@ -124,13 +155,12 @@ inline static __m128i SumOfAbsoluteDifferencesContiguousSSE( // Computes the sum of absolute differences between pattern and image. Pattern // must be 16-byte aligned, and the stride must be a multiple of 16. The image // does pointer does not have to be aligned. -int SumOfAbsoluteDifferencesContiguousImage( - const unsigned char *pattern, - unsigned int pattern_width, - unsigned int pattern_height, - unsigned int pattern_stride, - const unsigned char *image, - unsigned int image_stride) { +int SumOfAbsoluteDifferencesContiguousImage(const unsigned char* pattern, + unsigned int pattern_width, + unsigned int pattern_height, + unsigned int pattern_stride, + const unsigned char* image, + unsigned int image_stride) { #ifdef __SSE2__ // TODO(keir): Add interleaved accumulation, where accumulation is done into // two or more SSE registers that then get combined at the end. This reduces @@ -145,8 +175,7 @@ int SumOfAbsoluteDifferencesContiguousImage( sad); } return _mm_cvtsi128_si32( - _mm_add_epi32(sad, - _mm_shuffle_epi32(sad, _MM_SHUFFLE(3, 0, 1, 2)))); + _mm_add_epi32(sad, _mm_shuffle_epi32(sad, _MM_SHUFFLE(3, 0, 1, 2)))); #else int sad = 0; for (int r = 0; r < pattern_height; ++r) { @@ -161,12 +190,13 @@ int SumOfAbsoluteDifferencesContiguousImage( // Sample a region of size width, height centered at x,y in image, converting // from float to byte in the process. Samples from the first channel. Puts // result into *pattern. -void SampleRectangularPattern(const FloatImage &image, - double x, double y, +void SampleRectangularPattern(const FloatImage& image, + double x, + double y, int width, int height, int pattern_stride, - unsigned char *pattern) { + unsigned char* pattern) { // There are two cases for width and height: even or odd. If it's odd, then // the bounds [-width / 2, width / 2] works as expected. However, for even, // this results in one extra access past the end. So use < instead of <= in @@ -175,7 +205,7 @@ void SampleRectangularPattern(const FloatImage &image, int end_height = (height / 2) + (height % 2); for (int r = -height / 2; r < end_height; ++r) { for (int c = -width / 2; c < end_width; ++c) { - pattern[pattern_stride * (r + height / 2) + c + width / 2] = + pattern[pattern_stride * (r + height / 2) + c + width / 2] = SampleLinear(image, y + r, x + c, 0) * 255.0; } } @@ -195,30 +225,30 @@ inline int PadToAlignment(int x, int alignment) { // is returned in *pattern_stride. // // NOTE: Caller must free *pattern with aligned_malloc() from above. -void SampleSquarePattern(const FloatImage &image, - double x, double y, +void SampleSquarePattern(const FloatImage& image, + double x, + double y, int half_width, - unsigned char **pattern, - int *pattern_stride) { + unsigned char** pattern, + int* pattern_stride) { int width = 2 * half_width + 1; // Allocate an aligned block with padding on the end so each row of the // pattern starts on a 16-byte boundary. *pattern_stride = PadToAlignment(width, 16); int pattern_size_bytes = *pattern_stride * width; - *pattern = static_cast<unsigned char *>( - aligned_malloc(pattern_size_bytes, 16)); - SampleRectangularPattern(image, x, y, width, width, - *pattern_stride, - *pattern); + *pattern = + static_cast<unsigned char*>(aligned_malloc(pattern_size_bytes, 16)); + SampleRectangularPattern( + image, x, y, width, width, *pattern_stride, *pattern); } // NOTE: Caller must free *image with aligned_malloc() from above. -void FloatArrayToByteArrayWithPadding(const FloatImage &float_image, - unsigned char **image, - int *image_stride) { +void FloatArrayToByteArrayWithPadding(const FloatImage& float_image, + unsigned char** image, + int* image_stride) { // Allocate enough so that accessing 16 elements past the end is fine. *image_stride = float_image.Width() + 16; - *image = static_cast<unsigned char *>( + *image = static_cast<unsigned char*>( aligned_malloc(*image_stride * float_image.Height(), 16)); for (int i = 0; i < float_image.Height(); ++i) { for (int j = 0; j < float_image.Width(); ++j) { @@ -235,10 +265,12 @@ void FloatArrayToByteArrayWithPadding(const FloatImage &float_image, // values for every hypothesis looks like. // // TODO(keir): Priority queue for multiple hypothesis. -bool BruteRegionTracker::Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const { +bool BruteRegionTracker::Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const { if (!RegionIsInBounds(image1, x1, y1, half_window_size)) { LG << "Fell out of image1's window with x1=" << x1 << ", y1=" << y1 << ", hw=" << half_window_size << "."; @@ -252,28 +284,28 @@ bool BruteRegionTracker::Track(const FloatImage &image1, BlurredImageAndDerivativesChannels(image2, 0.9, &image_and_gradient2); // Sample the pattern to get it aligned to an image grid. - unsigned char *pattern; + unsigned char* pattern; int pattern_stride; - SampleSquarePattern(image_and_gradient1, x1, y1, half_window_size, - &pattern, - &pattern_stride); + SampleSquarePattern( + image_and_gradient1, x1, y1, half_window_size, &pattern, &pattern_stride); // Convert the search area directly to bytes without sampling. - unsigned char *search_area; + unsigned char* search_area; int search_area_stride; - FloatArrayToByteArrayWithPadding(image_and_gradient2, &search_area, - &search_area_stride); + FloatArrayToByteArrayWithPadding( + image_and_gradient2, &search_area, &search_area_stride); // Try all possible locations inside the search area. Yes, everywhere. int best_i = -1, best_j = -1, best_sad = INT_MAX; for (int i = 0; i < image2.Height() - pattern_width; ++i) { for (int j = 0; j < image2.Width() - pattern_width; ++j) { - int sad = SumOfAbsoluteDifferencesContiguousImage(pattern, - pattern_width, - pattern_width, - pattern_stride, - search_area + search_area_stride * i + j, - search_area_stride); + int sad = SumOfAbsoluteDifferencesContiguousImage( + pattern, + pattern_width, + pattern_width, + pattern_stride, + search_area + search_area_stride * i + j, + search_area_stride); if (sad < best_sad) { best_i = i; best_j = j; @@ -309,16 +341,23 @@ bool BruteRegionTracker::Track(const FloatImage &image1, } Array3Df image_and_gradient1_sampled, image_and_gradient2_sampled; - SamplePattern(image_and_gradient1, x1, y1, half_window_size, 3, + SamplePattern(image_and_gradient1, + x1, + y1, + half_window_size, + 3, &image_and_gradient1_sampled); - SamplePattern(image_and_gradient2, *x2, *y2, half_window_size, 3, + SamplePattern(image_and_gradient2, + *x2, + *y2, + half_window_size, + 3, &image_and_gradient2_sampled); // Compute the Pearson product-moment correlation coefficient to check // for sanity. double correlation = PearsonProductMomentCorrelation( - image_and_gradient1_sampled, - image_and_gradient2_sampled); + image_and_gradient1_sampled, image_and_gradient2_sampled); LG << "Final correlation: " << correlation; diff --git a/intern/libmv/libmv/tracking/brute_region_tracker.h b/intern/libmv/libmv/tracking/brute_region_tracker.h index a699c42ee92..183dc6df07b 100644 --- a/intern/libmv/libmv/tracking/brute_region_tracker.h +++ b/intern/libmv/libmv/tracking/brute_region_tracker.h @@ -27,17 +27,17 @@ namespace libmv { struct BruteRegionTracker : public RegionTracker { - BruteRegionTracker() - : half_window_size(4), - minimum_correlation(0.78) {} + BruteRegionTracker() : half_window_size(4), minimum_correlation(0.78) {} virtual ~BruteRegionTracker() {} // Tracker interface. - virtual bool Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const; + virtual bool Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const; // No point in creating getters or setters. int half_window_size; diff --git a/intern/libmv/libmv/tracking/hybrid_region_tracker.cc b/intern/libmv/libmv/tracking/hybrid_region_tracker.cc index ea3b0f5bfc0..f0392643a6c 100644 --- a/intern/libmv/libmv/tracking/hybrid_region_tracker.cc +++ b/intern/libmv/libmv/tracking/hybrid_region_tracker.cc @@ -20,17 +20,19 @@ #include "libmv/tracking/hybrid_region_tracker.h" -#include "libmv/image/image.h" #include "libmv/image/convolve.h" +#include "libmv/image/image.h" #include "libmv/image/sample.h" #include "libmv/logging/logging.h" namespace libmv { -bool HybridRegionTracker::Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const { +bool HybridRegionTracker::Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const { double x2_coarse = *x2; double y2_coarse = *y2; if (!coarse_tracker_->Track(image1, image2, x1, y1, &x2_coarse, &y2_coarse)) { diff --git a/intern/libmv/libmv/tracking/hybrid_region_tracker.h b/intern/libmv/libmv/tracking/hybrid_region_tracker.h index 967d2afd1e5..2730d2dbbf2 100644 --- a/intern/libmv/libmv/tracking/hybrid_region_tracker.h +++ b/intern/libmv/libmv/tracking/hybrid_region_tracker.h @@ -21,8 +21,8 @@ #ifndef LIBMV_REGION_TRACKING_HYBRID_REGION_TRACKER_H_ #define LIBMV_REGION_TRACKING_HYBRID_REGION_TRACKER_H_ -#include "libmv/image/image.h" #include "libmv/base/scoped_ptr.h" +#include "libmv/image/image.h" #include "libmv/tracking/region_tracker.h" namespace libmv { @@ -30,18 +30,19 @@ namespace libmv { // TODO(keir): Documentation! class HybridRegionTracker : public RegionTracker { public: - HybridRegionTracker(RegionTracker *coarse_tracker, - RegionTracker *fine_tracker) - : coarse_tracker_(coarse_tracker), - fine_tracker_(fine_tracker) {} + HybridRegionTracker(RegionTracker* coarse_tracker, + RegionTracker* fine_tracker) + : coarse_tracker_(coarse_tracker), fine_tracker_(fine_tracker) {} virtual ~HybridRegionTracker() {} // Tracker interface. - virtual bool Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const; + virtual bool Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const; scoped_ptr<RegionTracker> coarse_tracker_; scoped_ptr<RegionTracker> fine_tracker_; diff --git a/intern/libmv/libmv/tracking/kalman_filter.h b/intern/libmv/libmv/tracking/kalman_filter.h index 9841f0e912c..b1312d0e027 100644 --- a/intern/libmv/libmv/tracking/kalman_filter.h +++ b/intern/libmv/libmv/tracking/kalman_filter.h @@ -19,13 +19,14 @@ // IN THE SOFTWARE. #ifndef LIBMV_TRACKING_KALMAN_FILTER_H_ +#define LIBMV_TRACKING_KALMAN_FILTER_H_ #include "libmv/numeric/numeric.h" namespace mv { // A Kalman filter with order N and observation size K. -template<typename T, int N, int K> +template <typename T, int N, int K> class KalmanFilter { public: struct State { @@ -38,54 +39,47 @@ class KalmanFilter { const T* observation_data, const T* process_covariance_data, const T* default_measurement_covariance_data) - : state_transition_matrix_( - Eigen::Matrix<T, N, N, Eigen::RowMajor>(state_transition_data)), - observation_matrix_( - Eigen::Matrix<T, K, N, Eigen::RowMajor>(observation_data)), - process_covariance_( - Eigen::Matrix<T, N, N, Eigen::RowMajor>(process_covariance_data)), - default_measurement_covariance_( - Eigen::Matrix<T, K, K, Eigen::RowMajor>( - default_measurement_covariance_data)) { - } + : state_transition_matrix_( + Eigen::Matrix<T, N, N, Eigen::RowMajor>(state_transition_data)), + observation_matrix_( + Eigen::Matrix<T, K, N, Eigen::RowMajor>(observation_data)), + process_covariance_( + Eigen::Matrix<T, N, N, Eigen::RowMajor>(process_covariance_data)), + default_measurement_covariance_(Eigen::Matrix<T, K, K, Eigen::RowMajor>( + default_measurement_covariance_data)) {} - KalmanFilter( - const Eigen::Matrix<T, N, N> &state_transition_matrix, - const Eigen::Matrix<T, K, N> &observation_matrix, - const Eigen::Matrix<T, N, N> &process_covariance, - const Eigen::Matrix<T, K, K> &default_measurement_covariance) - : state_transition_matrix_(state_transition_matrix), - observation_matrix_(observation_matrix), - process_covariance_(process_covariance), - default_measurement_covariance_(default_measurement_covariance) { - } + KalmanFilter(const Eigen::Matrix<T, N, N>& state_transition_matrix, + const Eigen::Matrix<T, K, N>& observation_matrix, + const Eigen::Matrix<T, N, N>& process_covariance, + const Eigen::Matrix<T, K, K>& default_measurement_covariance) + : state_transition_matrix_(state_transition_matrix), + observation_matrix_(observation_matrix), + process_covariance_(process_covariance), + default_measurement_covariance_(default_measurement_covariance) {} // Advances the system according to the current state estimate. - void Step(State *state) const { + void Step(State* state) const { state->mean = state_transition_matrix_ * state->mean; - state->covariance = state_transition_matrix_ * - state->covariance * - state_transition_matrix_.transpose() + + state->covariance = state_transition_matrix_ * state->covariance * + state_transition_matrix_.transpose() + process_covariance_; } // Updates a state with a new measurement. - void Update(const Eigen::Matrix<T, K, 1> &measurement_mean, - const Eigen::Matrix<T, K, K> &measurement_covariance, - State *state) const { + void Update(const Eigen::Matrix<T, K, 1>& measurement_mean, + const Eigen::Matrix<T, K, K>& measurement_covariance, + State* state) const { // Calculate the innovation, which is a distribution over prediction error. - Eigen::Matrix<T, K, 1> innovation_mean = measurement_mean - - observation_matrix_ * - state->mean; + Eigen::Matrix<T, K, 1> innovation_mean = + measurement_mean - observation_matrix_ * state->mean; Eigen::Matrix<T, K, K> innovation_covariance = - observation_matrix_ * - state->covariance * - observation_matrix_.transpose() + + observation_matrix_ * state->covariance * + observation_matrix_.transpose() + measurement_covariance; // Calculate the Kalman gain. Eigen::Matrix<T, 6, 2> kalman_gain = state->covariance * - observation_matrix_.transpose() * + observation_matrix_.transpose() * innovation_covariance.inverse(); // Update the state mean and covariance. @@ -95,8 +89,8 @@ class KalmanFilter { state->covariance; } - void Update(State *state, - const Eigen::Matrix<T, K, 1> &measurement_mean) const { + void Update(State* state, + const Eigen::Matrix<T, K, 1>& measurement_mean) const { Update(state, measurement_mean, default_measurement_covariance_); } diff --git a/intern/libmv/libmv/tracking/klt_region_tracker.cc b/intern/libmv/libmv/tracking/klt_region_tracker.cc index dbbf9f0b996..df1ded65489 100644 --- a/intern/libmv/libmv/tracking/klt_region_tracker.cc +++ b/intern/libmv/libmv/tracking/klt_region_tracker.cc @@ -20,10 +20,10 @@ #include "libmv/tracking/klt_region_tracker.h" -#include "libmv/logging/logging.h" -#include "libmv/image/image.h" #include "libmv/image/convolve.h" +#include "libmv/image/image.h" #include "libmv/image/sample.h" +#include "libmv/logging/logging.h" namespace libmv { @@ -33,16 +33,18 @@ namespace libmv { // TODO(keir): The calls to SampleLinear() do boundary checking that should // instead happen outside the loop. Since this is the innermost loop, the extra // bounds checking hurts performance. -static void ComputeTrackingEquation(const Array3Df &image_and_gradient1, - const Array3Df &image_and_gradient2, - double x1, double y1, - double x2, double y2, +static void ComputeTrackingEquation(const Array3Df& image_and_gradient1, + const Array3Df& image_and_gradient2, + double x1, + double y1, + double x2, + double y2, int half_width, - float *gxx, - float *gxy, - float *gyy, - float *ex, - float *ey) { + float* gxx, + float* gxy, + float* gyy, + float* ex, + float* ey) { *gxx = *gxy = *gyy = 0; *ex = *ey = 0; for (int r = -half_width; r <= half_width; ++r) { @@ -51,8 +53,8 @@ static void ComputeTrackingEquation(const Array3Df &image_and_gradient1, float yy1 = y1 + r; float xx2 = x2 + c; float yy2 = y2 + r; - float I = SampleLinear(image_and_gradient1, yy1, xx1, 0); - float J = SampleLinear(image_and_gradient2, yy2, xx2, 0); + float I = SampleLinear(image_and_gradient1, yy1, xx1, 0); + float J = SampleLinear(image_and_gradient2, yy2, xx2, 0); float gx = SampleLinear(image_and_gradient2, yy2, xx2, 1); float gy = SampleLinear(image_and_gradient2, yy2, xx2, 2); *gxx += gx * gx; @@ -64,22 +66,21 @@ static void ComputeTrackingEquation(const Array3Df &image_and_gradient1, } } -static bool RegionIsInBounds(const FloatImage &image1, - double x, double y, - int half_window_size) { +static bool RegionIsInBounds(const FloatImage& image1, + double x, + double y, + int half_window_size) { // Check the minimum coordinates. int min_x = floor(x) - half_window_size - 1; int min_y = floor(y) - half_window_size - 1; - if (min_x < 0.0 || - min_y < 0.0) { + if (min_x < 0.0 || min_y < 0.0) { return false; } // Check the maximum coordinates. int max_x = ceil(x) + half_window_size + 1; int max_y = ceil(y) + half_window_size + 1; - if (max_x > image1.cols() || - max_y > image1.rows()) { + if (max_x > image1.cols() || max_y > image1.rows()) { return false; } @@ -87,10 +88,12 @@ static bool RegionIsInBounds(const FloatImage &image1, return true; } -bool KltRegionTracker::Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const { +bool KltRegionTracker::Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const { if (!RegionIsInBounds(image1, x1, y1, half_window_size)) { LG << "Fell out of image1's window with x1=" << x1 << ", y1=" << y1 << ", hw=" << half_window_size << "."; @@ -116,10 +119,16 @@ bool KltRegionTracker::Track(const FloatImage &image1, float gxx, gxy, gyy, ex, ey; ComputeTrackingEquation(image_and_gradient1, image_and_gradient2, - x1, y1, - *x2, *y2, + x1, + y1, + *x2, + *y2, half_window_size, - &gxx, &gxy, &gyy, &ex, &ey); + &gxx, + &gxy, + &gyy, + &ex, + &ey); // Solve the tracking equation // diff --git a/intern/libmv/libmv/tracking/klt_region_tracker.h b/intern/libmv/libmv/tracking/klt_region_tracker.h index 43977757084..07ed1b7155c 100644 --- a/intern/libmv/libmv/tracking/klt_region_tracker.h +++ b/intern/libmv/libmv/tracking/klt_region_tracker.h @@ -37,10 +37,12 @@ struct KltRegionTracker : public RegionTracker { virtual ~KltRegionTracker() {} // Tracker interface. - virtual bool Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const; + virtual bool Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const; // No point in creating getters or setters. int half_window_size; diff --git a/intern/libmv/libmv/tracking/pyramid_region_tracker.cc b/intern/libmv/libmv/tracking/pyramid_region_tracker.cc index 4db501050f3..52764a535e0 100644 --- a/intern/libmv/libmv/tracking/pyramid_region_tracker.cc +++ b/intern/libmv/libmv/tracking/pyramid_region_tracker.cc @@ -29,8 +29,9 @@ namespace libmv { -static void MakePyramid(const FloatImage &image, int num_levels, - std::vector<FloatImage> *pyramid) { +static void MakePyramid(const FloatImage& image, + int num_levels, + std::vector<FloatImage>* pyramid) { pyramid->resize(num_levels); (*pyramid)[0] = image; for (int i = 1; i < num_levels; ++i) { @@ -38,10 +39,12 @@ static void MakePyramid(const FloatImage &image, int num_levels, } } -bool PyramidRegionTracker::Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const { +bool PyramidRegionTracker::Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const { // Shrink the guessed x and y location to match the coarsest level + 1 (which // when gets corrected in the loop). *x2 /= pow(2., num_levels_); @@ -71,8 +74,8 @@ bool PyramidRegionTracker::Track(const FloatImage &image1, // Track the point on this level with the base tracker. LG << "Tracking on level " << i; - bool succeeded = tracker_->Track(pyramid1[i], pyramid2[i], xx, yy, - &x2_new, &y2_new); + bool succeeded = + tracker_->Track(pyramid1[i], pyramid2[i], xx, yy, &x2_new, &y2_new); if (!succeeded) { if (i == 0) { diff --git a/intern/libmv/libmv/tracking/pyramid_region_tracker.h b/intern/libmv/libmv/tracking/pyramid_region_tracker.h index 1f9675469f4..5fe21c95904 100644 --- a/intern/libmv/libmv/tracking/pyramid_region_tracker.h +++ b/intern/libmv/libmv/tracking/pyramid_region_tracker.h @@ -21,21 +21,24 @@ #ifndef LIBMV_CORRESPONDENCE_PYRAMID_TRACKER_H_ #define LIBMV_CORRESPONDENCE_PYRAMID_TRACKER_H_ -#include "libmv/image/image.h" #include "libmv/base/scoped_ptr.h" +#include "libmv/image/image.h" #include "libmv/tracking/region_tracker.h" namespace libmv { class PyramidRegionTracker : public RegionTracker { public: - PyramidRegionTracker(RegionTracker *tracker, int num_levels) + PyramidRegionTracker(RegionTracker* tracker, int num_levels) : tracker_(tracker), num_levels_(num_levels) {} - virtual bool Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const; + virtual bool Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const; + private: scoped_ptr<RegionTracker> tracker_; int num_levels_; diff --git a/intern/libmv/libmv/tracking/pyramid_region_tracker_test.cc b/intern/libmv/libmv/tracking/pyramid_region_tracker_test.cc index d90a1012237..2fcf292e404 100644 --- a/intern/libmv/libmv/tracking/pyramid_region_tracker_test.cc +++ b/intern/libmv/libmv/tracking/pyramid_region_tracker_test.cc @@ -19,8 +19,8 @@ // IN THE SOFTWARE. #include "libmv/tracking/pyramid_region_tracker.h" -#include "libmv/tracking/klt_region_tracker.h" #include "libmv/image/image.h" +#include "libmv/tracking/klt_region_tracker.h" #include "testing/testing.h" namespace libmv { @@ -55,8 +55,7 @@ TEST(PyramidKltRegionTracker, Track) { KltRegionTracker tracker; tracker.half_window_size = half_window_size; - EXPECT_FALSE(tracker.Track(image1, image2, x1, y1, - &x2_actual, &y2_actual)); + EXPECT_FALSE(tracker.Track(image1, image2, x1, y1, &x2_actual, &y2_actual)); } // Verify that it works with the pyramid tracker. @@ -64,12 +63,11 @@ TEST(PyramidKltRegionTracker, Track) { double x2_actual = x1; double y2_actual = y1; - KltRegionTracker *klt_tracker = new KltRegionTracker; + KltRegionTracker* klt_tracker = new KltRegionTracker; klt_tracker->half_window_size = half_window_size; PyramidRegionTracker tracker(klt_tracker, 3); - EXPECT_TRUE(tracker.Track(image1, image2, x1, y1, - &x2_actual, &y2_actual)); + EXPECT_TRUE(tracker.Track(image1, image2, x1, y1, &x2_actual, &y2_actual)); EXPECT_NEAR(x2_actual, x2, 0.001); EXPECT_NEAR(y2_actual, y2, 0.001); diff --git a/intern/libmv/libmv/tracking/region_tracker.h b/intern/libmv/libmv/tracking/region_tracker.h index 4f7574df1a3..e753ac8be6c 100644 --- a/intern/libmv/libmv/tracking/region_tracker.h +++ b/intern/libmv/libmv/tracking/region_tracker.h @@ -37,10 +37,12 @@ class RegionTracker { image2. If no guess is available, (\a x1, \a y1) is a good start. Returns true on success, false otherwise */ - virtual bool Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const = 0; + virtual bool Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const = 0; }; } // namespace libmv diff --git a/intern/libmv/libmv/tracking/retrack_region_tracker.cc b/intern/libmv/libmv/tracking/retrack_region_tracker.cc index 4d230086d28..9152078053c 100644 --- a/intern/libmv/libmv/tracking/retrack_region_tracker.cc +++ b/intern/libmv/libmv/tracking/retrack_region_tracker.cc @@ -25,10 +25,12 @@ namespace libmv { -bool RetrackRegionTracker::Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const { +bool RetrackRegionTracker::Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const { // Track forward, getting x2 and y2. if (!tracker_->Track(image1, image2, x1, y1, x2, y2)) { return false; diff --git a/intern/libmv/libmv/tracking/retrack_region_tracker.h b/intern/libmv/libmv/tracking/retrack_region_tracker.h index ab05f320834..504cf697349 100644 --- a/intern/libmv/libmv/tracking/retrack_region_tracker.h +++ b/intern/libmv/libmv/tracking/retrack_region_tracker.h @@ -21,8 +21,8 @@ #ifndef LIBMV_TRACKING_RETRACK_REGION_TRACKER_H_ #define LIBMV_TRACKING_RETRACK_REGION_TRACKER_H_ -#include "libmv/image/image.h" #include "libmv/base/scoped_ptr.h" +#include "libmv/image/image.h" #include "libmv/tracking/region_tracker.h" namespace libmv { @@ -31,13 +31,16 @@ namespace libmv { // track that doesn't track backwards to the starting point. class RetrackRegionTracker : public RegionTracker { public: - RetrackRegionTracker(RegionTracker *tracker, double tolerance) + RetrackRegionTracker(RegionTracker* tracker, double tolerance) : tracker_(tracker), tolerance_(tolerance) {} - virtual bool Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const; + virtual bool Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const; + private: scoped_ptr<RegionTracker> tracker_; double tolerance_; diff --git a/intern/libmv/libmv/tracking/track_region.cc b/intern/libmv/libmv/tracking/track_region.cc index 895c9a1e23d..403b4088174 100644 --- a/intern/libmv/libmv/tracking/track_region.cc +++ b/intern/libmv/libmv/tracking/track_region.cc @@ -27,14 +27,14 @@ #include "libmv/tracking/track_region.h" -#include <Eigen/SVD> #include <Eigen/QR> +#include <Eigen/SVD> #include <iostream> #include "ceres/ceres.h" -#include "libmv/logging/logging.h" +#include "libmv/image/convolve.h" #include "libmv/image/image.h" #include "libmv/image/sample.h" -#include "libmv/image/convolve.h" +#include "libmv/logging/logging.h" #include "libmv/multiview/homography.h" #include "libmv/numeric/numeric.h" @@ -44,57 +44,45 @@ namespace ceres { // A jet traits class to make it easier to work with mixed auto / numeric diff. -template<typename T> +template <typename T> struct JetOps { - static bool IsScalar() { - return true; - } - static T GetScalar(const T& t) { - return t; - } - static void SetScalar(const T& scalar, T* t) { - *t = scalar; - } - static void ScaleDerivative(double scale_by, T *value) { + static bool IsScalar() { return true; } + static T GetScalar(const T& t) { return t; } + static void SetScalar(const T& scalar, T* t) { *t = scalar; } + static void ScaleDerivative(double scale_by, T* value) { // For double, there is no derivative to scale. - (void) scale_by; // Ignored. - (void) value; // Ignored. + (void)scale_by; // Ignored. + (void)value; // Ignored. } }; -template<typename T, int N> -struct JetOps<Jet<T, N> > { - static bool IsScalar() { - return false; - } - static T GetScalar(const Jet<T, N>& t) { - return t.a; - } - static void SetScalar(const T& scalar, Jet<T, N>* t) { - t->a = scalar; - } - static void ScaleDerivative(double scale_by, Jet<T, N> *value) { +template <typename T, int N> +struct JetOps<Jet<T, N>> { + static bool IsScalar() { return false; } + static T GetScalar(const Jet<T, N>& t) { return t.a; } + static void SetScalar(const T& scalar, Jet<T, N>* t) { t->a = scalar; } + static void ScaleDerivative(double scale_by, Jet<T, N>* value) { value->v *= scale_by; } }; -template<typename FunctionType, int kNumArgs, typename ArgumentType> +template <typename FunctionType, int kNumArgs, typename ArgumentType> struct Chain { - static ArgumentType Rule(const FunctionType &f, + static ArgumentType Rule(const FunctionType& f, const FunctionType dfdx[kNumArgs], const ArgumentType x[kNumArgs]) { // In the default case of scalars, there's nothing to do since there are no // derivatives to propagate. - (void) dfdx; // Ignored. - (void) x; // Ignored. + (void)dfdx; // Ignored. + (void)x; // Ignored. return f; } }; // XXX Add documentation here! -template<typename FunctionType, int kNumArgs, typename T, int N> -struct Chain<FunctionType, kNumArgs, Jet<T, N> > { - static Jet<T, N> Rule(const FunctionType &f, +template <typename FunctionType, int kNumArgs, typename T, int N> +struct Chain<FunctionType, kNumArgs, Jet<T, N>> { + static Jet<T, N> Rule(const FunctionType& f, const FunctionType dfdx[kNumArgs], const Jet<T, N> x[kNumArgs]) { // x is itself a function of another variable ("z"); what this function @@ -107,8 +95,8 @@ struct Chain<FunctionType, kNumArgs, Jet<T, N> > { } // Map the input gradient dfdx into an Eigen row vector. - Eigen::Map<const Eigen::Matrix<FunctionType, 1, kNumArgs> > - vector_dfdx(dfdx, 1, kNumArgs); + Eigen::Map<const Eigen::Matrix<FunctionType, 1, kNumArgs>> vector_dfdx( + dfdx, 1, kNumArgs); // Now apply the chain rule to obtain df/dz. Combine the derivative with // the scalar part to obtain f with full derivative information. @@ -123,9 +111,9 @@ struct Chain<FunctionType, kNumArgs, Jet<T, N> > { namespace libmv { +using ceres::Chain; using ceres::Jet; using ceres::JetOps; -using ceres::Chain; TrackRegionOptions::TrackRegionOptions() : mode(TRANSLATION), @@ -144,17 +132,12 @@ TrackRegionOptions::TrackRegionOptions() namespace { // TODO(keir): Consider adding padding. -template<typename T> -bool InBounds(const FloatImage &image, - const T &x, - const T &y) { - return 0.0 <= x && x < image.Width() && - 0.0 <= y && y < image.Height(); +template <typename T> +bool InBounds(const FloatImage& image, const T& x, const T& y) { + return 0.0 <= x && x < image.Width() && 0.0 <= y && y < image.Height(); } -bool AllInBounds(const FloatImage &image, - const double *x, - const double *y) { +bool AllInBounds(const FloatImage& image, const double* x, const double* y) { for (int i = 0; i < 4; ++i) { if (!InBounds(image, x[i], y[i])) { return false; @@ -166,10 +149,10 @@ bool AllInBounds(const FloatImage &image, // Sample the image at position (x, y) but use the gradient, if present, to // propagate derivatives from x and y. This is needed to integrate the numeric // image gradients with Ceres's autodiff framework. -template<typename T> -static T SampleWithDerivative(const FloatImage &image_and_gradient, - const T &x, - const T &y) { +template <typename T> +static T SampleWithDerivative(const FloatImage& image_and_gradient, + const T& x, + const T& y) { float scalar_x = JetOps<T>::GetScalar(x); float scalar_y = JetOps<T>::GetScalar(y); @@ -184,18 +167,23 @@ static T SampleWithDerivative(const FloatImage &image_and_gradient, // For the derivative case, sample the gradient as well. SampleLinear(image_and_gradient, scalar_y, scalar_x, sample); } - T xy[2] = { x, y }; + T xy[2] = {x, y}; return Chain<float, 2, T>::Rule(sample[0], sample + 1, xy); } -template<typename Warp> +template <typename Warp> class TerminationCheckingCallback : public ceres::IterationCallback { public: - TerminationCheckingCallback(const TrackRegionOptions &options, + TerminationCheckingCallback(const TrackRegionOptions& options, const FloatImage& image2, - const Warp &warp, - const double *x1, const double *y1) - : options_(options), image2_(image2), warp_(warp), x1_(x1), y1_(y1), + const Warp& warp, + const double* x1, + const double* y1) + : options_(options), + image2_(image2), + warp_(warp), + x1_(x1), + y1_(y1), have_last_successful_step_(false) {} virtual ceres::CallbackReturnType operator()( @@ -229,7 +217,7 @@ class TerminationCheckingCallback : public ceres::IterationCallback { for (int i = 0; i < 4; ++i) { double dx = x2[i] - x2_last_successful_[i]; double dy = y2[i] - y2_last_successful_[i]; - double change_pixels = dx*dx + dy*dy; + double change_pixels = dx * dx + dy * dy; if (change_pixels > max_change_pixels) { max_change_pixels = change_pixels; } @@ -255,27 +243,27 @@ class TerminationCheckingCallback : public ceres::IterationCallback { } private: - const TrackRegionOptions &options_; - const FloatImage &image2_; - const Warp &warp_; - const double *x1_; - const double *y1_; + const TrackRegionOptions& options_; + const FloatImage& image2_; + const Warp& warp_; + const double* x1_; + const double* y1_; bool have_last_successful_step_; double x2_last_successful_[4]; double y2_last_successful_[4]; }; -template<typename Warp> +template <typename Warp> class PixelDifferenceCostFunctor { public: - PixelDifferenceCostFunctor(const TrackRegionOptions &options, - const FloatImage &image_and_gradient1, - const FloatImage &image_and_gradient2, - const Mat3 &canonical_to_image1, + PixelDifferenceCostFunctor(const TrackRegionOptions& options, + const FloatImage& image_and_gradient1, + const FloatImage& image_and_gradient2, + const Mat3& canonical_to_image1, int num_samples_x, int num_samples_y, - const Warp &warp) + const Warp& warp) : options_(options), image_and_gradient1_(image_and_gradient1), image_and_gradient2_(image_and_gradient2), @@ -322,8 +310,8 @@ class PixelDifferenceCostFunctor { src_mean_ /= num_samples; } - template<typename T> - bool operator()(const T *warp_parameters, T *residuals) const { + template <typename T> + bool operator()(const T* warp_parameters, T* residuals) const { if (options_.image1_mask != NULL) { VLOG(2) << "Using a mask."; } @@ -333,8 +321,7 @@ class PixelDifferenceCostFunctor { T dst_mean = T(1.0); if (options_.use_normalized_intensities) { - ComputeNormalizingCoefficient(warp_parameters, - &dst_mean); + ComputeNormalizingCoefficient(warp_parameters, &dst_mean); } int cursor = 0; @@ -374,9 +361,8 @@ class PixelDifferenceCostFunctor { &image2_position[1]); // Sample the destination, propagating derivatives. - T dst_sample = SampleWithDerivative(image_and_gradient2_, - image2_position[0], - image2_position[1]); + T dst_sample = SampleWithDerivative( + image_and_gradient2_, image2_position[0], image2_position[1]); // Sample the source. This is made complicated by ESM mode. T src_sample; @@ -386,8 +372,8 @@ class PixelDifferenceCostFunctor { // better convergence. Copy the derivative of the warp parameters // onto the jets for the image1 position. This is the ESM hack. T image1_position_jet[2] = { - image2_position[0], // Order is x, y. This matches the - image2_position[1] // derivative order in the patch. + image2_position[0], // Order is x, y. This matches the + image2_position[1] // derivative order in the patch. }; JetOps<T>::SetScalar(image1_position[0], image1_position_jet + 0); JetOps<T>::SetScalar(image1_position[1], image1_position_jet + 1); @@ -433,9 +419,9 @@ class PixelDifferenceCostFunctor { } // For normalized matching, the average and - template<typename T> - void ComputeNormalizingCoefficient(const T *warp_parameters, - T *dst_mean) const { + template <typename T> + void ComputeNormalizingCoefficient(const T* warp_parameters, + T* dst_mean) const { *dst_mean = T(0.0); double num_samples = 0.0; for (int r = 0; r < num_samples_y_; ++r) { @@ -462,14 +448,12 @@ class PixelDifferenceCostFunctor { &image2_position[0], &image2_position[1]); - // Sample the destination, propagating derivatives. // TODO(keir): This accumulation can, surprisingly, be done as a // pre-pass by using integral images. This is complicated by the need // to store the jets in the integral image, but it is possible. - T dst_sample = SampleWithDerivative(image_and_gradient2_, - image2_position[0], - image2_position[1]); + T dst_sample = SampleWithDerivative( + image_and_gradient2_, image2_position[0], image2_position[1]); // Weight the sample by the mask, if one is present. if (options_.image1_mask != NULL) { @@ -486,10 +470,10 @@ class PixelDifferenceCostFunctor { // TODO(keir): Consider also computing the cost here. double PearsonProductMomentCorrelationCoefficient( - const double *warp_parameters) const { + const double* warp_parameters) const { for (int i = 0; i < Warp::NUM_PARAMETERS; ++i) { - VLOG(2) << "Correlation warp_parameters[" << i << "]: " - << warp_parameters[i]; + VLOG(2) << "Correlation warp_parameters[" << i + << "]: " << warp_parameters[i]; } // The single-pass PMCC computation is somewhat numerically unstable, but @@ -537,9 +521,9 @@ class PixelDifferenceCostFunctor { } sX += x; sY += y; - sXX += x*x; - sYY += y*y; - sXY += x*y; + sXX += x * x; + sYY += y * y; + sXY += x * y; } } // Normalize. @@ -549,25 +533,24 @@ class PixelDifferenceCostFunctor { sYY /= num_samples; sXY /= num_samples; - double var_x = sXX - sX*sX; - double var_y = sYY - sY*sY; - double covariance_xy = sXY - sX*sY; + double var_x = sXX - sX * sX; + double var_y = sYY - sY * sY; + double covariance_xy = sXY - sX * sY; double correlation = covariance_xy / sqrt(var_x * var_y); - LG << "Covariance xy: " << covariance_xy - << ", var 1: " << var_x << ", var 2: " << var_y - << ", correlation: " << correlation; + LG << "Covariance xy: " << covariance_xy << ", var 1: " << var_x + << ", var 2: " << var_y << ", correlation: " << correlation; return correlation; } private: - const TrackRegionOptions &options_; - const FloatImage &image_and_gradient1_; - const FloatImage &image_and_gradient2_; - const Mat3 &canonical_to_image1_; + const TrackRegionOptions& options_; + const FloatImage& image_and_gradient1_; + const FloatImage& image_and_gradient2_; + const Mat3& canonical_to_image1_; int num_samples_x_; int num_samples_y_; - const Warp &warp_; + const Warp& warp_; double src_mean_; FloatImage pattern_and_gradient_; @@ -579,15 +562,15 @@ class PixelDifferenceCostFunctor { FloatImage pattern_mask_; }; -template<typename Warp> +template <typename Warp> class WarpRegularizingCostFunctor { public: - WarpRegularizingCostFunctor(const TrackRegionOptions &options, - const double *x1, - const double *y1, - const double *x2_original, - const double *y2_original, - const Warp &warp) + WarpRegularizingCostFunctor(const TrackRegionOptions& options, + const double* x1, + const double* y1, + const double* x2_original, + const double* y2_original, + const Warp& warp) : options_(options), x1_(x1), y1_(y1), @@ -606,11 +589,11 @@ class WarpRegularizingCostFunctor { original_centroid_[1] /= 4; } - template<typename T> - bool operator()(const T *warp_parameters, T *residuals) const { - T dst_centroid[2] = { T(0.0), T(0.0) }; + template <typename T> + bool operator()(const T* warp_parameters, T* residuals) const { + T dst_centroid[2] = {T(0.0), T(0.0)}; for (int i = 0; i < 4; ++i) { - T image1_position[2] = { T(x1_[i]), T(y1_[i]) }; + T image1_position[2] = {T(x1_[i]), T(y1_[i])}; T image2_position[2]; warp_.Forward(warp_parameters, T(x1_[i]), @@ -643,28 +626,30 @@ class WarpRegularizingCostFunctor { return true; } - const TrackRegionOptions &options_; - const double *x1_; - const double *y1_; - const double *x2_original_; - const double *y2_original_; + const TrackRegionOptions& options_; + const double* x1_; + const double* y1_; + const double* x2_original_; + const double* y2_original_; double original_centroid_[2]; - const Warp &warp_; + const Warp& warp_; }; // Compute the warp from rectangular coordinates, where one corner is the // origin, and the opposite corner is at (num_samples_x, num_samples_y). -Mat3 ComputeCanonicalHomography(const double *x1, - const double *y1, +Mat3 ComputeCanonicalHomography(const double* x1, + const double* y1, int num_samples_x, int num_samples_y) { Mat canonical(2, 4); - canonical << 0, num_samples_x, num_samples_x, 0, - 0, 0, num_samples_y, num_samples_y; + canonical << 0, num_samples_x, num_samples_x, 0, 0, 0, num_samples_y, + num_samples_y; Mat xy1(2, 4); + // clang-format off xy1 << x1[0], x1[1], x1[2], x1[3], y1[0], y1[1], y1[2], y1[3]; + // clang-format om Mat3 H; if (!Homography2DFromCorrespondencesLinear(canonical, xy1, &H, 1e-12)) { @@ -675,7 +660,7 @@ Mat3 ComputeCanonicalHomography(const double *x1, class Quad { public: - Quad(const double *x, const double *y) : x_(x), y_(y) { + Quad(const double* x, const double* y) : x_(x), y_(y) { // Compute the centroid and store it. centroid_ = Vec2(0.0, 0.0); for (int i = 0; i < 4; ++i) { @@ -685,9 +670,7 @@ class Quad { } // The centroid of the four points representing the quad. - const Vec2& Centroid() const { - return centroid_; - } + const Vec2& Centroid() const { return centroid_; } // The average magnitude of the four points relative to the centroid. double Scale() const { @@ -703,22 +686,24 @@ class Quad { } private: - const double *x_; - const double *y_; + const double* x_; + const double* y_; Vec2 centroid_; }; struct TranslationWarp { - TranslationWarp(const double *x1, const double *y1, - const double *x2, const double *y2) { + TranslationWarp(const double* x1, + const double* y1, + const double* x2, + const double* y2) { Vec2 t = Quad(x2, y2).Centroid() - Quad(x1, y1).Centroid(); parameters[0] = t[0]; parameters[1] = t[1]; } - template<typename T> - void Forward(const T *warp_parameters, - const T &x1, const T& y1, T *x2, T* y2) const { + template <typename T> + void Forward( + const T* warp_parameters, const T& x1, const T& y1, T* x2, T* y2) const { *x2 = x1 + warp_parameters[0]; *y2 = y1 + warp_parameters[1]; } @@ -729,8 +714,10 @@ struct TranslationWarp { }; struct TranslationScaleWarp { - TranslationScaleWarp(const double *x1, const double *y1, - const double *x2, const double *y2) + TranslationScaleWarp(const double* x1, + const double* y1, + const double* x2, + const double* y2) : q1(x1, y1) { Quad q2(x2, y2); @@ -746,9 +733,9 @@ struct TranslationScaleWarp { // The strange way of parameterizing the translation and scaling is to make // the knobs that the optimizer sees easy to adjust. This is less important // for the scaling case than the rotation case. - template<typename T> - void Forward(const T *warp_parameters, - const T &x1, const T& y1, T *x2, T* y2) const { + template <typename T> + void Forward( + const T* warp_parameters, const T& x1, const T& y1, T* x2, T* y2) const { // Make the centroid of Q1 the origin. const T x1_origin = x1 - q1.Centroid()(0); const T y1_origin = y1 - q1.Centroid()(1); @@ -775,15 +762,17 @@ struct TranslationScaleWarp { }; // Assumes the given points are already zero-centroid and the same size. -Mat2 OrthogonalProcrustes(const Mat2 &correlation_matrix) { +Mat2 OrthogonalProcrustes(const Mat2& correlation_matrix) { Eigen::JacobiSVD<Mat2> svd(correlation_matrix, Eigen::ComputeFullU | Eigen::ComputeFullV); return svd.matrixV() * svd.matrixU().transpose(); } struct TranslationRotationWarp { - TranslationRotationWarp(const double *x1, const double *y1, - const double *x2, const double *y2) + TranslationRotationWarp(const double* x1, + const double* y1, + const double* x2, + const double* y2) : q1(x1, y1) { Quad q2(x2, y2); @@ -816,9 +805,9 @@ struct TranslationRotationWarp { // // Instead, use the parameterization below that offers a parameterization // that exposes the degrees of freedom in a way amenable to optimization. - template<typename T> - void Forward(const T *warp_parameters, - const T &x1, const T& y1, T *x2, T* y2) const { + template <typename T> + void Forward( + const T* warp_parameters, const T& x1, const T& y1, T* x2, T* y2) const { // Make the centroid of Q1 the origin. const T x1_origin = x1 - q1.Centroid()(0); const T y1_origin = y1 - q1.Centroid()(1); @@ -847,8 +836,10 @@ struct TranslationRotationWarp { }; struct TranslationRotationScaleWarp { - TranslationRotationScaleWarp(const double *x1, const double *y1, - const double *x2, const double *y2) + TranslationRotationScaleWarp(const double* x1, + const double* y1, + const double* x2, + const double* y2) : q1(x1, y1) { Quad q2(x2, y2); @@ -884,9 +875,9 @@ struct TranslationRotationScaleWarp { // // Instead, use the parameterization below that offers a parameterization // that exposes the degrees of freedom in a way amenable to optimization. - template<typename T> - void Forward(const T *warp_parameters, - const T &x1, const T& y1, T *x2, T* y2) const { + template <typename T> + void Forward( + const T* warp_parameters, const T& x1, const T& y1, T* x2, T* y2) const { // Make the centroid of Q1 the origin. const T x1_origin = x1 - q1.Centroid()(0); const T y1_origin = y1 - q1.Centroid()(1); @@ -921,8 +912,10 @@ struct TranslationRotationScaleWarp { }; struct AffineWarp { - AffineWarp(const double *x1, const double *y1, - const double *x2, const double *y2) + AffineWarp(const double* x1, + const double* y1, + const double* x2, + const double* y2) : q1(x1, y1) { Quad q2(x2, y2); @@ -938,8 +931,8 @@ struct AffineWarp { Vec2 v1 = q1.CornerRelativeToCentroid(i); Vec2 v2 = q2.CornerRelativeToCentroid(i); - Q1.row(2 * i + 0) << v1[0], v1[1], 0, 0; - Q1.row(2 * i + 1) << 0, 0, v1[0], v1[1]; + Q1.row(2 * i + 0) << v1[0], v1[1], 0, 0; + Q1.row(2 * i + 1) << 0, 0, v1[0], v1[1]; Q2(2 * i + 0) = v2[0]; Q2(2 * i + 1) = v2[1]; @@ -957,8 +950,8 @@ struct AffineWarp { } // See comments in other parameterizations about why the centroid is used. - template<typename T> - void Forward(const T *p, const T &x1, const T& y1, T *x2, T* y2) const { + template <typename T> + void Forward(const T* p, const T& x1, const T& y1, T* x2, T* y2) const { // Make the centroid of Q1 the origin. const T x1_origin = x1 - q1.Centroid()(0); const T y1_origin = y1 - q1.Centroid()(1); @@ -985,15 +978,21 @@ struct AffineWarp { }; struct HomographyWarp { - HomographyWarp(const double *x1, const double *y1, - const double *x2, const double *y2) { + HomographyWarp(const double* x1, + const double* y1, + const double* x2, + const double* y2) { Mat quad1(2, 4); + // clang-format off quad1 << x1[0], x1[1], x1[2], x1[3], y1[0], y1[1], y1[2], y1[3]; + // clang-format on Mat quad2(2, 4); + // clang-format off quad2 << x2[0], x2[1], x2[2], x2[3], y2[0], y2[1], y2[2], y2[3]; + // clang-format on Mat3 H; if (!Homography2DFromCorrespondencesLinear(quad1, quad2, &H, 1e-12)) { @@ -1014,13 +1013,12 @@ struct HomographyWarp { } } - template<typename T> - static void Forward(const T *p, - const T &x1, const T& y1, T *x2, T* y2) { + template <typename T> + static void Forward(const T* p, const T& x1, const T& y1, T* x2, T* y2) { // Homography warp with manual 3x3 matrix multiply. - const T xx2 = (1.0 + p[0]) * x1 + p[1] * y1 + p[2]; - const T yy2 = p[3] * x1 + (1.0 + p[4]) * y1 + p[5]; - const T zz2 = p[6] * x1 + p[7] * y1 + 1.0; + const T xx2 = (1.0 + p[0]) * x1 + p[1] * y1 + p[2]; + const T yy2 = p[3] * x1 + (1.0 + p[4]) * y1 + p[5]; + const T zz2 = p[6] * x1 + p[7] * y1 + 1.0; *x2 = xx2 / zz2; *y2 = yy2 / zz2; } @@ -1036,11 +1034,14 @@ struct HomographyWarp { // // The idea is to take the maximum x or y distance. This may be oversampling. // TODO(keir): Investigate the various choices; perhaps average is better? -void PickSampling(const double *x1, const double *y1, - const double *x2, const double *y2, - int *num_samples_x, int *num_samples_y) { - (void) x2; // Ignored. - (void) y2; // Ignored. +void PickSampling(const double* x1, + const double* y1, + const double* x2, + const double* y2, + int* num_samples_x, + int* num_samples_y) { + (void)x2; // Ignored. + (void)y2; // Ignored. Vec2 a0(x1[0], y1[0]); Vec2 a1(x1[1], y1[1]); @@ -1053,18 +1054,10 @@ void PickSampling(const double *x1, const double *y1, Vec2 b3(x1[3], y1[3]); double x_dimensions[4] = { - (a1 - a0).norm(), - (a3 - a2).norm(), - (b1 - b0).norm(), - (b3 - b2).norm() - }; + (a1 - a0).norm(), (a3 - a2).norm(), (b1 - b0).norm(), (b3 - b2).norm()}; double y_dimensions[4] = { - (a3 - a0).norm(), - (a1 - a2).norm(), - (b3 - b0).norm(), - (b1 - b2).norm() - }; + (a3 - a0).norm(), (a1 - a2).norm(), (b3 - b0).norm(), (b1 - b2).norm()}; const double kScaleFactor = 1.0; *num_samples_x = static_cast<int>( kScaleFactor * *std::max_element(x_dimensions, x_dimensions + 4)); @@ -1074,17 +1067,18 @@ void PickSampling(const double *x1, const double *y1, << ", num_samples_y: " << *num_samples_y; } -bool SearchAreaTooBigForDescent(const FloatImage &image2, - const double *x2, const double *y2) { +bool SearchAreaTooBigForDescent(const FloatImage& image2, + const double* x2, + const double* y2) { // TODO(keir): Check the bounds and enable only when it makes sense. - (void) image2; // Ignored. - (void) x2; // Ignored. - (void) y2; // Ignored. + (void)image2; // Ignored. + (void)x2; // Ignored. + (void)y2; // Ignored. return true; } -bool PointOnRightHalfPlane(const Vec2 &a, const Vec2 &b, double x, double y) { +bool PointOnRightHalfPlane(const Vec2& a, const Vec2& b, double x, double y) { Vec2 ba = b - a; return ((Vec2(x, y) - b).transpose() * Vec2(-ba.y(), ba.x())) > 0; } @@ -1102,7 +1096,7 @@ bool PointOnRightHalfPlane(const Vec2 &a, const Vec2 &b, double x, double y) { // y // // The implementation does up to four half-plane comparisons. -bool PointInQuad(const double *xs, const double *ys, double x, double y) { +bool PointInQuad(const double* xs, const double* ys, double x, double y) { Vec2 a0(xs[0], ys[0]); Vec2 a1(xs[1], ys[1]); Vec2 a2(xs[2], ys[2]); @@ -1116,24 +1110,27 @@ bool PointInQuad(const double *xs, const double *ys, double x, double y) { // This makes it possible to map between Eigen float arrays and FloatImage // without using comparisons. -typedef Eigen::Array<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> FloatArray; +typedef Eigen::Array<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> + FloatArray; // This creates a pattern in the frame of image2, from the pixel is image1, // based on the initial guess represented by the two quads x1, y1, and x2, y2. -template<typename Warp> -void CreateBrutePattern(const double *x1, const double *y1, - const double *x2, const double *y2, - const FloatImage &image1, - const FloatImage *image1_mask, - FloatArray *pattern, - FloatArray *mask, - int *origin_x, - int *origin_y) { +template <typename Warp> +void CreateBrutePattern(const double* x1, + const double* y1, + const double* x2, + const double* y2, + const FloatImage& image1, + const FloatImage* image1_mask, + FloatArray* pattern, + FloatArray* mask, + int* origin_x, + int* origin_y) { // Get integer bounding box of quad2 in image2. int min_x = static_cast<int>(floor(*std::min_element(x2, x2 + 4))); int min_y = static_cast<int>(floor(*std::min_element(y2, y2 + 4))); - int max_x = static_cast<int>(ceil (*std::max_element(x2, x2 + 4))); - int max_y = static_cast<int>(ceil (*std::max_element(y2, y2 + 4))); + int max_x = static_cast<int>(ceil(*std::max_element(x2, x2 + 4))); + int max_y = static_cast<int>(ceil(*std::max_element(y2, y2 + 4))); int w = max_x - min_x; int h = max_y - min_y; @@ -1154,9 +1151,8 @@ void CreateBrutePattern(const double *x1, const double *y1, double dst_y = r; double src_x; double src_y; - inverse_warp.Forward(inverse_warp.parameters, - dst_x, dst_y, - &src_x, &src_y); + inverse_warp.Forward( + inverse_warp.parameters, dst_x, dst_y, &src_x, &src_y); if (PointInQuad(x1, y1, src_x, src_y)) { (*pattern)(i, j) = SampleLinear(image1, src_y, src_x); @@ -1191,24 +1187,32 @@ void CreateBrutePattern(const double *x1, const double *y1, // pattern, when doing brute initialization. Unfortunately that implies a // totally different warping interface, since access to more than a the source // and current destination frame is necessary. -template<typename Warp> -bool BruteTranslationOnlyInitialize(const FloatImage &image1, - const FloatImage *image1_mask, - const FloatImage &image2, +template <typename Warp> +bool BruteTranslationOnlyInitialize(const FloatImage& image1, + const FloatImage* image1_mask, + const FloatImage& image2, const int num_extra_points, const bool use_normalized_intensities, - const double *x1, const double *y1, - double *x2, double *y2) { + const double* x1, + const double* y1, + double* x2, + double* y2) { // Create the pattern to match in the space of image2, assuming our inital // guess isn't too far from the template in image1. If there is no image1 // mask, then the resulting mask is binary. FloatArray pattern; FloatArray mask; int origin_x = -1, origin_y = -1; - CreateBrutePattern<Warp>(x1, y1, x2, y2, - image1, image1_mask, - &pattern, &mask, - &origin_x, &origin_y); + CreateBrutePattern<Warp>(x1, + y1, + x2, + y2, + image1, + image1_mask, + &pattern, + &mask, + &origin_x, + &origin_y); // For normalization, premultiply the pattern by the inverse pattern mean. double mask_sum = 1.0; @@ -1251,8 +1255,10 @@ bool BruteTranslationOnlyInitialize(const FloatImage &image1, // instead, reducing the mean calculation to an O(1) operation. double inverse_search_mean = mask_sum / ((mask * search.block(r, c, h, w)).sum()); - sad = (mask * (pattern - (search.block(r, c, h, w) * - inverse_search_mean))).abs().sum(); + sad = (mask * + (pattern - (search.block(r, c, h, w) * inverse_search_mean))) + .abs() + .sum(); } else { sad = (mask * (pattern - search.block(r, c, h, w))).abs().sum(); } @@ -1274,9 +1280,8 @@ bool BruteTranslationOnlyInitialize(const FloatImage &image1, << "best_c: " << best_c << ", best_r: " << best_r << ", " << "origin_x: " << origin_x << ", origin_y: " << origin_y << ", " << "dc: " << (best_c - origin_x) << ", " - << "dr: " << (best_r - origin_y) - << ", tried " << ((image2.Height() - h) * (image2.Width() - w)) - << " shifts."; + << "dr: " << (best_r - origin_y) << ", tried " + << ((image2.Height() - h) * (image2.Width() - w)) << " shifts."; // Apply the shift. for (int i = 0; i < 4 + num_extra_points; ++i) { @@ -1286,8 +1291,10 @@ bool BruteTranslationOnlyInitialize(const FloatImage &image1, return true; } -void CopyQuad(double *src_x, double *src_y, - double *dst_x, double *dst_y, +void CopyQuad(double* src_x, + double* src_y, + double* dst_x, + double* dst_y, int num_extra_points) { for (int i = 0; i < 4 + num_extra_points; ++i) { dst_x[i] = src_x[i]; @@ -1297,16 +1304,18 @@ void CopyQuad(double *src_x, double *src_y, } // namespace -template<typename Warp> -void TemplatedTrackRegion(const FloatImage &image1, - const FloatImage &image2, - const double *x1, const double *y1, - const TrackRegionOptions &options, - double *x2, double *y2, - TrackRegionResult *result) { +template <typename Warp> +void TemplatedTrackRegion(const FloatImage& image1, + const FloatImage& image2, + const double* x1, + const double* y1, + const TrackRegionOptions& options, + double* x2, + double* y2, + TrackRegionResult* result) { for (int i = 0; i < 4 + options.num_extra_points; ++i) { - LG << "P" << i << ": (" << x1[i] << ", " << y1[i] << "); guess (" - << x2[i] << ", " << y2[i] << "); (dx, dy): (" << (x2[i] - x1[i]) << ", " + LG << "P" << i << ": (" << x1[i] << ", " << y1[i] << "); guess (" << x2[i] + << ", " << y2[i] << "); (dx, dy): (" << (x2[i] - x1[i]) << ", " << (y2[i] - y1[i]) << ")."; } @@ -1322,9 +1331,14 @@ void TemplatedTrackRegion(const FloatImage &image1, double y2_first_try[5]; CopyQuad(x2, y2, x2_first_try, y2_first_try, options.num_extra_points); - TemplatedTrackRegion<Warp>(image1, image2, - x1, y1, modified_options, - x2_first_try, y2_first_try, result); + TemplatedTrackRegion<Warp>(image1, + image2, + x1, + y1, + modified_options, + x2_first_try, + y2_first_try, + result); // Of the things that can happen in the first pass, don't try the brute // pass (and second attempt) if the error is one of the terminations below. @@ -1368,22 +1382,25 @@ void TemplatedTrackRegion(const FloatImage &image1, // Prepare the image and gradient. Array3Df image_and_gradient1; Array3Df image_and_gradient2; - BlurredImageAndDerivativesChannels(image1, options.sigma, - &image_and_gradient1); - BlurredImageAndDerivativesChannels(image2, options.sigma, - &image_and_gradient2); + BlurredImageAndDerivativesChannels( + image1, options.sigma, &image_and_gradient1); + BlurredImageAndDerivativesChannels( + image2, options.sigma, &image_and_gradient2); // Possibly do a brute-force translation-only initialization. if (SearchAreaTooBigForDescent(image2, x2, y2) && options.use_brute_initialization) { LG << "Running brute initialization..."; - bool found_any_alignment = BruteTranslationOnlyInitialize<Warp>( - image_and_gradient1, - options.image1_mask, - image2, - options.num_extra_points, - options.use_normalized_intensities, - x1, y1, x2, y2); + bool found_any_alignment = + BruteTranslationOnlyInitialize<Warp>(image_and_gradient1, + options.image1_mask, + image2, + options.num_extra_points, + options.use_normalized_intensities, + x1, + y1, + x2, + y2); if (!found_any_alignment) { LG << "Brute failed to find an alignment; pattern too small. " << "Failing entire track operation."; @@ -1391,9 +1408,9 @@ void TemplatedTrackRegion(const FloatImage &image1, return; } for (int i = 0; i < 4; ++i) { - LG << "P" << i << ": (" << x1[i] << ", " << y1[i] << "); brute (" - << x2[i] << ", " << y2[i] << "); (dx, dy): (" << (x2[i] - x1[i]) - << ", " << (y2[i] - y1[i]) << ")."; + LG << "P" << i << ": (" << x1[i] << ", " << y1[i] << "); brute (" << x2[i] + << ", " << y2[i] << "); (dx, dy): (" << (x2[i] - x1[i]) << ", " + << (y2[i] - y1[i]) << ")."; } } @@ -1408,14 +1425,13 @@ void TemplatedTrackRegion(const FloatImage &image1, PickSampling(x1, y1, x2, y2, &num_samples_x, &num_samples_y); // Compute the warp from rectangular coordinates. - Mat3 canonical_homography = ComputeCanonicalHomography(x1, y1, - num_samples_x, - num_samples_y); + Mat3 canonical_homography = + ComputeCanonicalHomography(x1, y1, num_samples_x, num_samples_y); ceres::Problem problem; // Construct the warp cost function. AutoDiffCostFunction takes ownership. - PixelDifferenceCostFunctor<Warp> *pixel_difference_cost_function = + PixelDifferenceCostFunctor<Warp>* pixel_difference_cost_function = new PixelDifferenceCostFunctor<Warp>(options, image_and_gradient1, image_and_gradient2, @@ -1424,28 +1440,24 @@ void TemplatedTrackRegion(const FloatImage &image1, num_samples_y, warp); problem.AddResidualBlock( - new ceres::AutoDiffCostFunction< - PixelDifferenceCostFunctor<Warp>, - ceres::DYNAMIC, - Warp::NUM_PARAMETERS>(pixel_difference_cost_function, - num_samples_x * num_samples_y), - NULL, - warp.parameters); + new ceres::AutoDiffCostFunction<PixelDifferenceCostFunctor<Warp>, + ceres::DYNAMIC, + Warp::NUM_PARAMETERS>( + pixel_difference_cost_function, num_samples_x * num_samples_y), + NULL, + warp.parameters); // Construct the regularizing cost function if (options.regularization_coefficient != 0.0) { - WarpRegularizingCostFunctor<Warp> *regularizing_warp_cost_function = - new WarpRegularizingCostFunctor<Warp>(options, - x1, y2, - x2_original, - y2_original, - warp); + WarpRegularizingCostFunctor<Warp>* regularizing_warp_cost_function = + new WarpRegularizingCostFunctor<Warp>( + options, x1, y2, x2_original, y2_original, warp); problem.AddResidualBlock( - new ceres::AutoDiffCostFunction< - WarpRegularizingCostFunctor<Warp>, - 8 /* num_residuals */, - Warp::NUM_PARAMETERS>(regularizing_warp_cost_function), + new ceres::AutoDiffCostFunction<WarpRegularizingCostFunctor<Warp>, + 8 /* num_residuals */, + Warp::NUM_PARAMETERS>( + regularizing_warp_cost_function), NULL, warp.parameters); } @@ -1488,10 +1500,10 @@ void TemplatedTrackRegion(const FloatImage &image1, return; } -#define HANDLE_TERMINATION(termination_enum) \ - if (summary.termination_type == ceres::termination_enum) { \ - result->termination = TrackRegionResult::termination_enum; \ - return; \ +#define HANDLE_TERMINATION(termination_enum) \ + if (summary.termination_type == ceres::termination_enum) { \ + result->termination = TrackRegionResult::termination_enum; \ + return; \ } // Avoid computing correlation for tracking failures. @@ -1499,8 +1511,9 @@ void TemplatedTrackRegion(const FloatImage &image1, // Otherwise, run a final correlation check. if (options.minimum_correlation > 0.0) { - result->correlation = pixel_difference_cost_function-> - PearsonProductMomentCorrelationCoefficient(warp.parameters); + result->correlation = + pixel_difference_cost_function + ->PearsonProductMomentCorrelationCoefficient(warp.parameters); if (result->correlation < options.minimum_correlation) { LG << "Failing with insufficient correlation."; result->termination = TrackRegionResult::INSUFFICIENT_CORRELATION; @@ -1523,36 +1536,39 @@ void TemplatedTrackRegion(const FloatImage &image1, #undef HANDLE_TERMINATION }; -void TrackRegion(const FloatImage &image1, - const FloatImage &image2, - const double *x1, const double *y1, - const TrackRegionOptions &options, - double *x2, double *y2, - TrackRegionResult *result) { +void TrackRegion(const FloatImage& image1, + const FloatImage& image2, + const double* x1, + const double* y1, + const TrackRegionOptions& options, + double* x2, + double* y2, + TrackRegionResult* result) { // Enum is necessary due to templated nature of autodiff. -#define HANDLE_MODE(mode_enum, mode_type) \ - if (options.mode == TrackRegionOptions::mode_enum) { \ - TemplatedTrackRegion<mode_type>(image1, image2, \ - x1, y1, \ - options, \ - x2, y2, \ - result); \ - return; \ +#define HANDLE_MODE(mode_enum, mode_type) \ + if (options.mode == TrackRegionOptions::mode_enum) { \ + TemplatedTrackRegion<mode_type>( \ + image1, image2, x1, y1, options, x2, y2, result); \ + return; \ } - HANDLE_MODE(TRANSLATION, TranslationWarp); - HANDLE_MODE(TRANSLATION_SCALE, TranslationScaleWarp); - HANDLE_MODE(TRANSLATION_ROTATION, TranslationRotationWarp); + HANDLE_MODE(TRANSLATION, TranslationWarp); + HANDLE_MODE(TRANSLATION_SCALE, TranslationScaleWarp); + HANDLE_MODE(TRANSLATION_ROTATION, TranslationRotationWarp); HANDLE_MODE(TRANSLATION_ROTATION_SCALE, TranslationRotationScaleWarp); - HANDLE_MODE(AFFINE, AffineWarp); - HANDLE_MODE(HOMOGRAPHY, HomographyWarp); + HANDLE_MODE(AFFINE, AffineWarp); + HANDLE_MODE(HOMOGRAPHY, HomographyWarp); #undef HANDLE_MODE } -bool SamplePlanarPatch(const FloatImage &image, - const double *xs, const double *ys, - int num_samples_x, int num_samples_y, - FloatImage *mask, FloatImage *patch, - double *warped_position_x, double *warped_position_y) { +bool SamplePlanarPatch(const FloatImage& image, + const double* xs, + const double* ys, + int num_samples_x, + int num_samples_y, + FloatImage* mask, + FloatImage* patch, + double* warped_position_x, + double* warped_position_y) { // Bail early if the points are outside the image. if (!AllInBounds(image, xs, ys)) { LG << "Can't sample patch: out of bounds."; @@ -1563,9 +1579,8 @@ bool SamplePlanarPatch(const FloatImage &image, patch->Resize(num_samples_y, num_samples_x, image.Depth()); // Compute the warp from rectangular coordinates. - Mat3 canonical_homography = ComputeCanonicalHomography(xs, ys, - num_samples_x, - num_samples_y); + Mat3 canonical_homography = + ComputeCanonicalHomography(xs, ys, num_samples_x, num_samples_y); // Walk over the coordinates in the canonical space, sampling from the image // in the original space and copying the result into the patch. @@ -1573,12 +1588,11 @@ bool SamplePlanarPatch(const FloatImage &image, for (int c = 0; c < num_samples_x; ++c) { Vec3 image_position = canonical_homography * Vec3(c, r, 1); image_position /= image_position(2); - SampleLinear(image, image_position(1), - image_position(0), - &(*patch)(r, c, 0)); + SampleLinear( + image, image_position(1), image_position(0), &(*patch)(r, c, 0)); if (mask) { - float mask_value = SampleLinear(*mask, image_position(1), - image_position(0), 0); + float mask_value = + SampleLinear(*mask, image_position(1), image_position(0), 0); for (int d = 0; d < image.Depth(); d++) (*patch)(r, c, d) *= mask_value; diff --git a/intern/libmv/libmv/tracking/track_region.h b/intern/libmv/libmv/tracking/track_region.h index 61dce22bcb8..7868e3b8b77 100644 --- a/intern/libmv/libmv/tracking/track_region.h +++ b/intern/libmv/libmv/tracking/track_region.h @@ -19,6 +19,7 @@ // IN THE SOFTWARE. #ifndef LIBMV_TRACKING_TRACK_REGION_H_ +#define LIBMV_TRACKING_TRACK_REGION_H_ #include "libmv/image/image.h" #include "libmv/image/sample.h" @@ -107,7 +108,7 @@ struct TrackRegionOptions { // If non-null, this is used as the pattern mask. It should match the size of // image1, even though only values inside the image1 quad are examined. The // values must be in the range 0.0 to 0.1. - FloatImage *image1_mask; + FloatImage* image1_mask; }; struct TrackRegionResult { @@ -128,8 +129,7 @@ struct TrackRegionResult { Termination termination; bool is_usable() { - return termination == CONVERGENCE || - termination == NO_CONVERGENCE; + return termination == CONVERGENCE || termination == NO_CONVERGENCE; } int num_iterations; @@ -140,12 +140,14 @@ struct TrackRegionResult { }; // Always needs 4 correspondences. -void TrackRegion(const FloatImage &image1, - const FloatImage &image2, - const double *x1, const double *y1, - const TrackRegionOptions &options, - double *x2, double *y2, - TrackRegionResult *result); +void TrackRegion(const FloatImage& image1, + const FloatImage& image2, + const double* x1, + const double* y1, + const TrackRegionOptions& options, + double* x2, + double* y2, + TrackRegionResult* result); // Sample a "canonical" version of the passed planar patch, using bilinear // sampling. The passed corners must be within the image, and have at least two @@ -156,11 +158,15 @@ void TrackRegion(const FloatImage &image1, // the size of image. // Warped coordinates of marker's position would be returned in // warped_position_x and warped_position_y -bool SamplePlanarPatch(const FloatImage &image, - const double *xs, const double *ys, - int num_samples_x, int num_samples_y, - FloatImage *mask, FloatImage *patch, - double *warped_position_x, double *warped_position_y); +bool SamplePlanarPatch(const FloatImage& image, + const double* xs, + const double* ys, + int num_samples_x, + int num_samples_y, + FloatImage* mask, + FloatImage* patch, + double* warped_position_x, + double* warped_position_y); } // namespace libmv diff --git a/intern/libmv/libmv/tracking/trklt_region_tracker.cc b/intern/libmv/libmv/tracking/trklt_region_tracker.cc index 05ef3d1d272..7ffa7555467 100644 --- a/intern/libmv/libmv/tracking/trklt_region_tracker.cc +++ b/intern/libmv/libmv/tracking/trklt_region_tracker.cc @@ -20,27 +20,29 @@ #include "libmv/tracking/trklt_region_tracker.h" -#include "libmv/logging/logging.h" -#include "libmv/numeric/numeric.h" -#include "libmv/image/image.h" #include "libmv/image/convolve.h" +#include "libmv/image/image.h" #include "libmv/image/sample.h" +#include "libmv/logging/logging.h" +#include "libmv/numeric/numeric.h" namespace libmv { // TODO(keir): Switch this to use the smarter LM loop like in ESM. // Computes U and e from the Ud = e equation (number 14) from the paper. -static void ComputeTrackingEquation(const Array3Df &image_and_gradient1, - const Array3Df &image_and_gradient2, - double x1, double y1, - double x2, double y2, +static void ComputeTrackingEquation(const Array3Df& image_and_gradient1, + const Array3Df& image_and_gradient2, + double x1, + double y1, + double x2, + double y2, int half_width, double lambda, - Mat2f *U, - Vec2f *e) { + Mat2f* U, + Vec2f* e) { Mat2f A, B, C, D; - A = B = C = D = Mat2f::Zero(); + A = B = C = D = Mat2f::Zero(); Vec2f R, S, V, W; R = S = V = W = Vec2f::Zero(); @@ -57,9 +59,9 @@ static void ComputeTrackingEquation(const Array3Df &image_and_gradient1, Vec2f gI, gJ; gI << SampleLinear(image_and_gradient1, yy1, xx1, 1), - SampleLinear(image_and_gradient1, yy1, xx1, 2); + SampleLinear(image_and_gradient1, yy1, xx1, 2); gJ << SampleLinear(image_and_gradient2, yy2, xx2, 1), - SampleLinear(image_and_gradient2, yy2, xx2, 2); + SampleLinear(image_and_gradient2, yy2, xx2, 2); // Equation 15 from the paper. A += gI * gI.transpose(); @@ -77,26 +79,25 @@ static void ComputeTrackingEquation(const Array3Df &image_and_gradient1, Mat2f Di = B.transpose().inverse(); // Equation 14 from the paper. - *U = A*Di*C + lambda*Di*C - 0.5*B; - *e = (A + lambda*Mat2f::Identity())*Di*(V - W) + 0.5*(S - R); + *U = A * Di * C + lambda * Di * C - 0.5 * B; + *e = (A + lambda * Mat2f::Identity()) * Di * (V - W) + 0.5 * (S - R); } -static bool RegionIsInBounds(const FloatImage &image1, - double x, double y, - int half_window_size) { +static bool RegionIsInBounds(const FloatImage& image1, + double x, + double y, + int half_window_size) { // Check the minimum coordinates. int min_x = floor(x) - half_window_size - 1; int min_y = floor(y) - half_window_size - 1; - if (min_x < 0.0 || - min_y < 0.0) { + if (min_x < 0.0 || min_y < 0.0) { return false; } // Check the maximum coordinates. int max_x = ceil(x) + half_window_size + 1; int max_y = ceil(y) + half_window_size + 1; - if (max_x > image1.cols() || - max_y > image1.rows()) { + if (max_x > image1.cols() || max_y > image1.rows()) { return false; } @@ -104,10 +105,12 @@ static bool RegionIsInBounds(const FloatImage &image1, return true; } -bool TrkltRegionTracker::Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const { +bool TrkltRegionTracker::Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const { if (!RegionIsInBounds(image1, x1, y1, half_window_size)) { LG << "Fell out of image1's window with x1=" << x1 << ", y1=" << y1 << ", hw=" << half_window_size << "."; @@ -134,11 +137,14 @@ bool TrkltRegionTracker::Track(const FloatImage &image1, Vec2f e; ComputeTrackingEquation(image_and_gradient1, image_and_gradient2, - x1, y1, - *x2, *y2, + x1, + y1, + *x2, + *y2, half_window_size, lambda, - &U, &e); + &U, + &e); // Solve the linear system for the best update to x2 and y2. d = U.lu().solve(e); @@ -161,7 +167,6 @@ bool TrkltRegionTracker::Track(const FloatImage &image1, LG << "x=" << *x2 << ", y=" << *y2 << ", dx=" << d[0] << ", dy=" << d[1] << ", det=" << determinant; - // If the update is small, then we probably found the target. if (d.squaredNorm() < min_update_squared_distance) { LG << "Successful track in " << i << " iterations."; diff --git a/intern/libmv/libmv/tracking/trklt_region_tracker.h b/intern/libmv/libmv/tracking/trklt_region_tracker.h index 26d0621aa02..a9cf5580f61 100644 --- a/intern/libmv/libmv/tracking/trklt_region_tracker.h +++ b/intern/libmv/libmv/tracking/trklt_region_tracker.h @@ -46,10 +46,12 @@ struct TrkltRegionTracker : public RegionTracker { virtual ~TrkltRegionTracker() {} // Tracker interface. - virtual bool Track(const FloatImage &image1, - const FloatImage &image2, - double x1, double y1, - double *x2, double *y2) const; + virtual bool Track(const FloatImage& image1, + const FloatImage& image2, + double x1, + double y1, + double* x2, + double* y2) const; // No point in creating getters or setters. int half_window_size; |