diff options
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; |