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Diffstat (limited to 'libavfilter/opencl')
-rw-r--r-- | libavfilter/opencl/deshake.cl | 647 |
1 files changed, 647 insertions, 0 deletions
diff --git a/libavfilter/opencl/deshake.cl b/libavfilter/opencl/deshake.cl new file mode 100644 index 0000000000..fef2681dc6 --- /dev/null +++ b/libavfilter/opencl/deshake.cl @@ -0,0 +1,647 @@ +/* + * This file is part of FFmpeg. + * + * FFmpeg is free software; you can redistribute it and/or + * modify it under the terms of the GNU Lesser General Public + * License as published by the Free Software Foundation; either + * version 2.1 of the License, or (at your option) any later version. + * + * FFmpeg is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU + * Lesser General Public License for more details. + * + * You should have received a copy of the GNU Lesser General Public + * License along with FFmpeg; if not, write to the Free Software + * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA + * + * Copyright (C) 2000, Intel Corporation, all rights reserved. + * Copyright (C) 2013, OpenCV Foundation, all rights reserved. + * Third party copyrights are property of their respective owners. + * + * Redistribution and use in source and binary forms, with or without modification, + * are permitted provided that the following conditions are met: + * + * * Redistribution's of source code must retain the above copyright notice, + * this list of conditions and the following disclaimer. + * + * * Redistribution's in binary form must reproduce the above copyright notice, + * this list of conditions and the following disclaimer in the documentation + * and/or other materials provided with the distribution. + * + * * The name of the copyright holders may not be used to endorse or promote products + * derived from this software without specific prior written permission. + * + * This software is provided by the copyright holders and contributors "as is" and + * any express or implied warranties, including, but not limited to, the implied + * warranties of merchantability and fitness for a particular purpose are disclaimed. + * In no event shall the Intel Corporation or contributors be liable for any direct, + * indirect, incidental, special, exemplary, or consequential damages + * (including, but not limited to, procurement of substitute goods or services; + * loss of use, data, or profits; or business interruption) however caused + * and on any theory of liability, whether in contract, strict liability, + * or tort (including negligence or otherwise) arising in any way out of + * the use of this software, even if advised of the possibility of such damage. + */ + +#define HARRIS_THRESHOLD 3.0f +// Block size over which to compute harris response +// +// Note that changing this will require fiddling with the local array sizes in +// harris_response +#define HARRIS_RADIUS 2 +#define DISTANCE_THRESHOLD 80 + +// Sub-pixel refinement window for feature points +#define REFINE_WIN_HALF_W 5 +#define REFINE_WIN_HALF_H 5 +#define REFINE_WIN_W 11 // REFINE_WIN_HALF_W * 2 + 1 +#define REFINE_WIN_H 11 + +// Non-maximum suppression window size +#define NONMAX_WIN 30 +#define NONMAX_WIN_HALF 15 // NONMAX_WIN / 2 + +typedef struct PointPair { + // Previous frame + float2 p1; + // Current frame + float2 p2; +} PointPair; + +typedef struct SmoothedPointPair { + // Non-smoothed point in current frame + int2 p1; + // Smoothed point in current frame + float2 p2; +} SmoothedPointPair; + +typedef struct MotionVector { + PointPair p; + // Used to mark vectors as potential outliers + int should_consider; +} MotionVector; + +const sampler_t sampler = CLK_NORMALIZED_COORDS_FALSE | + CLK_ADDRESS_CLAMP_TO_EDGE | + CLK_FILTER_NEAREST; + +const sampler_t sampler_linear = CLK_NORMALIZED_COORDS_FALSE | + CLK_ADDRESS_CLAMP_TO_EDGE | + CLK_FILTER_LINEAR; + +const sampler_t sampler_linear_mirror = CLK_NORMALIZED_COORDS_TRUE | + CLK_ADDRESS_MIRRORED_REPEAT | + CLK_FILTER_LINEAR; + +// Writes to a 1D array at loc, treating it as a 2D array with the same +// dimensions as the global work size. +static void write_to_1d_arrf(__global float *buf, int2 loc, float val) { + buf[loc.x + loc.y * get_global_size(0)] = val; +} + +static void write_to_1d_arrul8(__global ulong8 *buf, int2 loc, ulong8 val) { + buf[loc.x + loc.y * get_global_size(0)] = val; +} + +static void write_to_1d_arrvec(__global MotionVector *buf, int2 loc, MotionVector val) { + buf[loc.x + loc.y * get_global_size(0)] = val; +} + +static void write_to_1d_arrf2(__global float2 *buf, int2 loc, float2 val) { + buf[loc.x + loc.y * get_global_size(0)] = val; +} + +static ulong8 read_from_1d_arrul8(__global const ulong8 *buf, int2 loc) { + return buf[loc.x + loc.y * get_global_size(0)]; +} + +static float2 read_from_1d_arrf2(__global const float2 *buf, int2 loc) { + return buf[loc.x + loc.y * get_global_size(0)]; +} + +// Returns the grayscale value at the given point. +static float pixel_grayscale(__read_only image2d_t src, int2 loc) { + float4 pixel = read_imagef(src, sampler, loc); + return (pixel.x + pixel.y + pixel.z) / 3.0f; +} + +static float convolve( + __local const float *grayscale, + int local_idx_x, + int local_idx_y, + float mask[3][3] +) { + float ret = 0; + + // These loops touch each pixel surrounding loc as well as loc itself + for (int i = 1, i2 = 0; i >= -1; --i, ++i2) { + for (int j = -1, j2 = 0; j <= 1; ++j, ++j2) { + ret += mask[i2][j2] * grayscale[(local_idx_x + 3 + j) + (local_idx_y + 3 + i) * 14]; + } + } + + return ret; +} + +// Sums dx * dy for all pixels within radius of loc +static float sum_deriv_prod( + __local const float *grayscale, + float mask_x[3][3], + float mask_y[3][3] +) { + float ret = 0; + + for (int i = HARRIS_RADIUS; i >= -HARRIS_RADIUS; --i) { + for (int j = -HARRIS_RADIUS; j <= HARRIS_RADIUS; ++j) { + ret += convolve(grayscale, get_local_id(0) + j, get_local_id(1) + i, mask_x) * + convolve(grayscale, get_local_id(0) + j, get_local_id(1) + i, mask_y); + } + } + + return ret; +} + +// Sums d<>^2 (determined by mask) for all pixels within radius of loc +static float sum_deriv_pow(__local const float *grayscale, float mask[3][3]) +{ + float ret = 0; + + for (int i = HARRIS_RADIUS; i >= -HARRIS_RADIUS; --i) { + for (int j = -HARRIS_RADIUS; j <= HARRIS_RADIUS; ++j) { + float deriv = convolve(grayscale, get_local_id(0) + j, get_local_id(1) + i, mask); + ret += deriv * deriv; + } + } + + return ret; +} + +// Fills a box with the given radius and pixel around loc +static void draw_box(__write_only image2d_t dst, int2 loc, float4 pixel, int radius) +{ + for (int i = -radius; i <= radius; ++i) { + for (int j = -radius; j <= radius; ++j) { + write_imagef( + dst, + (int2)( + // Clamp to avoid writing outside image bounds + clamp(loc.x + i, 0, get_image_dim(dst).x - 1), + clamp(loc.y + j, 0, get_image_dim(dst).y - 1) + ), + pixel + ); + } + } +} + +// Converts the src image to grayscale +__kernel void grayscale( + __read_only image2d_t src, + __write_only image2d_t grayscale +) { + int2 loc = (int2)(get_global_id(0), get_global_id(1)); + write_imagef(grayscale, loc, (float4)(pixel_grayscale(src, loc), 0.0f, 0.0f, 1.0f)); +} + +// This kernel computes the harris response for the given grayscale src image +// within the given radius and writes it to harris_buf +__kernel void harris_response( + __read_only image2d_t grayscale, + __global float *harris_buf +) { + int2 loc = (int2)(get_global_id(0), get_global_id(1)); + + if (loc.x > get_image_width(grayscale) - 1 || loc.y > get_image_height(grayscale) - 1) { + write_to_1d_arrf(harris_buf, loc, 0); + return; + } + + float scale = 1.0f / ((1 << 2) * HARRIS_RADIUS * 255.0f); + + float sobel_mask_x[3][3] = { + {-1, 0, 1}, + {-2, 0, 2}, + {-1, 0, 1} + }; + + float sobel_mask_y[3][3] = { + { 1, 2, 1}, + { 0, 0, 0}, + {-1, -2, -1} + }; + + // 8 x 8 local work + 3 pixels around each side (needed to accomodate for the + // block size radius of 2) + __local float grayscale_data[196]; + + int idx = get_group_id(0) * get_local_size(0); + int idy = get_group_id(1) * get_local_size(1); + + for (int i = idy - 3, it = 0; i < idy + (int)get_local_size(1) + 3; i++, it++) { + for (int j = idx - 3, jt = 0; j < idx + (int)get_local_size(0) + 3; j++, jt++) { + grayscale_data[jt + it * 14] = read_imagef(grayscale, sampler, (int2)(j, i)).x; + } + } + + barrier(CLK_LOCAL_MEM_FENCE); + + float sumdxdy = sum_deriv_prod(grayscale_data, sobel_mask_x, sobel_mask_y); + float sumdx2 = sum_deriv_pow(grayscale_data, sobel_mask_x); + float sumdy2 = sum_deriv_pow(grayscale_data, sobel_mask_y); + + float trace = sumdx2 + sumdy2; + // r = det(M) - k(trace(M))^2 + // k usually between 0.04 to 0.06 + float r = (sumdx2 * sumdy2 - sumdxdy * sumdxdy) - 0.04f * (trace * trace) * pown(scale, 4); + + // Threshold the r value + harris_buf[loc.x + loc.y * get_image_width(grayscale)] = r * step(HARRIS_THRESHOLD, r); +} + +// Gets a patch centered around a float coordinate from a grayscale image using +// bilinear interpolation +static void get_rect_sub_pix( + __read_only image2d_t grayscale, + float *buffer, + int size_x, + int size_y, + float2 center +) { + float2 offset = ((float2)(size_x, size_y) - 1.0f) * 0.5f; + + for (int i = 0; i < size_y; i++) { + for (int j = 0; j < size_x; j++) { + buffer[i * size_x + j] = read_imagef( + grayscale, + sampler_linear, + (float2)(j, i) + center - offset + ).x * 255.0f; + } + } +} + +// Refines detected features at a sub-pixel level +// +// This function is ported from OpenCV +static float2 corner_sub_pix( + __read_only image2d_t grayscale, + float2 feature, + float *mask +) { + float2 init = feature; + int src_width = get_global_size(0); + int src_height = get_global_size(1); + + const int max_iters = 40; + const float eps = 0.001f * 0.001f; + int i, j, k; + + int iter = 0; + float err = 0; + float subpix[(REFINE_WIN_W + 2) * (REFINE_WIN_H + 2)]; + const float flt_epsilon = 0x1.0p-23f; + + do { + float2 feature_tmp; + float a = 0, b = 0, c = 0, bb1 = 0, bb2 = 0; + + get_rect_sub_pix(grayscale, subpix, REFINE_WIN_W + 2, REFINE_WIN_H + 2, feature); + float *subpix_ptr = subpix; + subpix_ptr += REFINE_WIN_W + 2 + 1; + + // process gradient + for (i = 0, k = 0; i < REFINE_WIN_H; i++, subpix_ptr += REFINE_WIN_W + 2) { + float py = i - REFINE_WIN_HALF_H; + + for (j = 0; j < REFINE_WIN_W; j++, k++) { + float m = mask[k]; + float tgx = subpix_ptr[j + 1] - subpix_ptr[j - 1]; + float tgy = subpix_ptr[j + REFINE_WIN_W + 2] - subpix_ptr[j - REFINE_WIN_W - 2]; + float gxx = tgx * tgx * m; + float gxy = tgx * tgy * m; + float gyy = tgy * tgy * m; + float px = j - REFINE_WIN_HALF_W; + + a += gxx; + b += gxy; + c += gyy; + + bb1 += gxx * px + gxy * py; + bb2 += gxy * px + gyy * py; + } + } + + float det = a * c - b * b; + if (fabs(det) <= flt_epsilon * flt_epsilon) { + break; + } + + // 2x2 matrix inversion + float scale = 1.0f / det; + feature_tmp.x = (float)(feature.x + (c * scale * bb1) - (b * scale * bb2)); + feature_tmp.y = (float)(feature.y - (b * scale * bb1) + (a * scale * bb2)); + err = dot(feature_tmp - feature, feature_tmp - feature); + + feature = feature_tmp; + if (feature.x < 0 || feature.x >= src_width || feature.y < 0 || feature.y >= src_height) { + break; + } + } while (++iter < max_iters && err > eps); + + // Make sure new point isn't too far from the initial point (indicates poor convergence) + if (fabs(feature.x - init.x) > REFINE_WIN_HALF_W || fabs(feature.y - init.y) > REFINE_WIN_HALF_H) { + feature = init; + } + + return feature; +} + +// Performs non-maximum suppression on the harris response and writes the resulting +// feature locations to refined_features. +// +// Assumes that refined_features and the global work sizes are set up such that the image +// is split up into a grid of 32x32 blocks where each block has a single slot in the +// refined_features buffer. This kernel finds the best corner in each block (if the +// block has any) and writes it to the corresponding slot in the buffer. +// +// If subpixel_refine is true, the features are additionally refined at a sub-pixel +// level for increased precision. +__kernel void refine_features( + __read_only image2d_t grayscale, + __global const float *harris_buf, + __global float2 *refined_features, + int subpixel_refine +) { + int2 loc = (int2)(get_global_id(0), get_global_id(1)); + // The location in the grayscale buffer rather than the compacted grid + int2 loc_i = (int2)(loc.x * 32, loc.y * 32); + + float new_val; + float max_val = 0; + float2 loc_max = (float2)(-1, -1); + + int end_x = min(loc_i.x + 32, (int)get_image_dim(grayscale).x - 1); + int end_y = min(loc_i.y + 32, (int)get_image_dim(grayscale).y - 1); + + for (int i = loc_i.x; i < end_x; ++i) { + for (int j = loc_i.y; j < end_y; ++j) { + new_val = harris_buf[i + j * get_image_dim(grayscale).x]; + + if (new_val > max_val) { + max_val = new_val; + loc_max = (float2)(i, j); + } + } + } + + if (max_val == 0) { + // There are no features in this part of the frame + write_to_1d_arrf2(refined_features, loc, loc_max); + return; + } + + if (subpixel_refine) { + float mask[REFINE_WIN_H * REFINE_WIN_W]; + for (int i = 0; i < REFINE_WIN_H; i++) { + float y = (float)(i - REFINE_WIN_HALF_H) / REFINE_WIN_HALF_H; + float vy = exp(-y * y); + + for (int j = 0; j < REFINE_WIN_W; j++) { + float x = (float)(j - REFINE_WIN_HALF_W) / REFINE_WIN_HALF_W; + mask[i * REFINE_WIN_W + j] = (float)(vy * exp(-x * x)); + } + } + + loc_max = corner_sub_pix(grayscale, loc_max, mask); + } + + write_to_1d_arrf2(refined_features, loc, loc_max); +} + +// Extracts BRIEF descriptors from the grayscale src image for the given features +// using the provided sampler. +__kernel void brief_descriptors( + __read_only image2d_t grayscale, + __global const float2 *refined_features, + // for 512 bit descriptors + __global ulong8 *desc_buf, + __global const PointPair *brief_pattern +) { + int2 loc = (int2)(get_global_id(0), get_global_id(1)); + float2 feature = read_from_1d_arrf2(refined_features, loc); + + // There was no feature in this part of the frame + if (feature.x == -1) { + write_to_1d_arrul8(desc_buf, loc, (ulong8)(0)); + return; + } + + ulong8 desc = 0; + ulong *p = &desc; + + for (int i = 0; i < 8; ++i) { + for (int j = 0; j < 64; ++j) { + PointPair pair = brief_pattern[j * (i + 1)]; + float l1 = read_imagef(grayscale, sampler_linear, feature + pair.p1).x; + float l2 = read_imagef(grayscale, sampler_linear, feature + pair.p2).x; + + if (l1 < l2) { + p[i] |= 1UL << j; + } + } + } + + write_to_1d_arrul8(desc_buf, loc, desc); +} + +// Given buffers with descriptors for the current and previous frame, determines +// which ones match, writing correspondences to matches_buf. +// +// Feature and descriptor buffers are assumed to be compacted (each element sourced +// from a 32x32 block in the frame being processed). +__kernel void match_descriptors( + __global const float2 *prev_refined_features, + __global const float2 *refined_features, + __global const ulong8 *desc_buf, + __global const ulong8 *prev_desc_buf, + __global MotionVector *matches_buf +) { + int2 loc = (int2)(get_global_id(0), get_global_id(1)); + ulong8 desc = read_from_1d_arrul8(desc_buf, loc); + const int search_radius = 3; + + MotionVector invalid_vector = (MotionVector) { + (PointPair) { + (float2)(-1, -1), + (float2)(-1, -1) + }, + 0 + }; + + if (desc.s0 == 0 && desc.s1 == 0) { + // There was no feature in this part of the frame + write_to_1d_arrvec( + matches_buf, + loc, + invalid_vector + ); + return; + } + + int2 start = max(loc - search_radius, 0); + int2 end = min(loc + search_radius, (int2)(get_global_size(0) - 1, get_global_size(1) - 1)); + + for (int i = start.x; i < end.x; ++i) { + for (int j = start.y; j < end.y; ++j) { + int2 prev_point = (int2)(i, j); + int total_dist = 0; + + ulong8 prev_desc = read_from_1d_arrul8(prev_desc_buf, prev_point); + + if (prev_desc.s0 == 0 && prev_desc.s1 == 0) { + continue; + } + + ulong *prev_desc_p = &prev_desc; + ulong *desc_p = &desc; + + for (int i = 0; i < 8; i++) { + total_dist += popcount(desc_p[i] ^ prev_desc_p[i]); + } + + if (total_dist < DISTANCE_THRESHOLD) { + write_to_1d_arrvec( + matches_buf, + loc, + (MotionVector) { + (PointPair) { + read_from_1d_arrf2(prev_refined_features, prev_point), + read_from_1d_arrf2(refined_features, loc) + }, + 1 + } + ); + + return; + } + } + } + + // There is no found match for this point + write_to_1d_arrvec( + matches_buf, + loc, + invalid_vector + ); +} + +// Returns the position of the given point after the transform is applied +static float2 transformed_point(float2 p, __global const float *transform) { + float2 ret; + + ret.x = p.x * transform[0] + p.y * transform[1] + transform[2]; + ret.y = p.x * transform[3] + p.y * transform[4] + transform[5]; + + return ret; +} + + +// Performs the given transform on the src image +__kernel void transform( + __read_only image2d_t src, + __write_only image2d_t dst, + __global const float *transform +) { + int2 loc = (int2)(get_global_id(0), get_global_id(1)); + float2 norm = convert_float2(get_image_dim(src)); + + write_imagef( + dst, + loc, + read_imagef( + src, + sampler_linear_mirror, + transformed_point((float2)(loc.x, loc.y), transform) / norm + ) + ); +} + +// Returns the new location of the given point using the given crop bounding box +// and the width and height of the original frame. +static float2 cropped_point( + float2 p, + float2 top_left, + float2 bottom_right, + int2 orig_dim +) { + float2 ret; + + float crop_width = bottom_right.x - top_left.x; + float crop_height = bottom_right.y - top_left.y; + + float width_norm = p.x / (float)orig_dim.x; + float height_norm = p.y / (float)orig_dim.y; + + ret.x = (width_norm * crop_width) + top_left.x; + ret.y = (height_norm * crop_height) + ((float)orig_dim.y - bottom_right.y); + + return ret; +} + +// Upscales the given cropped region to the size of the original frame +__kernel void crop_upscale( + __read_only image2d_t src, + __write_only image2d_t dst, + float2 top_left, + float2 bottom_right +) { + int2 loc = (int2)(get_global_id(0), get_global_id(1)); + + write_imagef( + dst, + loc, + read_imagef( + src, + sampler_linear, + cropped_point((float2)(loc.x, loc.y), top_left, bottom_right, get_image_dim(dst)) + ) + ); +} + +// Draws boxes to represent the given point matches and uses the given transform +// and crop info to make sure their positions are accurate on the transformed frame. +// +// model_matches is an array of three points that were used by the RANSAC process +// to generate the given transform +__kernel void draw_debug_info( + __write_only image2d_t dst, + __global const MotionVector *matches, + __global const MotionVector *model_matches, + int num_model_matches, + __global const float *transform +) { + int loc = get_global_id(0); + MotionVector vec = matches[loc]; + // Black box: matched point that RANSAC considered an outlier + float4 big_rect_color = (float4)(0.1f, 0.1f, 0.1f, 1.0f); + + if (vec.should_consider) { + // Green box: matched point that RANSAC considered an inlier + big_rect_color = (float4)(0.0f, 1.0f, 0.0f, 1.0f); + } + + for (int i = 0; i < num_model_matches; i++) { + if (vec.p.p2.x == model_matches[i].p.p2.x && vec.p.p2.y == model_matches[i].p.p2.y) { + // Orange box: point used to calculate model + big_rect_color = (float4)(1.0f, 0.5f, 0.0f, 1.0f); + } + } + + float2 transformed_p1 = transformed_point(vec.p.p1, transform); + float2 transformed_p2 = transformed_point(vec.p.p2, transform); + + draw_box(dst, (int2)(transformed_p2.x, transformed_p2.y), big_rect_color, 5); + // Small light blue box: the point in the previous frame + draw_box(dst, (int2)(transformed_p1.x, transformed_p1.y), (float4)(0.0f, 0.3f, 0.7f, 1.0f), 3); +} |