From 36e42084f0dba16ac4c9d99e27b8eb577f58e4d4 Mon Sep 17 00:00:00 2001 From: Vladislav Vinogradov Date: Wed, 13 Feb 2013 15:57:40 +0400 Subject: [PATCH] added gpu BM optical flow implementation --- modules/gpu/include/opencv2/gpu/gpu.hpp | 18 ++ modules/gpu/perf/perf_video.cpp | 117 +++++++++ modules/gpu/src/cuda/optflowbm.cu | 414 ++++++++++++++++++++++++++++++++ modules/gpu/src/optflowbm.cpp | 243 +++++++++++++++++++ modules/gpu/test/test_optflow.cpp | 175 ++++++++++++++ 5 files changed, 967 insertions(+) create mode 100644 modules/gpu/src/cuda/optflowbm.cu create mode 100644 modules/gpu/src/optflowbm.cpp diff --git a/modules/gpu/include/opencv2/gpu/gpu.hpp b/modules/gpu/include/opencv2/gpu/gpu.hpp index 090392b..7cc57e4 100644 --- a/modules/gpu/include/opencv2/gpu/gpu.hpp +++ b/modules/gpu/include/opencv2/gpu/gpu.hpp @@ -2074,6 +2074,24 @@ private: }; +//! Calculates optical flow for 2 images using block matching algorithm */ +CV_EXPORTS void calcOpticalFlowBM(const GpuMat& prev, const GpuMat& curr, + Size block_size, Size shift_size, Size max_range, bool use_previous, + GpuMat& velx, GpuMat& vely, GpuMat& buf, + Stream& stream = Stream::Null()); + +class CV_EXPORTS FastOpticalFlowBM +{ +public: + void operator ()(const GpuMat& I0, const GpuMat& I1, GpuMat& flowx, GpuMat& flowy, int search_window = 21, int block_window = 7, Stream& s = Stream::Null()); + +private: + GpuMat buffer; + GpuMat extended_I0; + GpuMat extended_I1; +}; + + //! Interpolate frames (images) using provided optical flow (displacement field). //! frame0 - frame 0 (32-bit floating point images, single channel) //! frame1 - frame 1 (the same type and size) diff --git a/modules/gpu/perf/perf_video.cpp b/modules/gpu/perf/perf_video.cpp index b228580..bf2fd99 100644 --- a/modules/gpu/perf/perf_video.cpp +++ b/modules/gpu/perf/perf_video.cpp @@ -445,6 +445,123 @@ PERF_TEST_P(ImagePair, Video_OpticalFlowDual_TVL1, } ////////////////////////////////////////////////////// +// OpticalFlowBM + +void calcOpticalFlowBM(const cv::Mat& prev, const cv::Mat& curr, + cv::Size bSize, cv::Size shiftSize, cv::Size maxRange, int usePrevious, + cv::Mat& velx, cv::Mat& vely) +{ + cv::Size sz((curr.cols - bSize.width + shiftSize.width)/shiftSize.width, (curr.rows - bSize.height + shiftSize.height)/shiftSize.height); + + velx.create(sz, CV_32FC1); + vely.create(sz, CV_32FC1); + + CvMat cvprev = prev; + CvMat cvcurr = curr; + + CvMat cvvelx = velx; + CvMat cvvely = vely; + + cvCalcOpticalFlowBM(&cvprev, &cvcurr, bSize, shiftSize, maxRange, usePrevious, &cvvelx, &cvvely); +} + +PERF_TEST_P(ImagePair, Video_OpticalFlowBM, + Values(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png"))) +{ + declare.time(400); + + cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE); + ASSERT_FALSE(frame0.empty()); + + cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE); + ASSERT_FALSE(frame1.empty()); + + cv::Size block_size(16, 16); + cv::Size shift_size(1, 1); + cv::Size max_range(16, 16); + + if (PERF_RUN_GPU()) + { + cv::gpu::GpuMat d_frame0(frame0); + cv::gpu::GpuMat d_frame1(frame1); + cv::gpu::GpuMat d_velx, d_vely, buf; + + cv::gpu::calcOpticalFlowBM(d_frame0, d_frame1, block_size, shift_size, max_range, false, d_velx, d_vely, buf); + + TEST_CYCLE() + { + cv::gpu::calcOpticalFlowBM(d_frame0, d_frame1, block_size, shift_size, max_range, false, d_velx, d_vely, buf); + } + + GPU_SANITY_CHECK(d_velx); + GPU_SANITY_CHECK(d_vely); + } + else + { + cv::Mat velx, vely; + + calcOpticalFlowBM(frame0, frame1, block_size, shift_size, max_range, false, velx, vely); + + TEST_CYCLE() + { + calcOpticalFlowBM(frame0, frame1, block_size, shift_size, max_range, false, velx, vely); + } + + CPU_SANITY_CHECK(velx); + CPU_SANITY_CHECK(vely); + } +} + +PERF_TEST_P(ImagePair, Video_FastOpticalFlowBM, + Values(make_pair("gpu/opticalflow/frame0.png", "gpu/opticalflow/frame1.png"))) +{ + declare.time(400); + + cv::Mat frame0 = readImage(GetParam().first, cv::IMREAD_GRAYSCALE); + ASSERT_FALSE(frame0.empty()); + + cv::Mat frame1 = readImage(GetParam().second, cv::IMREAD_GRAYSCALE); + ASSERT_FALSE(frame1.empty()); + + cv::Size block_size(16, 16); + cv::Size shift_size(1, 1); + cv::Size max_range(16, 16); + + if (PERF_RUN_GPU()) + { + cv::gpu::GpuMat d_frame0(frame0); + cv::gpu::GpuMat d_frame1(frame1); + cv::gpu::GpuMat d_velx, d_vely; + + cv::gpu::FastOpticalFlowBM fastBM; + + fastBM(d_frame0, d_frame1, d_velx, d_vely, max_range.width, block_size.width); + + TEST_CYCLE() + { + fastBM(d_frame0, d_frame1, d_velx, d_vely, max_range.width, block_size.width); + } + + GPU_SANITY_CHECK(d_velx); + GPU_SANITY_CHECK(d_vely); + } + else + { + cv::Mat velx, vely; + + calcOpticalFlowBM(frame0, frame1, block_size, shift_size, max_range, false, velx, vely); + + TEST_CYCLE() + { + calcOpticalFlowBM(frame0, frame1, block_size, shift_size, max_range, false, velx, vely); + } + + CPU_SANITY_CHECK(velx); + CPU_SANITY_CHECK(vely); + } +} + +////////////////////////////////////////////////////// // FGDStatModel DEF_PARAM_TEST_1(Video, string); diff --git a/modules/gpu/src/cuda/optflowbm.cu b/modules/gpu/src/cuda/optflowbm.cu new file mode 100644 index 0000000..baf8dfb --- /dev/null +++ b/modules/gpu/src/cuda/optflowbm.cu @@ -0,0 +1,414 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., 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 bpied warranties, including, but not limited to, the bpied +// 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. +// +//M*/ + +#if !defined CUDA_DISABLER + +#include "opencv2/gpu/device/common.hpp" +#include "opencv2/gpu/device/limits.hpp" +#include "opencv2/gpu/device/functional.hpp" +#include "opencv2/gpu/device/reduce.hpp" + +using namespace cv::gpu; +using namespace cv::gpu::device; + +namespace optflowbm +{ + texture tex_prev(false, cudaFilterModePoint, cudaAddressModeClamp); + texture tex_curr(false, cudaFilterModePoint, cudaAddressModeClamp); + + __device__ int cmpBlocks(int X1, int Y1, int X2, int Y2, int2 blockSize) + { + int s = 0; + + for (int y = 0; y < blockSize.y; ++y) + { + for (int x = 0; x < blockSize.x; ++x) + s += ::abs(tex2D(tex_prev, X1 + x, Y1 + y) - tex2D(tex_curr, X2 + x, Y2 + y)); + } + + return s; + } + + __global__ void calcOptFlowBM(PtrStepSzf velx, PtrStepf vely, const int2 blockSize, const int2 shiftSize, const bool usePrevious, + const int maxX, const int maxY, const int acceptLevel, const int escapeLevel, + const short2* ss, const int ssCount) + { + const int j = blockIdx.x * blockDim.x + threadIdx.x; + const int i = blockIdx.y * blockDim.y + threadIdx.y; + + if (i >= velx.rows || j >= velx.cols) + return; + + const int X1 = j * shiftSize.x; + const int Y1 = i * shiftSize.y; + + const int offX = usePrevious ? __float2int_rn(velx(i, j)) : 0; + const int offY = usePrevious ? __float2int_rn(vely(i, j)) : 0; + + int X2 = X1 + offX; + int Y2 = Y1 + offY; + + int dist = numeric_limits::max(); + + if (0 <= X2 && X2 <= maxX && 0 <= Y2 && Y2 <= maxY) + dist = cmpBlocks(X1, Y1, X2, Y2, blockSize); + + int countMin = 1; + int sumx = offX; + int sumy = offY; + + if (dist > acceptLevel) + { + // do brute-force search + for (int k = 0; k < ssCount; ++k) + { + const short2 ssVal = ss[k]; + + const int dx = offX + ssVal.x; + const int dy = offY + ssVal.y; + + X2 = X1 + dx; + Y2 = Y1 + dy; + + if (0 <= X2 && X2 <= maxX && 0 <= Y2 && Y2 <= maxY) + { + const int tmpDist = cmpBlocks(X1, Y1, X2, Y2, blockSize); + if (tmpDist < acceptLevel) + { + sumx = dx; + sumy = dy; + countMin = 1; + break; + } + + if (tmpDist < dist) + { + dist = tmpDist; + sumx = dx; + sumy = dy; + countMin = 1; + } + else if (tmpDist == dist) + { + sumx += dx; + sumy += dy; + countMin++; + } + } + } + + if (dist > escapeLevel) + { + sumx = offX; + sumy = offY; + countMin = 1; + } + } + + velx(i, j) = static_cast(sumx) / countMin; + vely(i, j) = static_cast(sumy) / countMin; + } + + void calc(PtrStepSzb prev, PtrStepSzb curr, PtrStepSzf velx, PtrStepSzf vely, int2 blockSize, int2 shiftSize, bool usePrevious, + int maxX, int maxY, int acceptLevel, int escapeLevel, const short2* ss, int ssCount, cudaStream_t stream) + { + bindTexture(&tex_prev, prev); + bindTexture(&tex_curr, curr); + + const dim3 block(32, 8); + const dim3 grid(divUp(velx.cols, block.x), divUp(vely.rows, block.y)); + + calcOptFlowBM<<>>(velx, vely, blockSize, shiftSize, usePrevious, + maxX, maxY, acceptLevel, escapeLevel, ss, ssCount); + cudaSafeCall( cudaGetLastError() ); + + if (stream == 0) + cudaSafeCall( cudaDeviceSynchronize() ); + } +} + +///////////////////////////////////////////////////////// +// Fast approximate version + +namespace optflowbm_fast +{ + enum + { + CTA_SIZE = 128, + + TILE_COLS = 128, + TILE_ROWS = 32, + + STRIDE = CTA_SIZE + }; + + template __device__ __forceinline__ int calcDist(T a, T b) + { + return ::abs(a - b); + } + + template struct FastOptFlowBM + { + + int search_radius; + int block_radius; + + int search_window; + int block_window; + + PtrStepSz I0; + PtrStep I1; + + mutable PtrStepi buffer; + + FastOptFlowBM(int search_window_, int block_window_, + PtrStepSz I0_, PtrStepSz I1_, + PtrStepi buffer_) : + search_radius(search_window_ / 2), block_radius(block_window_ / 2), + search_window(search_window_), block_window(block_window_), + I0(I0_), I1(I1_), + buffer(buffer_) + { + } + + __device__ __forceinline__ void initSums_BruteForce(int i, int j, int* dist_sums, PtrStepi& col_sums, PtrStepi& up_col_sums) const + { + for (int index = threadIdx.x; index < search_window * search_window; index += STRIDE) + { + dist_sums[index] = 0; + + for (int tx = 0; tx < block_window; ++tx) + col_sums(tx, index) = 0; + + int y = index / search_window; + int x = index - y * search_window; + + int ay = i; + int ax = j; + + int by = i + y - search_radius; + int bx = j + x - search_radius; + + for (int tx = -block_radius; tx <= block_radius; ++tx) + { + int col_sum = 0; + for (int ty = -block_radius; ty <= block_radius; ++ty) + { + int dist = calcDist(I0(ay + ty, ax + tx), I1(by + ty, bx + tx)); + + dist_sums[index] += dist; + col_sum += dist; + } + + col_sums(tx + block_radius, index) = col_sum; + } + + up_col_sums(j, index) = col_sums(block_window - 1, index); + } + } + + __device__ __forceinline__ void shiftRight_FirstRow(int i, int j, int first, int* dist_sums, PtrStepi& col_sums, PtrStepi& up_col_sums) const + { + for (int index = threadIdx.x; index < search_window * search_window; index += STRIDE) + { + int y = index / search_window; + int x = index - y * search_window; + + int ay = i; + int ax = j + block_radius; + + int by = i + y - search_radius; + int bx = j + x - search_radius + block_radius; + + int col_sum = 0; + + for (int ty = -block_radius; ty <= block_radius; ++ty) + col_sum += calcDist(I0(ay + ty, ax), I1(by + ty, bx)); + + dist_sums[index] += col_sum - col_sums(first, index); + + col_sums(first, index) = col_sum; + up_col_sums(j, index) = col_sum; + } + } + + __device__ __forceinline__ void shiftRight_UpSums(int i, int j, int first, int* dist_sums, PtrStepi& col_sums, PtrStepi& up_col_sums) const + { + int ay = i; + int ax = j + block_radius; + + T a_up = I0(ay - block_radius - 1, ax); + T a_down = I0(ay + block_radius, ax); + + for(int index = threadIdx.x; index < search_window * search_window; index += STRIDE) + { + int y = index / search_window; + int x = index - y * search_window; + + int by = i + y - search_radius; + int bx = j + x - search_radius + block_radius; + + T b_up = I1(by - block_radius - 1, bx); + T b_down = I1(by + block_radius, bx); + + int col_sum = up_col_sums(j, index) + calcDist(a_down, b_down) - calcDist(a_up, b_up); + + dist_sums[index] += col_sum - col_sums(first, index); + col_sums(first, index) = col_sum; + up_col_sums(j, index) = col_sum; + } + } + + __device__ __forceinline__ void convolve_window(int i, int j, const int* dist_sums, float& velx, float& vely) const + { + int bestDist = numeric_limits::max(); + int bestInd = -1; + + for (int index = threadIdx.x; index < search_window * search_window; index += STRIDE) + { + int curDist = dist_sums[index]; + if (curDist < bestDist) + { + bestDist = curDist; + bestInd = index; + } + } + + __shared__ int cta_dist_buffer[CTA_SIZE]; + __shared__ int cta_ind_buffer[CTA_SIZE]; + + reduceKeyVal(cta_dist_buffer, bestDist, cta_ind_buffer, bestInd, threadIdx.x, less()); + + if (threadIdx.x == 0) + { + int y = bestInd / search_window; + int x = bestInd - y * search_window; + + velx = x - search_radius; + vely = y - search_radius; + } + } + + __device__ __forceinline__ void operator()(PtrStepf velx, PtrStepf vely) const + { + int tbx = blockIdx.x * TILE_COLS; + int tby = blockIdx.y * TILE_ROWS; + + int tex = ::min(tbx + TILE_COLS, I0.cols); + int tey = ::min(tby + TILE_ROWS, I0.rows); + + PtrStepi col_sums; + col_sums.data = buffer.ptr(I0.cols + blockIdx.x * block_window) + blockIdx.y * search_window * search_window; + col_sums.step = buffer.step; + + PtrStepi up_col_sums; + up_col_sums.data = buffer.data + blockIdx.y * search_window * search_window; + up_col_sums.step = buffer.step; + + extern __shared__ int dist_sums[]; //search_window * search_window + + int first = 0; + + for (int i = tby; i < tey; ++i) + { + for (int j = tbx; j < tex; ++j) + { + __syncthreads(); + + if (j == tbx) + { + initSums_BruteForce(i, j, dist_sums, col_sums, up_col_sums); + first = 0; + } + else + { + if (i == tby) + shiftRight_FirstRow(i, j, first, dist_sums, col_sums, up_col_sums); + else + shiftRight_UpSums(i, j, first, dist_sums, col_sums, up_col_sums); + + first = (first + 1) % block_window; + } + + __syncthreads(); + + convolve_window(i, j, dist_sums, velx(i, j), vely(i, j)); + } + } + } + + }; + + template __global__ void optflowbm_fast_kernel(const FastOptFlowBM fbm, PtrStepf velx, PtrStepf vely) + { + fbm(velx, vely); + } + + void get_buffer_size(int src_cols, int src_rows, int search_window, int block_window, int& buffer_cols, int& buffer_rows) + { + dim3 grid(divUp(src_cols, TILE_COLS), divUp(src_rows, TILE_ROWS)); + + buffer_cols = search_window * search_window * grid.y; + buffer_rows = src_cols + block_window * grid.x; + } + + template + void calc(PtrStepSzb I0, PtrStepSzb I1, PtrStepSzf velx, PtrStepSzf vely, PtrStepi buffer, int search_window, int block_window, cudaStream_t stream) + { + FastOptFlowBM fbm(search_window, block_window, I0, I1, buffer); + + dim3 block(CTA_SIZE, 1); + dim3 grid(divUp(I0.cols, TILE_COLS), divUp(I0.rows, TILE_ROWS)); + + size_t smem = search_window * search_window * sizeof(int); + + optflowbm_fast_kernel<<>>(fbm, velx, vely); + cudaSafeCall ( cudaGetLastError () ); + + if (stream == 0) + cudaSafeCall( cudaDeviceSynchronize() ); + } + + template void calc(PtrStepSzb I0, PtrStepSzb I1, PtrStepSzf velx, PtrStepSzf vely, PtrStepi buffer, int search_window, int block_window, cudaStream_t stream); +} + +#endif // !defined CUDA_DISABLER diff --git a/modules/gpu/src/optflowbm.cpp b/modules/gpu/src/optflowbm.cpp new file mode 100644 index 0000000..a4321c8 --- /dev/null +++ b/modules/gpu/src/optflowbm.cpp @@ -0,0 +1,243 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009, Willow Garage Inc., 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. +// +//M*/ + +#include "precomp.hpp" + +using namespace std; +using namespace cv; +using namespace cv::gpu; + +#if !defined HAVE_CUDA || defined(CUDA_DISABLER) + +void cv::gpu::calcOpticalFlowBM(const GpuMat&, const GpuMat&, Size, Size, Size, bool, GpuMat&, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); } + +void cv::gpu::FastOpticalFlowBM::operator ()(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, int, int, Stream&) { throw_nogpu(); } + +#else // HAVE_CUDA + +namespace optflowbm +{ + void calc(PtrStepSzb prev, PtrStepSzb curr, PtrStepSzf velx, PtrStepSzf vely, int2 blockSize, int2 shiftSize, bool usePrevious, + int maxX, int maxY, int acceptLevel, int escapeLevel, const short2* ss, int ssCount, cudaStream_t stream); +} + +void cv::gpu::calcOpticalFlowBM(const GpuMat& prev, const GpuMat& curr, Size blockSize, Size shiftSize, Size maxRange, bool usePrevious, GpuMat& velx, GpuMat& vely, GpuMat& buf, Stream& st) +{ + CV_Assert( prev.type() == CV_8UC1 ); + CV_Assert( curr.size() == prev.size() && curr.type() == prev.type() ); + + const Size velSize((prev.cols - blockSize.width + shiftSize.width) / shiftSize.width, + (prev.rows - blockSize.height + shiftSize.height) / shiftSize.height); + + velx.create(velSize, CV_32FC1); + vely.create(velSize, CV_32FC1); + + // scanning scheme coordinates + vector ss((2 * maxRange.width + 1) * (2 * maxRange.height + 1)); + int ssCount = 0; + + // Calculate scanning scheme + const int minCount = std::min(maxRange.width, maxRange.height); + + // use spiral search pattern + // + // 9 10 11 12 + // 8 1 2 13 + // 7 * 3 14 + // 6 5 4 15 + //... 20 19 18 17 + // + + for (int i = 0; i < minCount; ++i) + { + // four cycles along sides + int x = -i - 1, y = x; + + // upper side + for (int j = -i; j <= i + 1; ++j, ++ssCount) + { + ss[ssCount].x = ++x; + ss[ssCount].y = y; + } + + // right side + for (int j = -i; j <= i + 1; ++j, ++ssCount) + { + ss[ssCount].x = x; + ss[ssCount].y = ++y; + } + + // bottom side + for (int j = -i; j <= i + 1; ++j, ++ssCount) + { + ss[ssCount].x = --x; + ss[ssCount].y = y; + } + + // left side + for (int j = -i; j <= i + 1; ++j, ++ssCount) + { + ss[ssCount].x = x; + ss[ssCount].y = --y; + } + } + + // the rest part + if (maxRange.width < maxRange.height) + { + const int xleft = -minCount; + + // cycle by neighbor rings + for (int i = minCount; i < maxRange.height; ++i) + { + // two cycles by x + int y = -(i + 1); + int x = xleft; + + // upper side + for (int j = -maxRange.width; j <= maxRange.width; ++j, ++ssCount, ++x) + { + ss[ssCount].x = x; + ss[ssCount].y = y; + } + + x = xleft; + y = -y; + + // bottom side + for (int j = -maxRange.width; j <= maxRange.width; ++j, ++ssCount, ++x) + { + ss[ssCount].x = x; + ss[ssCount].y = y; + } + } + } + else if (maxRange.width > maxRange.height) + { + const int yupper = -minCount; + + // cycle by neighbor rings + for (int i = minCount; i < maxRange.width; ++i) + { + // two cycles by y + int x = -(i + 1); + int y = yupper; + + // left side + for (int j = -maxRange.height; j <= maxRange.height; ++j, ++ssCount, ++y) + { + ss[ssCount].x = x; + ss[ssCount].y = y; + } + + y = yupper; + x = -x; + + // right side + for (int j = -maxRange.height; j <= maxRange.height; ++j, ++ssCount, ++y) + { + ss[ssCount].x = x; + ss[ssCount].y = y; + } + } + } + + const cudaStream_t stream = StreamAccessor::getStream(st); + + ensureSizeIsEnough(1, ssCount, CV_16SC2, buf); + if (stream == 0) + cudaSafeCall( cudaMemcpy(buf.data, &ss[0], ssCount * sizeof(short2), cudaMemcpyHostToDevice) ); + else + cudaSafeCall( cudaMemcpyAsync(buf.data, &ss[0], ssCount * sizeof(short2), cudaMemcpyHostToDevice, stream) ); + + const int maxX = prev.cols - blockSize.width; + const int maxY = prev.rows - blockSize.height; + + const int SMALL_DIFF = 2; + const int BIG_DIFF = 128; + + const int blSize = blockSize.area(); + const int acceptLevel = blSize * SMALL_DIFF; + const int escapeLevel = blSize * BIG_DIFF; + + optflowbm::calc(prev, curr, velx, vely, + make_int2(blockSize.width, blockSize.height), make_int2(shiftSize.width, shiftSize.height), usePrevious, + maxX, maxY, acceptLevel, escapeLevel, buf.ptr(), ssCount, stream); +} + +namespace optflowbm_fast +{ + void get_buffer_size(int src_cols, int src_rows, int search_window, int block_window, int& buffer_cols, int& buffer_rows); + + template + void calc(PtrStepSzb I0, PtrStepSzb I1, PtrStepSzf velx, PtrStepSzf vely, PtrStepi buffer, int search_window, int block_window, cudaStream_t stream); +} + +void cv::gpu::FastOpticalFlowBM::operator ()(const GpuMat& I0, const GpuMat& I1, GpuMat& flowx, GpuMat& flowy, int search_window, int block_window, Stream& stream) +{ + CV_Assert( I0.type() == CV_8UC1 ); + CV_Assert( I1.size() == I0.size() && I1.type() == I0.type() ); + + int border_size = search_window / 2 + block_window / 2; + Size esize = I0.size() + Size(border_size, border_size) * 2; + + ensureSizeIsEnough(esize, I0.type(), extended_I0); + ensureSizeIsEnough(esize, I0.type(), extended_I1); + + copyMakeBorder(I0, extended_I0, border_size, border_size, border_size, border_size, cv::BORDER_DEFAULT, Scalar(), stream); + copyMakeBorder(I1, extended_I1, border_size, border_size, border_size, border_size, cv::BORDER_DEFAULT, Scalar(), stream); + + GpuMat I0_hdr = extended_I0(Rect(Point2i(border_size, border_size), I0.size())); + GpuMat I1_hdr = extended_I1(Rect(Point2i(border_size, border_size), I0.size())); + + int bcols, brows; + optflowbm_fast::get_buffer_size(I0.cols, I0.rows, search_window, block_window, bcols, brows); + + ensureSizeIsEnough(brows, bcols, CV_32SC1, buffer); + + flowx.create(I0.size(), CV_32FC1); + flowy.create(I0.size(), CV_32FC1); + + optflowbm_fast::calc(I0_hdr, I1_hdr, flowx, flowy, buffer, search_window, block_window, StreamAccessor::getStream(stream)); +} + +#endif // HAVE_CUDA diff --git a/modules/gpu/test/test_optflow.cpp b/modules/gpu/test/test_optflow.cpp index 46b71b5..c93ebbe 100644 --- a/modules/gpu/test/test_optflow.cpp +++ b/modules/gpu/test/test_optflow.cpp @@ -445,4 +445,179 @@ INSTANTIATE_TEST_CASE_P(GPU_Video, OpticalFlowDual_TVL1, testing::Combine( ALL_DEVICES, WHOLE_SUBMAT)); +////////////////////////////////////////////////////// +// OpticalFlowBM + +namespace +{ + void calcOpticalFlowBM(const cv::Mat& prev, const cv::Mat& curr, + cv::Size bSize, cv::Size shiftSize, cv::Size maxRange, int usePrevious, + cv::Mat& velx, cv::Mat& vely) + { + cv::Size sz((curr.cols - bSize.width + shiftSize.width)/shiftSize.width, (curr.rows - bSize.height + shiftSize.height)/shiftSize.height); + + velx.create(sz, CV_32FC1); + vely.create(sz, CV_32FC1); + + CvMat cvprev = prev; + CvMat cvcurr = curr; + + CvMat cvvelx = velx; + CvMat cvvely = vely; + + cvCalcOpticalFlowBM(&cvprev, &cvcurr, bSize, shiftSize, maxRange, usePrevious, &cvvelx, &cvvely); + } +} + +struct OpticalFlowBM : testing::TestWithParam +{ +}; + +GPU_TEST_P(OpticalFlowBM, Accuracy) +{ + cv::gpu::DeviceInfo devInfo = GetParam(); + cv::gpu::setDevice(devInfo.deviceID()); + + cv::Mat frame0 = readImage("opticalflow/rubberwhale1.png", cv::IMREAD_GRAYSCALE); + ASSERT_FALSE(frame0.empty()); + + cv::Mat frame1 = readImage("opticalflow/rubberwhale2.png", cv::IMREAD_GRAYSCALE); + ASSERT_FALSE(frame1.empty()); + + cv::Size block_size(16, 16); + cv::Size shift_size(1, 1); + cv::Size max_range(16, 16); + + cv::gpu::GpuMat d_velx, d_vely, buf; + cv::gpu::calcOpticalFlowBM(loadMat(frame0), loadMat(frame1), + block_size, shift_size, max_range, false, + d_velx, d_vely, buf); + + cv::Mat velx, vely; + calcOpticalFlowBM(frame0, frame1, block_size, shift_size, max_range, false, velx, vely); + + EXPECT_MAT_NEAR(velx, d_velx, 0); + EXPECT_MAT_NEAR(vely, d_vely, 0); +} + +INSTANTIATE_TEST_CASE_P(GPU_Video, OpticalFlowBM, ALL_DEVICES); + +////////////////////////////////////////////////////// +// FastOpticalFlowBM + +namespace +{ + void FastOpticalFlowBM_gold(const cv::Mat_& I0, const cv::Mat_& I1, cv::Mat_& velx, cv::Mat_& vely, int search_window, int block_window) + { + velx.create(I0.size()); + vely.create(I0.size()); + + int search_radius = search_window / 2; + int block_radius = block_window / 2; + + for (int y = 0; y < I0.rows; ++y) + { + for (int x = 0; x < I0.cols; ++x) + { + int bestDist = std::numeric_limits::max(); + int bestDx = 0; + int bestDy = 0; + + for (int dy = -search_radius; dy <= search_radius; ++dy) + { + for (int dx = -search_radius; dx <= search_radius; ++dx) + { + int dist = 0; + + for (int by = -block_radius; by <= block_radius; ++by) + { + for (int bx = -block_radius; bx <= block_radius; ++bx) + { + int I0_val = I0(cv::borderInterpolate(y + by, I0.rows, cv::BORDER_DEFAULT), cv::borderInterpolate(x + bx, I0.cols, cv::BORDER_DEFAULT)); + int I1_val = I1(cv::borderInterpolate(y + dy + by, I0.rows, cv::BORDER_DEFAULT), cv::borderInterpolate(x + dx + bx, I0.cols, cv::BORDER_DEFAULT)); + + dist += std::abs(I0_val - I1_val); + } + } + + if (dist < bestDist) + { + bestDist = dist; + bestDx = dx; + bestDy = dy; + } + } + } + + velx(y, x) = (float) bestDx; + vely(y, x) = (float) bestDy; + } + } + } + + double calc_rmse(const cv::Mat_& flow1, const cv::Mat_& flow2) + { + double sum = 0.0; + + for (int y = 0; y < flow1.rows; ++y) + { + for (int x = 0; x < flow1.cols; ++x) + { + double diff = flow1(y, x) - flow2(y, x); + sum += diff * diff; + } + } + + return std::sqrt(sum / flow1.size().area()); + } +} + +struct FastOpticalFlowBM : testing::TestWithParam +{ +}; + +GPU_TEST_P(FastOpticalFlowBM, Accuracy) +{ + const double MAX_RMSE = 0.6; + + int search_window = 15; + int block_window = 5; + + cv::gpu::DeviceInfo devInfo = GetParam(); + cv::gpu::setDevice(devInfo.deviceID()); + + cv::Mat frame0 = readImage("opticalflow/rubberwhale1.png", cv::IMREAD_GRAYSCALE); + ASSERT_FALSE(frame0.empty()); + + cv::Mat frame1 = readImage("opticalflow/rubberwhale2.png", cv::IMREAD_GRAYSCALE); + ASSERT_FALSE(frame1.empty()); + + cv::Size smallSize(320, 240); + cv::Mat frame0_small; + cv::Mat frame1_small; + + cv::resize(frame0, frame0_small, smallSize); + cv::resize(frame1, frame1_small, smallSize); + + cv::gpu::GpuMat d_flowx; + cv::gpu::GpuMat d_flowy; + cv::gpu::FastOpticalFlowBM fastBM; + + fastBM(loadMat(frame0_small), loadMat(frame1_small), d_flowx, d_flowy, search_window, block_window); + + cv::Mat_ flowx; + cv::Mat_ flowy; + FastOpticalFlowBM_gold(frame0_small, frame1_small, flowx, flowy, search_window, block_window); + + double err; + + err = calc_rmse(flowx, cv::Mat(d_flowx)); + EXPECT_LE(err, MAX_RMSE); + + err = calc_rmse(flowy, cv::Mat(d_flowy)); + EXPECT_LE(err, MAX_RMSE); +} + +INSTANTIATE_TEST_CASE_P(GPU_Video, FastOpticalFlowBM, ALL_DEVICES); + #endif // HAVE_CUDA -- 2.7.4