提交 da017fbe 编写于 作者: V Vladislav Vinogradov

fast optical flow bm implementation

上级 caf91ac1
......@@ -94,13 +94,13 @@ PERF_TEST_P(Image, HoughLinesP,
{
cv::gpu::GpuMat d_image(image);
cv::gpu::GpuMat d_lines;
cv::gpu::CannyBuf d_buf;
cv::gpu::HoughLinesBuf d_buf;
cv::gpu::HoughLinesP(d_image, d_lines, d_buf, minLineLenght, maxLineGap);
cv::gpu::HoughLinesP(d_image, d_lines, d_buf, rho, theta, minLineLenght, maxLineGap);
TEST_CYCLE()
{
cv::gpu::HoughLinesP(d_image, d_lines, d_buf, minLineLenght, maxLineGap);
cv::gpu::HoughLinesP(d_image, d_lines, d_buf, rho, theta, minLineLenght, maxLineGap);
}
}
else
......@@ -434,3 +434,56 @@ PERF_TEST_P(ImagePair_BlockSize_ShiftSize_MaxRange, OpticalFlowBM,
SANITY_CHECK(0);
}
PERF_TEST_P(ImagePair_BlockSize_ShiftSize_MaxRange, FastOpticalFlowBM,
testing::Combine(
testing::Values(string_pair("im1_1280x800.jpg", "im2_1280x800.jpg")),
testing::Values(cv::Size(16, 16)),
testing::Values(cv::Size(1, 1)),
testing::Values(cv::Size(16, 16))
))
{
declare.time(1000);
const string_pair fileNames = std::tr1::get<0>(GetParam());
const cv::Size block_size = std::tr1::get<1>(GetParam());
const cv::Size shift_size = std::tr1::get<2>(GetParam());
const cv::Size max_range = std::tr1::get<3>(GetParam());
cv::Mat src1 = cv::imread(fileNames.first, cv::IMREAD_GRAYSCALE);
if (src1.empty())
FAIL() << "Unable to load source image [" << fileNames.first << "]";
cv::Mat src2 = cv::imread(fileNames.second, cv::IMREAD_GRAYSCALE);
if (src2.empty())
FAIL() << "Unable to load source image [" << fileNames.second << "]";
if (PERF_RUN_GPU())
{
cv::gpu::GpuMat d_src1(src1);
cv::gpu::GpuMat d_src2(src2);
cv::gpu::GpuMat d_velx, d_vely;
cv::gpu::FastOpticalFlowBM fastBM;
fastBM(d_src1, d_src2, d_velx, d_vely, max_range.width, block_size.width);
TEST_CYCLE_N(10)
{
fastBM(d_src1, d_src2, d_velx, d_vely, max_range.width, block_size.width);
}
}
else
{
cv::Mat velx, vely;
calcOpticalFlowBM(src1, src2, block_size, shift_size, max_range, false, velx, vely);
TEST_CYCLE_N(10)
{
calcOpticalFlowBM(src1, src2, block_size, shift_size, max_range, false, velx, vely);
}
}
SANITY_CHECK(0);
}
......@@ -2129,6 +2129,17 @@ CV_EXPORTS void calcOpticalFlowBM(const GpuMat& prev, const GpuMat& curr,
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)
......
......@@ -512,6 +512,55 @@ PERF_TEST_P(ImagePair, Video_OpticalFlowBM,
}
}
PERF_TEST_P(ImagePair, Video_FastOpticalFlowBM,
Values<pair_string>(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
......
......@@ -44,6 +44,8 @@
#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;
......@@ -164,4 +166,249 @@ namespace optflowbm
}
}
/////////////////////////////////////////////////////////
// Fast approximate version
namespace optflowbm_fast
{
enum
{
CTA_SIZE = 128,
TILE_COLS = 128,
TILE_ROWS = 32,
STRIDE = CTA_SIZE
};
template <typename T> __device__ __forceinline__ int calcDist(T a, T b)
{
return ::abs(a - b);
}
template <class T> struct FastOptFlowBM
{
int search_radius;
int block_radius;
int search_window;
int block_window;
PtrStepSz<T> I0;
PtrStep<T> I1;
mutable PtrStepi buffer;
FastOptFlowBM(int search_window_, int block_window_,
PtrStepSz<T> I0_, PtrStepSz<T> 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__ 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__ 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__ 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__ void convolve_window(int i, int j, const int* dist_sums, float& velx, float& vely) const
{
int bestDist = numeric_limits<int>::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_SIZE>(cta_dist_buffer, bestDist, cta_ind_buffer, bestInd, threadIdx.x, less<int>());
if (threadIdx.x == 0)
{
int y = bestInd / search_window;
int x = bestInd - y * search_window;
velx = x - search_radius;
vely = y - search_radius;
}
}
__device__ 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<typename T> __global__ void optflowbm_fast_kernel(const FastOptFlowBM<T> 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 <typename T>
void calc(PtrStepSzb I0, PtrStepSzb I1, PtrStepSzf velx, PtrStepSzf vely, PtrStepi buffer, int search_window, int block_window, cudaStream_t stream)
{
FastOptFlowBM<T> 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<<<grid, block, smem, stream>>>(fbm, velx, vely);
cudaSafeCall ( cudaGetLastError () );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
template void calc<uchar>(PtrStepSzb I0, PtrStepSzb I1, PtrStepSzf velx, PtrStepSzf vely, PtrStepi buffer, int search_window, int block_window, cudaStream_t stream);
}
#endif // !defined CUDA_DISABLER
......@@ -50,6 +50,8 @@ using namespace cv::gpu;
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
......@@ -202,4 +204,40 @@ void cv::gpu::calcOpticalFlowBM(const GpuMat& prev, const GpuMat& curr, Size blo
maxX, maxY, acceptLevel, escapeLevel, buf.ptr<short2>(), 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 <typename T>
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<uchar>(I0_hdr, I1_hdr, flowx, flowy, buffer, search_window, block_window, StreamAccessor::getStream(stream));
}
#endif // HAVE_CUDA
......@@ -513,6 +513,121 @@ TEST_P(OpticalFlowBM, Accuracy)
INSTANTIATE_TEST_CASE_P(GPU_Video, OpticalFlowBM, ALL_DEVICES);
//////////////////////////////////////////////////////
// FastOpticalFlowBM
static void FastOpticalFlowBM_gold(const cv::Mat_<uchar>& I0, const cv::Mat_<uchar>& I1, cv::Mat_<float>& velx, cv::Mat_<float>& 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<int>::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) = bestDx;
vely(y, x) = bestDy;
}
}
}
static double calc_rmse(const cv::Mat_<float>& flow1, const cv::Mat_<float>& 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<cv::gpu::DeviceInfo>
{
};
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_<float> flowx;
cv::Mat_<float> 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);
//////////////////////////////////////////////////////
// FGDStatModel
......
......@@ -121,6 +121,17 @@ static void drawOpticalFlow(const Mat_<float>& flowx, const Mat_<float>& flowy,
}
}
static void showFlow(const char* name, const GpuMat& d_flowx, const GpuMat& d_flowy)
{
Mat flowx(d_flowx);
Mat flowy(d_flowy);
Mat out;
drawOpticalFlow(flowx, flowy, out, 10);
imshow(name, out);
}
int main(int argc, const char* argv[])
{
if (argc < 3)
......@@ -152,20 +163,90 @@ int main(int argc, const char* argv[])
GpuMat d_frame0(frame0);
GpuMat d_frame1(frame1);
GpuMat d_flowx, d_flowy;
GpuMat d_flowx(frame0.size(), CV_32FC1);
GpuMat d_flowy(frame0.size(), CV_32FC1);
BroxOpticalFlow brox(0.197, 50.0, 0.8, 10, 77, 10);
PyrLKOpticalFlow lk; lk.winSize = Size(7, 7);
FarnebackOpticalFlow farn;
OpticalFlowDual_TVL1_GPU tvl1;
FastOpticalFlowBM fastBM;
const double start = getTickCount();
tvl1(d_frame0, d_frame1, d_flowx, d_flowy);
const double timeSec = (getTickCount() - start) / getTickFrequency();
cout << "Time : " << timeSec << " sec" << endl;
{
GpuMat d_frame0f;
GpuMat d_frame1f;
Mat flowx(d_flowx);
Mat flowy(d_flowy);
Mat out;
drawOpticalFlow(flowx, flowy, out);
d_frame0.convertTo(d_frame0f, CV_32F, 1.0 / 255.0);
d_frame1.convertTo(d_frame1f, CV_32F, 1.0 / 255.0);
const double start = getTickCount();
brox(d_frame0f, d_frame1f, d_flowx, d_flowy);
const double timeSec = (getTickCount() - start) / getTickFrequency();
cout << "Brox : " << timeSec << " sec" << endl;
showFlow("Brox", d_flowx, d_flowy);
}
{
const double start = getTickCount();
lk.dense(d_frame0, d_frame1, d_flowx, d_flowy);
const double timeSec = (getTickCount() - start) / getTickFrequency();
cout << "LK : " << timeSec << " sec" << endl;
showFlow("LK", d_flowx, d_flowy);
}
{
const double start = getTickCount();
farn(d_frame0, d_frame1, d_flowx, d_flowy);
const double timeSec = (getTickCount() - start) / getTickFrequency();
cout << "Farn : " << timeSec << " sec" << endl;
showFlow("Farn", d_flowx, d_flowy);
}
{
const double start = getTickCount();
tvl1(d_frame0, d_frame1, d_flowx, d_flowy);
const double timeSec = (getTickCount() - start) / getTickFrequency();
cout << "TVL1 : " << timeSec << " sec" << endl;
showFlow("TVL1", d_flowx, d_flowy);
}
{
const double start = getTickCount();
GpuMat buf;
calcOpticalFlowBM(d_frame0, d_frame1, Size(7, 7), Size(1, 1), Size(21, 21), false, d_flowx, d_flowy, buf);
const double timeSec = (getTickCount() - start) / getTickFrequency();
cout << "BM : " << timeSec << " sec" << endl;
showFlow("BM", d_flowx, d_flowy);
}
{
const double start = getTickCount();
fastBM(d_frame0, d_frame1, d_flowx, d_flowy);
const double timeSec = (getTickCount() - start) / getTickFrequency();
cout << "Fast BM : " << timeSec << " sec" << endl;
showFlow("Fast BM", d_flowx, d_flowy);
}
imshow("Flow", out);
imshow("Frame 0", frame0);
imshow("Frame 1", frame1);
waitKey();
return 0;
......
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