generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

move obsolete algorithms from cudaoptflow to cudalegacy

Browse Source
This commit is contained in:
Vladislav Vinogradov
2014-12-31 15:35:23 +03:00
parent c4b2058d23
commit 19c6bbe7d9
11 changed files with 49 additions and 311 deletions
Download Patch File Download Diff File Expand all files Collapse all files

118
modules/cudaoptflow/test/test_optflow.cpp
View File

@@ -378,122 +378,4 @@ INSTANTIATE_TEST_CASE_P(CUDA_OptFlow, OpticalFlowDual_TVL1, testing::Combine(
ALL_DEVICES,
testing::Values(Gamma(0.0), Gamma(1.0))));
//////////////////////////////////////////////////////
// FastOpticalFlowBM
namespace
{
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) = (float) bestDx;
vely(y, x) = (float) bestDy;
}
}
}
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::cuda::DeviceInfo>
{
};
CUDA_TEST_P(FastOpticalFlowBM, Accuracy)
{
const double MAX_RMSE = 0.6;
int search_window = 15;
int block_window = 5;
cv::cuda::DeviceInfo devInfo = GetParam();
cv::cuda::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::cuda::GpuMat d_flowx;
cv::cuda::GpuMat d_flowy;
cv::cuda::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(CUDA_OptFlow, FastOpticalFlowBM, ALL_DEVICES);
#endif // HAVE_CUDA