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simplify TVL1 accuracy test to reduce run time

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This commit is contained in:
Vladislav Vinogradov 2014-12-31 11:27:51 +03:00
parent 71c391cd8d
commit c4b2058d23
1 changed files with 16 additions and 19 deletions
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35
modules/cudaoptflow/test/test_optflow.cpp
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@ -325,15 +325,20 @@ INSTANTIATE_TEST_CASE_P(CUDA_OptFlow, FarnebackOpticalFlow, testing::Combine(
////////////////////////////////////////////////////// //////////////////////////////////////////////////////
// OpticalFlowDual_TVL1 // OpticalFlowDual_TVL1
PARAM_TEST_CASE(OpticalFlowDual_TVL1, cv::cuda::DeviceInfo, UseRoi) namespace
{
IMPLEMENT_PARAM_CLASS(Gamma, double)
}
PARAM_TEST_CASE(OpticalFlowDual_TVL1, cv::cuda::DeviceInfo, Gamma)
{ {
cv::cuda::DeviceInfo devInfo; cv::cuda::DeviceInfo devInfo;
bool useRoi; double gamma;
virtual void SetUp() virtual void SetUp()
{ {
devInfo = GET_PARAM(0); devInfo = GET_PARAM(0);
useRoi = GET_PARAM(1); gamma = GET_PARAM(1);
cv::cuda::setDevice(devInfo.deviceID()); cv::cuda::setDevice(devInfo.deviceID());
} }
@ -348,30 +353,22 @@ CUDA_TEST_P(OpticalFlowDual_TVL1, Accuracy)
ASSERT_FALSE(frame1.empty()); ASSERT_FALSE(frame1.empty());
cv::cuda::OpticalFlowDual_TVL1_CUDA d_alg; cv::cuda::OpticalFlowDual_TVL1_CUDA d_alg;
cv::cuda::GpuMat d_flowx = createMat(frame0.size(), CV_32FC1, useRoi); d_alg.iterations = 10;
cv::cuda::GpuMat d_flowy = createMat(frame0.size(), CV_32FC1, useRoi); d_alg.gamma = gamma;
d_alg(loadMat(frame0, useRoi), loadMat(frame1, useRoi), d_flowx, d_flowy);
cv::cuda::GpuMat d_flowx, d_flowy;
d_alg(loadMat(frame0), loadMat(frame1), d_flowx, d_flowy);
cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1(); cv::Ptr<cv::DenseOpticalFlow> alg = cv::createOptFlow_DualTVL1();
alg->set("medianFiltering", 1); alg->set("medianFiltering", 1);
alg->set("innerIterations", 1); alg->set("innerIterations", 1);
alg->set("outerIterations", d_alg.iterations); alg->set("outerIterations", d_alg.iterations);
alg->set("gamma", gamma);
cv::Mat flow; cv::Mat flow;
alg->calc(frame0, frame1, flow); alg->calc(frame0, frame1, flow);
cv::Mat gold[2]; cv::Mat gold[2];
cv::split(flow, gold); cv::split(flow, gold);
cv::Mat mx(d_flowx);
cv::Mat my(d_flowx);
EXPECT_MAT_SIMILAR(gold[0], d_flowx, 4e-3);
EXPECT_MAT_SIMILAR(gold[1], d_flowy, 4e-3);
d_alg.gamma = 1;
alg->set("gamma", 1);
d_alg(loadMat(frame0, useRoi), loadMat(frame1, useRoi), d_flowx, d_flowy);
alg->calc(frame0, frame1, flow);
cv::split(flow, gold);
mx = cv::Mat(d_flowx);
my = cv::Mat(d_flowx);
EXPECT_MAT_SIMILAR(gold[0], d_flowx, 4e-3); EXPECT_MAT_SIMILAR(gold[0], d_flowx, 4e-3);
EXPECT_MAT_SIMILAR(gold[1], d_flowy, 4e-3); EXPECT_MAT_SIMILAR(gold[1], d_flowy, 4e-3);
@ -379,7 +376,7 @@ CUDA_TEST_P(OpticalFlowDual_TVL1, Accuracy)
INSTANTIATE_TEST_CASE_P(CUDA_OptFlow, OpticalFlowDual_TVL1, testing::Combine( INSTANTIATE_TEST_CASE_P(CUDA_OptFlow, OpticalFlowDual_TVL1, testing::Combine(
ALL_DEVICES, ALL_DEVICES,
WHOLE_SUBMAT)); testing::Values(Gamma(0.0), Gamma(1.0))));
////////////////////////////////////////////////////// //////////////////////////////////////////////////////
// FastOpticalFlowBM // FastOpticalFlowBM