• Li Peng's avatar
    OCL implementation of DIS optical flow · 7ed6f778
    Li Peng authored
    This patch adds ocl kernels to accelerate Dense Inverse Search
    based optical flow algorithm, it acclerates 3 parts in the algorithm,
    including 1) Structure tensor elements compute, 2) Patch inverse search,
    3) Densification compute.
    
    Perf and accuracy test are also added. The perf test shows it is 30%
    faster than the current implementation.
    Signed-off-by: 's avatarLi Peng <peng.li@intel.com>
    7ed6f778
test_dis.cpp 3.46 KB
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#include "../test_precomp.hpp"
#include "opencv2/ts/ocl_test.hpp"

#ifdef HAVE_OPENCL

using namespace cv;
using namespace optflow;

namespace cvtest {
namespace ocl {

PARAM_TEST_CASE(OCL_DenseOpticalFlow_DIS, int)
{
    int preset;

    virtual void SetUp()
    {
        preset = GET_PARAM(0);
    }
};

OCL_TEST_P(OCL_DenseOpticalFlow_DIS, Mat)
{
    Mat frame1, frame2, GT;

    frame1 = imread(TS::ptr()->get_data_path() + "optflow/RubberWhale1.png");
    frame2 = imread(TS::ptr()->get_data_path() + "optflow/RubberWhale2.png");

    CV_Assert(!frame1.empty() && !frame2.empty());

    cvtColor(frame1, frame1, COLOR_BGR2GRAY);
    cvtColor(frame2, frame2, COLOR_BGR2GRAY);

    Ptr<DenseOpticalFlow> algo;

    // iterate over presets:
    for (int i = 0; i < test_loop_times; i++)
    {
        Mat flow;
        UMat ocl_flow;

        algo = createOptFlow_DIS(preset);
        OCL_OFF(algo->calc(frame1, frame2, flow));
        OCL_ON(algo->calc(frame1, frame2, ocl_flow));
        ASSERT_EQ(flow.rows, ocl_flow.rows);
        ASSERT_EQ(flow.cols, ocl_flow.cols);

        EXPECT_MAT_SIMILAR(flow, ocl_flow, 6e-3);
    }
}

OCL_INSTANTIATE_TEST_CASE_P(Contrib, OCL_DenseOpticalFlow_DIS,
                            Values(DISOpticalFlow::PRESET_ULTRAFAST,
                                   DISOpticalFlow::PRESET_FAST,
                                   DISOpticalFlow::PRESET_MEDIUM));

} } // namespace cvtest::ocl

#endif // HAVE_OPENCL