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     42 
     43 #include "test_precomp.hpp"
     44 
     45 #ifdef HAVE_CUDA
     46 
     47 using namespace cvtest;
     48 
     49 ////////////////////////////////////////////////////////////////////////////
     50 // Blend
     51 
     52 namespace
     53 {
     54     template <typename T>
     55     void blendLinearGold(const cv::Mat& img1, const cv::Mat& img2, const cv::Mat& weights1, const cv::Mat& weights2, cv::Mat& result_gold)
     56     {
     57         result_gold.create(img1.size(), img1.type());
     58 
     59         int cn = img1.channels();
     60 
     61         for (int y = 0; y < img1.rows; ++y)
     62         {
     63             const float* weights1_row = weights1.ptr<float>(y);
     64             const float* weights2_row = weights2.ptr<float>(y);
     65             const T* img1_row = img1.ptr<T>(y);
     66             const T* img2_row = img2.ptr<T>(y);
     67             T* result_gold_row = result_gold.ptr<T>(y);
     68 
     69             for (int x = 0; x < img1.cols * cn; ++x)
     70             {
     71                 float w1 = weights1_row[x / cn];
     72                 float w2 = weights2_row[x / cn];
     73                 result_gold_row[x] = static_cast<T>((img1_row[x] * w1 + img2_row[x] * w2) / (w1 + w2 + 1e-5f));
     74             }
     75         }
     76     }
     77 }
     78 
     79 PARAM_TEST_CASE(Blend, cv::cuda::DeviceInfo, cv::Size, MatType, UseRoi)
     80 {
     81     cv::cuda::DeviceInfo devInfo;
     82     cv::Size size;
     83     int type;
     84     bool useRoi;
     85 
     86     virtual void SetUp()
     87     {
     88         devInfo = GET_PARAM(0);
     89         size = GET_PARAM(1);
     90         type = GET_PARAM(2);
     91         useRoi = GET_PARAM(3);
     92 
     93         cv::cuda::setDevice(devInfo.deviceID());
     94     }
     95 };
     96 
     97 CUDA_TEST_P(Blend, Accuracy)
     98 {
     99     int depth = CV_MAT_DEPTH(type);
    100 
    101     cv::Mat img1 = randomMat(size, type, 0.0, depth == CV_8U ? 255.0 : 1.0);
    102     cv::Mat img2 = randomMat(size, type, 0.0, depth == CV_8U ? 255.0 : 1.0);
    103     cv::Mat weights1 = randomMat(size, CV_32F, 0, 1);
    104     cv::Mat weights2 = randomMat(size, CV_32F, 0, 1);
    105 
    106     cv::cuda::GpuMat result;
    107     cv::cuda::blendLinear(loadMat(img1, useRoi), loadMat(img2, useRoi), loadMat(weights1, useRoi), loadMat(weights2, useRoi), result);
    108 
    109     cv::Mat result_gold;
    110     if (depth == CV_8U)
    111         blendLinearGold<uchar>(img1, img2, weights1, weights2, result_gold);
    112     else
    113         blendLinearGold<float>(img1, img2, weights1, weights2, result_gold);
    114 
    115     EXPECT_MAT_NEAR(result_gold, result, CV_MAT_DEPTH(type) == CV_8U ? 1.0 : 1e-5);
    116 }
    117 
    118 INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, Blend, testing::Combine(
    119     ALL_DEVICES,
    120     DIFFERENT_SIZES,
    121     testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
    122     WHOLE_SUBMAT));
    123 
    124 #endif // HAVE_CUDA
    125