test_blend.cpp 4.6 KB

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  1. /*M///////////////////////////////////////////////////////////////////////////////////////
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  7. // copy or use the software.
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  10. // License Agreement
  11. // For Open Source Computer Vision Library
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  14. // Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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  41. //M*/
  42. #include "test_precomp.hpp"
  43. #ifdef HAVE_CUDA
  44. namespace opencv_test { namespace {
  45. ////////////////////////////////////////////////////////////////////////////
  46. // Blend
  47. namespace
  48. {
  49. template <typename T>
  50. void blendLinearGold(const cv::Mat& img1, const cv::Mat& img2, const cv::Mat& weights1, const cv::Mat& weights2, cv::Mat& result_gold)
  51. {
  52. result_gold.create(img1.size(), img1.type());
  53. int cn = img1.channels();
  54. for (int y = 0; y < img1.rows; ++y)
  55. {
  56. const float* weights1_row = weights1.ptr<float>(y);
  57. const float* weights2_row = weights2.ptr<float>(y);
  58. const T* img1_row = img1.ptr<T>(y);
  59. const T* img2_row = img2.ptr<T>(y);
  60. T* result_gold_row = result_gold.ptr<T>(y);
  61. for (int x = 0; x < img1.cols * cn; ++x)
  62. {
  63. float w1 = weights1_row[x / cn];
  64. float w2 = weights2_row[x / cn];
  65. result_gold_row[x] = static_cast<T>((img1_row[x] * w1 + img2_row[x] * w2) / (w1 + w2 + 1e-5f));
  66. }
  67. }
  68. }
  69. }
  70. PARAM_TEST_CASE(Blend, cv::cuda::DeviceInfo, cv::Size, MatType, UseRoi)
  71. {
  72. cv::cuda::DeviceInfo devInfo;
  73. cv::Size size;
  74. int type;
  75. bool useRoi;
  76. virtual void SetUp()
  77. {
  78. devInfo = GET_PARAM(0);
  79. size = GET_PARAM(1);
  80. type = GET_PARAM(2);
  81. useRoi = GET_PARAM(3);
  82. cv::cuda::setDevice(devInfo.deviceID());
  83. }
  84. };
  85. CUDA_TEST_P(Blend, Accuracy)
  86. {
  87. int depth = CV_MAT_DEPTH(type);
  88. cv::Mat img1 = randomMat(size, type, 0.0, depth == CV_8U ? 255.0 : 1.0);
  89. cv::Mat img2 = randomMat(size, type, 0.0, depth == CV_8U ? 255.0 : 1.0);
  90. cv::Mat weights1 = randomMat(size, CV_32F, 0, 1);
  91. cv::Mat weights2 = randomMat(size, CV_32F, 0, 1);
  92. cv::cuda::GpuMat result;
  93. cv::cuda::blendLinear(loadMat(img1, useRoi), loadMat(img2, useRoi), loadMat(weights1, useRoi), loadMat(weights2, useRoi), result);
  94. cv::Mat result_gold;
  95. if (depth == CV_8U)
  96. blendLinearGold<uchar>(img1, img2, weights1, weights2, result_gold);
  97. else
  98. blendLinearGold<float>(img1, img2, weights1, weights2, result_gold);
  99. EXPECT_MAT_NEAR(result_gold, result, CV_MAT_DEPTH(type) == CV_8U ? 1.0 : 1e-5);
  100. }
  101. INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, Blend, testing::Combine(
  102. ALL_DEVICES,
  103. DIFFERENT_SIZES,
  104. testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
  105. WHOLE_SUBMAT));
  106. }} // namespace
  107. #endif // HAVE_CUDA