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  #include "test_precomp.hpp"
  
  #ifdef HAVE_CUDA
  
  namespace opencv_test { namespace {
  
  namespace
  {
      cv::Mat createTransformMatrix(cv::Size srcSize, double angle)
      {
          cv::Mat M(2, 3, CV_64FC1);
  
          M.at<double>(0, 0) = std::cos(angle); M.at<double>(0, 1) = -std::sin(angle); M.at<double>(0, 2) = srcSize.width / 2;
          M.at<double>(1, 0) = std::sin(angle); M.at<double>(1, 1) =  std::cos(angle); M.at<double>(1, 2) = 0.0;
  
          return M;
      }
  }
  
  ///////////////////////////////////////////////////////////////////
  // Test buildWarpAffineMaps
  
  PARAM_TEST_CASE(BuildWarpAffineMaps, cv::cuda::DeviceInfo, cv::Size, Inverse)
  {
      cv::cuda::DeviceInfo devInfo;
      cv::Size size;
      bool inverse;
  
      virtual void SetUp()
      {
          devInfo = GET_PARAM(0);
          size = GET_PARAM(1);
          inverse = GET_PARAM(2);
  
          cv::cuda::setDevice(devInfo.deviceID());
      }
  };
  
  CUDA_TEST_P(BuildWarpAffineMaps, Accuracy)
  {
      cv::Mat M = createTransformMatrix(size, CV_PI / 4);
      cv::Mat src = randomMat(randomSize(200, 400), CV_8UC1);
  
      cv::cuda::GpuMat xmap, ymap;
      cv::cuda::buildWarpAffineMaps(M, inverse, size, xmap, ymap);
  
      int interpolation = cv::INTER_NEAREST;
      int borderMode = cv::BORDER_CONSTANT;
      int flags = interpolation;
      if (inverse)
          flags |= cv::WARP_INVERSE_MAP;
  
      cv::Mat dst;
      cv::remap(src, dst, cv::Mat(xmap), cv::Mat(ymap), interpolation, borderMode);
  
      cv::Mat dst_gold;
      cv::warpAffine(src, dst_gold, M, size, flags, borderMode);
  
      EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
  }
  
  INSTANTIATE_TEST_CASE_P(CUDA_Warping, BuildWarpAffineMaps, testing::Combine(
      ALL_DEVICES,
      DIFFERENT_SIZES,
      DIRECT_INVERSE));
  
  ///////////////////////////////////////////////////////////////////
  // Gold implementation
  
  namespace
  {
      template <typename T, template <typename> class Interpolator> void warpAffineImpl(const cv::Mat& src, const cv::Mat& M, cv::Size dsize, cv::Mat& dst, int borderType, cv::Scalar borderVal)
      {
          const int cn = src.channels();
  
          dst.create(dsize, src.type());
  
          for (int y = 0; y < dsize.height; ++y)
          {
              for (int x = 0; x < dsize.width; ++x)
              {
                  float xcoo = static_cast<float>(M.at<double>(0, 0) * x + M.at<double>(0, 1) * y + M.at<double>(0, 2));
                  float ycoo = static_cast<float>(M.at<double>(1, 0) * x + M.at<double>(1, 1) * y + M.at<double>(1, 2));
  
                  for (int c = 0; c < cn; ++c)
                      dst.at<T>(y, x * cn + c) = Interpolator<T>::getValue(src, ycoo, xcoo, c, borderType, borderVal);
              }
          }
      }
  
      void warpAffineGold(const cv::Mat& src, const cv::Mat& M, bool inverse, cv::Size dsize, cv::Mat& dst, int interpolation, int borderType, cv::Scalar borderVal)
      {
          typedef void (*func_t)(const cv::Mat& src, const cv::Mat& M, cv::Size dsize, cv::Mat& dst, int borderType, cv::Scalar borderVal);
  
          static const func_t nearest_funcs[] =
          {
              warpAffineImpl<unsigned char, NearestInterpolator>,
              warpAffineImpl<signed char, NearestInterpolator>,
              warpAffineImpl<unsigned short, NearestInterpolator>,
              warpAffineImpl<short, NearestInterpolator>,
              warpAffineImpl<int, NearestInterpolator>,
              warpAffineImpl<float, NearestInterpolator>
          };
  
          static const func_t linear_funcs[] =
          {
              warpAffineImpl<unsigned char, LinearInterpolator>,
              warpAffineImpl<signed char, LinearInterpolator>,
              warpAffineImpl<unsigned short, LinearInterpolator>,
              warpAffineImpl<short, LinearInterpolator>,
              warpAffineImpl<int, LinearInterpolator>,
              warpAffineImpl<float, LinearInterpolator>
          };
  
          static const func_t cubic_funcs[] =
          {
              warpAffineImpl<unsigned char, CubicInterpolator>,
              warpAffineImpl<signed char, CubicInterpolator>,
              warpAffineImpl<unsigned short, CubicInterpolator>,
              warpAffineImpl<short, CubicInterpolator>,
              warpAffineImpl<int, CubicInterpolator>,
              warpAffineImpl<float, CubicInterpolator>
          };
  
          static const func_t* funcs[] = {nearest_funcs, linear_funcs, cubic_funcs};
  
          if (inverse)
              funcs[interpolation][src.depth()](src, M, dsize, dst, borderType, borderVal);
          else
          {
              cv::Mat iM;
              cv::invertAffineTransform(M, iM);
              funcs[interpolation][src.depth()](src, iM, dsize, dst, borderType, borderVal);
          }
      }
  }
  
  ///////////////////////////////////////////////////////////////////
  // Test
  
  PARAM_TEST_CASE(WarpAffine, cv::cuda::DeviceInfo, cv::Size, MatType, Inverse, Interpolation, BorderType, UseRoi)
  {
      cv::cuda::DeviceInfo devInfo;
      cv::Size size;
      int type;
      bool inverse;
      int interpolation;
      int borderType;
      bool useRoi;
  
      virtual void SetUp()
      {
          devInfo = GET_PARAM(0);
          size = GET_PARAM(1);
          type = GET_PARAM(2);
          inverse = GET_PARAM(3);
          interpolation = GET_PARAM(4);
          borderType = GET_PARAM(5);
          useRoi = GET_PARAM(6);
  
          cv::cuda::setDevice(devInfo.deviceID());
      }
  };
  
  CUDA_TEST_P(WarpAffine, Accuracy)
  {
      cv::Mat src = randomMat(size, type);
      cv::Mat M = createTransformMatrix(size, CV_PI / 3);
      int flags = interpolation;
      if (inverse)
          flags |= cv::WARP_INVERSE_MAP;
      cv::Scalar val = randomScalar(0.0, 255.0);
  
      cv::cuda::GpuMat dst = createMat(size, type, useRoi);
      cv::cuda::warpAffine(loadMat(src, useRoi), dst, M, size, flags, borderType, val);
  
      cv::Mat dst_gold;
      warpAffineGold(src, M, inverse, size, dst_gold, interpolation, borderType, val);
  
      EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-1 : 1.0);
  }
  
  INSTANTIATE_TEST_CASE_P(CUDA_Warping, WarpAffine, testing::Combine(
      ALL_DEVICES,
      DIFFERENT_SIZES,
      testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
      DIRECT_INVERSE,
      testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
      testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_REFLECT), BorderType(cv::BORDER_WRAP)),
      WHOLE_SUBMAT));
  
  ///////////////////////////////////////////////////////////////////
  // Test NPP
  
  PARAM_TEST_CASE(WarpAffineNPP, cv::cuda::DeviceInfo, MatType, Inverse, Interpolation)
  {
      cv::cuda::DeviceInfo devInfo;
      int type;
      bool inverse;
      int interpolation;
  
      virtual void SetUp()
      {
          devInfo = GET_PARAM(0);
          type = GET_PARAM(1);
          inverse = GET_PARAM(2);
          interpolation = GET_PARAM(3);
  
          cv::cuda::setDevice(devInfo.deviceID());
      }
  };
  
  CUDA_TEST_P(WarpAffineNPP, Accuracy)
  {
      cv::Mat src = readImageType("stereobp/aloe-L.png", type);
      ASSERT_FALSE(src.empty());
  
      cv::Mat M = createTransformMatrix(src.size(), CV_PI / 4);
      int flags = interpolation;
      if (inverse)
          flags |= cv::WARP_INVERSE_MAP;
  
      cv::cuda::GpuMat dst;
      cv::cuda::warpAffine(loadMat(src), dst, M, src.size(), flags);
  
      cv::Mat dst_gold;
      warpAffineGold(src, M, inverse, src.size(), dst_gold, interpolation, cv::BORDER_CONSTANT, cv::Scalar::all(0));
  
      EXPECT_MAT_SIMILAR(dst_gold, dst, 2e-2);
  }
  
  INSTANTIATE_TEST_CASE_P(CUDA_Warping, WarpAffineNPP, testing::Combine(
      ALL_DEVICES,
      testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
      DIRECT_INVERSE,
      testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC))));
  
  
  }} // namespace
  #endif // HAVE_CUDA
  