vendor: OpenCV 5.0.0 snapshot at 755e50675d97db9b7d449d8bd6b09888646f6c6e

2026-08-22 00:11:13 +08:00
commit 12022378a3
3872 changed files with 2513409 additions and 0 deletions
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+#include "test_precomp.hpp"
+
+#ifdef HAVE_CUDA
+
+namespace opencv_test { namespace {
+
+///////////////////////////////////////////////////////////////////
+// Gold implementation
+
+namespace
+{
+    template <typename T>
+    void resizeLanczosImpl(const cv::Mat& src, cv::Mat& dst, double fx, double fy)
+    {
+        const int cn = src.channels();
+
+        cv::Size dsize(cv::saturate_cast<int>(src.cols * fx), cv::saturate_cast<int>(src.rows * fy));
+
+        dst.create(dsize, src.type());
+
+        float ifx = static_cast<float>(1.0 / fx);
+        float ify = static_cast<float>(1.0 / fy);
+
+        // OpenCV CPU resize uses center-aligned coordinate mapping: (x + 0.5) * fx - 0.5
+        // Since fx and fy here are scale factors, and ifx = 1.0 / fx, ify = 1.0 / fy,
+        // the center-aligned mapping becomes: (x + 0.5) / fx - 0.5 = (x + 0.5) * ifx - 0.5
+        for (int y = 0; y < dsize.height; ++y)
+        {
+            for (int x = 0; x < dsize.width; ++x)
+            {
+                for (int c = 0; c < cn; ++c)
+                {
+                    float src_x = (static_cast<float>(x) + 0.5f) * ifx - 0.5f;
+                    float src_y = (static_cast<float>(y) + 0.5f) * ify - 0.5f;
+                    dst.at<T>(y, x * cn + c) = LanczosInterpolator<T>::getValue(src, src_y, src_x, c, cv::BORDER_REPLICATE);
+                }
+            }
+        }
+    }
+
+    void resizeLanczosGold(const cv::Mat& src, cv::Mat& dst, double fx, double fy)
+    {
+        typedef void (*func_t)(const cv::Mat& src, cv::Mat& dst, double fx, double fy);
+
+        static const func_t lanczos_funcs[] =
+        {
+            resizeLanczosImpl<unsigned char>,
+            resizeLanczosImpl<signed char>,
+            resizeLanczosImpl<unsigned short>,
+            resizeLanczosImpl<short>,
+            resizeLanczosImpl<int>,
+            resizeLanczosImpl<float>
+        };
+
+        lanczos_funcs[src.depth()](src, dst, fx, fy);
+    }
+}
+
+///////////////////////////////////////////////////////////////////
+// Test
+
+PARAM_TEST_CASE(ResizeLanczos, cv::cuda::DeviceInfo, cv::Size, MatType, double, UseRoi)
+{
+    cv::cuda::DeviceInfo devInfo;
+    cv::Size size;
+    double coeff;
+    int type;
+    bool useRoi;
+
+    virtual void SetUp()
+    {
+        devInfo = GET_PARAM(0);
+        size = GET_PARAM(1);
+        type = GET_PARAM(2);
+        coeff = GET_PARAM(3);
+        useRoi = GET_PARAM(4);
+
+        cv::cuda::setDevice(devInfo.deviceID());
+    }
+
+    virtual void TearDown()
+    {
+        // GpuMat destructors will automatically clean up GPU memory
+    }
+};
+
+CUDA_TEST_P(ResizeLanczos, Accuracy)
+{
+    cv::Mat src = randomMat(size, type);
+
+    cv::cuda::GpuMat dst = createMat(cv::Size(cv::saturate_cast<int>(src.cols * coeff), cv::saturate_cast<int>(src.rows * coeff)), type, useRoi);
+    cv::cuda::resize(loadMat(src, useRoi), dst, cv::Size(), coeff, coeff, cv::INTER_LANCZOS4);
+
+    cv::Mat dst_gold;
+    resizeLanczosGold(src, dst_gold, coeff, coeff);
+
+    EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-2 : 1.0);
+}
+
+INSTANTIATE_TEST_CASE_P(CUDA_Warping, ResizeLanczos, testing::Combine(
+    testing::Values(cv::cuda::DeviceInfo()),
+    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)),
+    testing::Values(0.3, 0.5, 1.5, 2.0),
+    WHOLE_SUBMAT));
+
+/////////////////
+
+PARAM_TEST_CASE(ResizeLanczosSameAsHost, cv::cuda::DeviceInfo, cv::Size, MatType, double, UseRoi)
+{
+    cv::cuda::DeviceInfo devInfo;
+    cv::Size size;
+    double coeff;
+    int type;
+    bool useRoi;
+
+    virtual void SetUp()
+    {
+        devInfo = GET_PARAM(0);
+        size = GET_PARAM(1);
+        type = GET_PARAM(2);
+        coeff = GET_PARAM(3);
+        useRoi = GET_PARAM(4);
+
+        cv::cuda::setDevice(devInfo.deviceID());
+    }
+
+    virtual void TearDown()
+    {
+        // GpuMat destructors will automatically clean up GPU memory
+    }
+};
+
+CUDA_TEST_P(ResizeLanczosSameAsHost, Accuracy)
+{
+    cv::Mat src = randomMat(size, type);
+
+    cv::cuda::GpuMat dst = createMat(cv::Size(cv::saturate_cast<int>(src.cols * coeff), cv::saturate_cast<int>(src.rows * coeff)), type, useRoi);
+    cv::cuda::resize(loadMat(src, useRoi), dst, cv::Size(), coeff, coeff, cv::INTER_LANCZOS4);
+
+    cv::Mat dst_gold;
+    cv::resize(src, dst_gold, cv::Size(), coeff, coeff, cv::INTER_LANCZOS4);
+
+    EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-2 : 1.0);
+}
+
+INSTANTIATE_TEST_CASE_P(CUDA_Warping, ResizeLanczosSameAsHost, testing::Combine(
+    testing::Values(cv::cuda::DeviceInfo()),
+    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)),
+    testing::Values(0.3, 0.5, 1.5, 2.0),
+    WHOLE_SUBMAT));
+
+}} // namespace
+#endif // HAVE_CUDA