feat: 切换后端至PaddleOCR-NCNN，切换工程为CMake

1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试
2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程
3.重整权利声明文件，重整代码工程，确保最小化侵权风险

Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake
Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c

3rdparty/opencv-4.5.4/modules/photo/test/ocl/test_denoising.cpp

@@ -0,0 +1,133 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+// Copyright (C) 2014, Advanced Micro Devices, Inc., all rights reserved.
+// Third party copyrights are property of their respective owners.
+
+#include "../test_precomp.hpp"
+#include "opencv2/ts/ocl_test.hpp"
+
+#ifdef HAVE_OPENCL
+
+namespace opencv_test {
+namespace ocl {
+
+PARAM_TEST_CASE(FastNlMeansDenoisingTestBase, Channels, int, bool, bool)
+{
+    int cn, normType, templateWindowSize, searchWindowSize;
+    std::vector<float> h;
+    bool use_roi, use_image;
+
+    TEST_DECLARE_INPUT_PARAMETER(src);
+    TEST_DECLARE_OUTPUT_PARAMETER(dst);
+
+    virtual void SetUp()
+    {
+        cn = GET_PARAM(0);
+        normType = GET_PARAM(1);
+        use_roi = GET_PARAM(2);
+        use_image = GET_PARAM(3);
+
+        templateWindowSize = 7;
+        searchWindowSize = 21;
+
+        h.resize(cn);
+        for (int i=0; i<cn; i++)
+            h[i] = 3.0f + 0.5f*i;
+    }
+
+    void generateTestData()
+    {
+        const int type = CV_8UC(cn);
+        Mat image;
+
+        if (use_image) {
+            image = readImage("denoising/lena_noised_gaussian_sigma=10.png",
+                                  cn == 1 ? IMREAD_GRAYSCALE : IMREAD_COLOR);
+            ASSERT_FALSE(image.empty());
+        }
+
+        Size roiSize = use_image ? image.size() : randomSize(1, MAX_VALUE);
+        Border srcBorder = randomBorder(0, use_roi ? MAX_VALUE : 0);
+        randomSubMat(src, src_roi, roiSize, srcBorder, type, 0, 255);
+        if (use_image) {
+            ASSERT_TRUE(cn > 0 && cn <= 4);
+            if (cn == 2) {
+                int from_to[] = { 0,0, 1,1 };
+                src_roi.create(roiSize, type);
+                mixChannels(&image, 1, &src_roi, 1, from_to, 2);
+            }
+            else if (cn == 4) {
+                int from_to[] = { 0,0, 1,1, 2,2, 1,3};
+                src_roi.create(roiSize, type);
+                mixChannels(&image, 1, &src_roi, 1, from_to, 4);
+            }
+            else image.copyTo(src_roi);
+        }
+
+        Border dstBorder = randomBorder(0, use_roi ? MAX_VALUE : 0);
+        randomSubMat(dst, dst_roi, roiSize, dstBorder, type, 0, 255);
+
+        UMAT_UPLOAD_INPUT_PARAMETER(src);
+        UMAT_UPLOAD_OUTPUT_PARAMETER(dst);
+    }
+};
+
+typedef FastNlMeansDenoisingTestBase FastNlMeansDenoising;
+
+OCL_TEST_P(FastNlMeansDenoising, Mat)
+{
+    for (int j = 0; j < test_loop_times; j++)
+    {
+        generateTestData();
+
+        OCL_OFF(cv::fastNlMeansDenoising(src_roi, dst_roi, std::vector<float>(1, h[0]), templateWindowSize, searchWindowSize, normType));
+        OCL_ON(cv::fastNlMeansDenoising(usrc_roi, udst_roi, std::vector<float>(1, h[0]), templateWindowSize, searchWindowSize, normType));
+
+        OCL_EXPECT_MATS_NEAR(dst, 1);
+    }
+}
+
+typedef FastNlMeansDenoisingTestBase FastNlMeansDenoising_hsep;
+
+OCL_TEST_P(FastNlMeansDenoising_hsep, Mat)
+{
+    for (int j = 0; j < test_loop_times; j++)
+    {
+        generateTestData();
+
+        OCL_OFF(cv::fastNlMeansDenoising(src_roi, dst_roi, h, templateWindowSize, searchWindowSize, normType));
+        OCL_ON(cv::fastNlMeansDenoising(usrc_roi, udst_roi, h, templateWindowSize, searchWindowSize, normType));
+
+        OCL_EXPECT_MATS_NEAR(dst, 1);
+    }
+}
+
+typedef FastNlMeansDenoisingTestBase FastNlMeansDenoisingColored;
+
+OCL_TEST_P(FastNlMeansDenoisingColored, Mat)
+{
+    for (int j = 0; j < test_loop_times; j++)
+    {
+        generateTestData();
+
+        OCL_OFF(cv::fastNlMeansDenoisingColored(src_roi, dst_roi, h[0], h[0], templateWindowSize, searchWindowSize));
+        OCL_ON(cv::fastNlMeansDenoisingColored(usrc_roi, udst_roi, h[0], h[0], templateWindowSize, searchWindowSize));
+
+        OCL_EXPECT_MATS_NEAR(dst, 1);
+    }
+}
+
+OCL_INSTANTIATE_TEST_CASE_P(Photo, FastNlMeansDenoising,
+                            Combine(Values(1, 2, 3, 4), Values((int)NORM_L2, (int)NORM_L1),
+                                    Bool(), Values(true)));
+OCL_INSTANTIATE_TEST_CASE_P(Photo, FastNlMeansDenoising_hsep,
+                            Combine(Values(1, 2, 3, 4), Values((int)NORM_L2, (int)NORM_L1),
+                                    Bool(), Values(true)));
+OCL_INSTANTIATE_TEST_CASE_P(Photo, FastNlMeansDenoisingColored,
+                            Combine(Values(3, 4), Values((int)NORM_L2), Bool(), Values(false)));
+
+} } // namespace opencv_test::ocl
+
+#endif // HAVE_OPENCL