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/imgproc/test/ocl/test_houghlines.cpp

@@ -0,0 +1,184 @@
+// 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, Itseez, 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 {
+
+struct Vec2fComparator
+{
+    bool operator()(const Vec2f& a, const Vec2f b) const
+    {
+        if(a[0] != b[0]) return a[0] < b[0];
+        else return a[1] < b[1];
+    }
+};
+
+/////////////////////////////// HoughLines ////////////////////////////////////
+
+PARAM_TEST_CASE(HoughLines, double, double, int)
+{
+    double rhoStep, thetaStep;
+    int threshold;
+
+    Size src_size;
+    Mat src, dst;
+    UMat usrc, udst;
+
+    virtual void SetUp()
+    {
+        rhoStep = GET_PARAM(0);
+        thetaStep = GET_PARAM(1);
+        threshold = GET_PARAM(2);
+    }
+
+    void generateTestData()
+    {
+        src_size = randomSize(500, 1920);
+        src.create(src_size, CV_8UC1);
+        src.setTo(Scalar::all(0));
+        line(src, Point(0, 100), Point(100, 100), Scalar::all(255), 1);
+        line(src, Point(0, 200), Point(100, 200), Scalar::all(255), 1);
+        line(src, Point(0, 400), Point(100, 400), Scalar::all(255), 1);
+        line(src, Point(100, 0), Point(100, 200), Scalar::all(255), 1);
+        line(src, Point(200, 0), Point(200, 200), Scalar::all(255), 1);
+        line(src, Point(400, 0), Point(400, 200), Scalar::all(255), 1);
+
+        src.copyTo(usrc);
+    }
+
+    void readRealTestData()
+    {
+        Mat img = readImage("shared/pic5.png", IMREAD_GRAYSCALE);
+        Canny(img, src, 100, 150, 3);
+
+        src.copyTo(usrc);
+    }
+
+    void Near(double eps = 0.)
+    {
+        EXPECT_EQ(dst.size(), udst.size());
+
+        if (dst.total() > 0)
+        {
+            Mat lines_cpu, lines_gpu;
+            dst.copyTo(lines_cpu);
+            udst.copyTo(lines_gpu);
+
+            std::sort(lines_cpu.begin<Vec2f>(), lines_cpu.end<Vec2f>(), Vec2fComparator());
+            std::sort(lines_gpu.begin<Vec2f>(), lines_gpu.end<Vec2f>(), Vec2fComparator());
+
+            EXPECT_LE(TestUtils::checkNorm2(lines_cpu, lines_gpu), eps);
+        }
+    }
+};
+
+OCL_TEST_P(HoughLines, RealImage)
+{
+    readRealTestData();
+
+    OCL_OFF(cv::HoughLines(src, dst, rhoStep, thetaStep, threshold));
+    OCL_ON(cv::HoughLines(usrc, udst, rhoStep, thetaStep, threshold));
+
+    Near(1e-5);
+}
+
+OCL_TEST_P(HoughLines, GeneratedImage)
+{
+    for (int j = 0; j < test_loop_times; j++)
+    {
+        generateTestData();
+
+        OCL_OFF(cv::HoughLines(src, dst, rhoStep, thetaStep, threshold));
+        OCL_ON(cv::HoughLines(usrc, udst, rhoStep, thetaStep, threshold));
+
+        Near(1e-5);
+    }
+}
+
+/////////////////////////////// HoughLinesP ///////////////////////////////////
+
+PARAM_TEST_CASE(HoughLinesP, int, double, double)
+{
+    double rhoStep, thetaStep, minLineLength, maxGap;
+    int threshold;
+
+    Size src_size;
+    Mat src, dst;
+    UMat usrc, udst;
+
+    virtual void SetUp()
+    {
+        rhoStep = 1.0;
+        thetaStep = CV_PI / 180;
+        threshold = GET_PARAM(0);
+        minLineLength = GET_PARAM(1);
+        maxGap = GET_PARAM(2);
+    }
+
+    void readRealTestData()
+    {
+        Mat img = readImage("shared/pic5.png", IMREAD_GRAYSCALE);
+        Canny(img, src, 50, 200, 3);
+
+        src.copyTo(usrc);
+    }
+
+    void Near(double eps = 0.)
+    {
+        Mat lines_gpu = udst.getMat(ACCESS_READ);
+
+        if (dst.total() > 0 && lines_gpu.total() > 0)
+        {
+            Mat result_cpu(src.size(), CV_8UC1, Scalar::all(0));
+            Mat result_gpu(src.size(), CV_8UC1, Scalar::all(0));
+
+            MatConstIterator_<Vec4i> it = dst.begin<Vec4i>(), end = dst.end<Vec4i>();
+            for ( ; it != end; it++)
+            {
+                Vec4i p = *it;
+                line(result_cpu, Point(p[0], p[1]), Point(p[2], p[3]), Scalar(255));
+            }
+
+            it = lines_gpu.begin<Vec4i>(), end = lines_gpu.end<Vec4i>();
+            for ( ; it != end; it++)
+            {
+                Vec4i p = *it;
+                line(result_gpu, Point(p[0], p[1]), Point(p[2], p[3]), Scalar(255));
+            }
+
+            EXPECT_MAT_SIMILAR(result_cpu, result_gpu, eps);
+        }
+    }
+};
+
+
+OCL_TEST_P(HoughLinesP, RealImage)
+{
+    readRealTestData();
+
+    OCL_OFF(cv::HoughLinesP(src, dst, rhoStep, thetaStep, threshold, minLineLength, maxGap));
+    OCL_ON(cv::HoughLinesP(usrc, udst, rhoStep, thetaStep, threshold, minLineLength, maxGap));
+
+    Near(0.25);
+}
+
+OCL_INSTANTIATE_TEST_CASE_P(Imgproc, HoughLines, Combine(Values(1, 0.5),                        // rhoStep
+                                                         Values(CV_PI / 180.0, CV_PI / 360.0),  // thetaStep
+                                                         Values(85, 150)));                     // threshold
+
+OCL_INSTANTIATE_TEST_CASE_P(Imgproc, HoughLinesP, Combine(Values(100, 150),                     // threshold
+                                                          Values(50, 100),                      // minLineLength
+                                                          Values(5, 10)));                      // maxLineGap
+
+} } // namespace opencv_test::ocl
+
+#endif // HAVE_OPENCL