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/python/test/test_houghcircles.py

@@ -0,0 +1,131 @@
+#!/usr/bin/python
+
+'''
+This example illustrates how to use cv.HoughCircles() function.
+'''
+
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import cv2 as cv
+import numpy as np
+import sys
+from numpy import pi, sin, cos
+
+from tests_common import NewOpenCVTests
+
+def circleApproximation(circle):
+
+    nPoints = 30
+    dPhi = 2*pi / nPoints
+    contour = []
+    for i in range(nPoints):
+        contour.append(([circle[0] + circle[2]*cos(i*dPhi),
+            circle[1] + circle[2]*sin(i*dPhi)]))
+
+    return np.array(contour).astype(int)
+
+def convContoursIntersectiponRate(c1, c2):
+
+    s1 = cv.contourArea(c1)
+    s2 = cv.contourArea(c2)
+
+    s, _ = cv.intersectConvexConvex(c1, c2)
+
+    return 2*s/(s1+s2)
+
+class houghcircles_test(NewOpenCVTests):
+
+    def test_houghcircles(self):
+
+        fn = "samples/data/board.jpg"
+
+        src = self.get_sample(fn, 1)
+        img = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
+        img = cv.medianBlur(img, 5)
+
+        circles = cv.HoughCircles(img, cv.HOUGH_GRADIENT, 1, 10, np.array([]), 100, 30, 1, 30)[0]
+
+        testCircles = [[38, 181, 17.6],
+        [99.7, 166, 13.12],
+        [142.7, 160, 13.52],
+        [223.6, 110, 8.62],
+        [79.1, 206.7, 8.62],
+        [47.5, 351.6, 11.64],
+        [189.5, 354.4, 11.64],
+        [189.8, 298.9, 10.64],
+        [189.5, 252.4, 14.62],
+        [252.5, 393.4, 15.62],
+        [602.9, 467.5, 11.42],
+        [222, 210.4, 9.12],
+        [263.1, 216.7, 9.12],
+        [359.8, 222.6, 9.12],
+        [518.9, 120.9, 9.12],
+        [413.8, 113.4, 9.12],
+        [489, 127.2, 9.12],
+        [448.4, 121.3, 9.12],
+        [384.6, 128.9, 8.62]]
+
+        matches_counter = 0
+
+        for i in range(len(testCircles)):
+            for j in range(len(circles)):
+
+                tstCircle = circleApproximation(testCircles[i])
+                circle = circleApproximation(circles[j])
+                if convContoursIntersectiponRate(tstCircle, circle) > 0.6:
+                    matches_counter += 1
+
+        self.assertGreater(float(matches_counter) / len(testCircles), .5)
+        self.assertLess(float(len(circles) - matches_counter) / len(circles), .75)
+
+
+    def test_houghcircles_alt(self):
+
+        fn = "samples/data/board.jpg"
+
+        src = self.get_sample(fn, 1)
+        img = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
+        img = cv.medianBlur(img, 5)
+
+        circles = cv.HoughCircles(img, cv.HOUGH_GRADIENT_ALT, 1, 10, np.array([]), 300, 0.9, 1, 30)
+
+        self.assertEqual(circles.shape, (1, 18, 3))
+
+        circles = circles[0]
+
+        testCircles = [[38, 181, 17.6],
+        [99.7, 166, 13.12],
+        [142.7, 160, 13.52],
+        [223.6, 110, 8.62],
+        [79.1, 206.7, 8.62],
+        [47.5, 351.6, 11.64],
+        [189.5, 354.4, 11.64],
+        [189.8, 298.9, 10.64],
+        [189.5, 252.4, 14.62],
+        [252.5, 393.4, 15.62],
+        [602.9, 467.5, 11.42],
+        [222, 210.4, 9.12],
+        [263.1, 216.7, 9.12],
+        [359.8, 222.6, 9.12],
+        [518.9, 120.9, 9.12],
+        [413.8, 113.4, 9.12],
+        [489, 127.2, 9.12],
+        [448.4, 121.3, 9.12],
+        [384.6, 128.9, 8.62]]
+
+        matches_counter = 0
+
+        for i in range(len(testCircles)):
+            for j in range(len(circles)):
+
+                tstCircle = circleApproximation(testCircles[i])
+                circle = circleApproximation(circles[j])
+                if convContoursIntersectiponRate(tstCircle, circle) > 0.6:
+                    matches_counter += 1
+
+        self.assertGreater(float(matches_counter) / len(testCircles), .5)
+        self.assertLess(float(len(circles) - matches_counter) / len(circles), .75)
+
+if __name__ == '__main__':
+    NewOpenCVTests.bootstrap()