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/samples/python/tutorial_code/ImgTrans/HoughLine/hough_lines.py

@@ -0,0 +1,79 @@
+"""
+@file hough_lines.py
+@brief This program demonstrates line finding with the Hough transform
+"""
+import sys
+import math
+import cv2 as cv
+import numpy as np
+
+
+def main(argv):
+    ## [load]
+    default_file = 'sudoku.png'
+    filename = argv[0] if len(argv) > 0 else default_file
+
+    # Loads an image
+    src = cv.imread(cv.samples.findFile(filename), cv.IMREAD_GRAYSCALE)
+
+    # Check if image is loaded fine
+    if src is None:
+        print ('Error opening image!')
+        print ('Usage: hough_lines.py [image_name -- default ' + default_file + '] \n')
+        return -1
+    ## [load]
+
+    ## [edge_detection]
+    # Edge detection
+    dst = cv.Canny(src, 50, 200, None, 3)
+    ## [edge_detection]
+
+    # Copy edges to the images that will display the results in BGR
+    cdst = cv.cvtColor(dst, cv.COLOR_GRAY2BGR)
+    cdstP = np.copy(cdst)
+
+    ## [hough_lines]
+    #  Standard Hough Line Transform
+    lines = cv.HoughLines(dst, 1, np.pi / 180, 150, None, 0, 0)
+    ## [hough_lines]
+    ## [draw_lines]
+    # Draw the lines
+    if lines is not None:
+        for i in range(0, len(lines)):
+            rho = lines[i][0][0]
+            theta = lines[i][0][1]
+            a = math.cos(theta)
+            b = math.sin(theta)
+            x0 = a * rho
+            y0 = b * rho
+            pt1 = (int(x0 + 1000*(-b)), int(y0 + 1000*(a)))
+            pt2 = (int(x0 - 1000*(-b)), int(y0 - 1000*(a)))
+
+            cv.line(cdst, pt1, pt2, (0,0,255), 3, cv.LINE_AA)
+    ## [draw_lines]
+
+    ## [hough_lines_p]
+    # Probabilistic Line Transform
+    linesP = cv.HoughLinesP(dst, 1, np.pi / 180, 50, None, 50, 10)
+    ## [hough_lines_p]
+    ## [draw_lines_p]
+    # Draw the lines
+    if linesP is not None:
+        for i in range(0, len(linesP)):
+            l = linesP[i][0]
+            cv.line(cdstP, (l[0], l[1]), (l[2], l[3]), (0,0,255), 3, cv.LINE_AA)
+    ## [draw_lines_p]
+    ## [imshow]
+    # Show results
+    cv.imshow("Source", src)
+    cv.imshow("Detected Lines (in red) - Standard Hough Line Transform", cdst)
+    cv.imshow("Detected Lines (in red) - Probabilistic Line Transform", cdstP)
+    ## [imshow]
+    ## [exit]
+    # Wait and Exit
+    cv.waitKey()
+    return 0
+    ## [exit]
+
+if __name__ == "__main__":
+    main(sys.argv[1:])