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/stereo_match.py

@@ -0,0 +1,85 @@
+#!/usr/bin/env python
+
+'''
+Simple example of stereo image matching and point cloud generation.
+
+Resulting .ply file cam be easily viewed using MeshLab ( http://meshlab.sourceforge.net/ )
+'''
+
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import numpy as np
+import cv2 as cv
+
+ply_header = '''ply
+format ascii 1.0
+element vertex %(vert_num)d
+property float x
+property float y
+property float z
+property uchar red
+property uchar green
+property uchar blue
+end_header
+'''
+
+def write_ply(fn, verts, colors):
+    verts = verts.reshape(-1, 3)
+    colors = colors.reshape(-1, 3)
+    verts = np.hstack([verts, colors])
+    with open(fn, 'wb') as f:
+        f.write((ply_header % dict(vert_num=len(verts))).encode('utf-8'))
+        np.savetxt(f, verts, fmt='%f %f %f %d %d %d ')
+
+
+def main():
+    print('loading images...')
+    imgL = cv.pyrDown(cv.imread(cv.samples.findFile('aloeL.jpg')))  # downscale images for faster processing
+    imgR = cv.pyrDown(cv.imread(cv.samples.findFile('aloeR.jpg')))
+
+    # disparity range is tuned for 'aloe' image pair
+    window_size = 3
+    min_disp = 16
+    num_disp = 112-min_disp
+    stereo = cv.StereoSGBM_create(minDisparity = min_disp,
+        numDisparities = num_disp,
+        blockSize = 16,
+        P1 = 8*3*window_size**2,
+        P2 = 32*3*window_size**2,
+        disp12MaxDiff = 1,
+        uniquenessRatio = 10,
+        speckleWindowSize = 100,
+        speckleRange = 32
+    )
+
+    print('computing disparity...')
+    disp = stereo.compute(imgL, imgR).astype(np.float32) / 16.0
+
+    print('generating 3d point cloud...',)
+    h, w = imgL.shape[:2]
+    f = 0.8*w                          # guess for focal length
+    Q = np.float32([[1, 0, 0, -0.5*w],
+                    [0,-1, 0,  0.5*h], # turn points 180 deg around x-axis,
+                    [0, 0, 0,     -f], # so that y-axis looks up
+                    [0, 0, 1,      0]])
+    points = cv.reprojectImageTo3D(disp, Q)
+    colors = cv.cvtColor(imgL, cv.COLOR_BGR2RGB)
+    mask = disp > disp.min()
+    out_points = points[mask]
+    out_colors = colors[mask]
+    out_fn = 'out.ply'
+    write_ply(out_fn, out_points, out_colors)
+    print('%s saved' % out_fn)
+
+    cv.imshow('left', imgL)
+    cv.imshow('disparity', (disp-min_disp)/num_disp)
+    cv.waitKey()
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()