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/calibrate.py

@@ -0,0 +1,135 @@
+#!/usr/bin/env python
+
+'''
+camera calibration for distorted images with chess board samples
+reads distorted images, calculates the calibration and write undistorted images
+
+usage:
+    calibrate.py [--debug <output path>] [--square_size] [<image mask>]
+
+default values:
+    --debug:    ./output/
+    --square_size: 1.0
+    <image mask> defaults to ../data/left*.jpg
+'''
+
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import numpy as np
+import cv2 as cv
+
+# local modules
+from common import splitfn
+
+# built-in modules
+import os
+
+def main():
+    import sys
+    import getopt
+    from glob import glob
+
+    args, img_mask = getopt.getopt(sys.argv[1:], '', ['debug=', 'square_size=', 'threads='])
+    args = dict(args)
+    args.setdefault('--debug', './output/')
+    args.setdefault('--square_size', 1.0)
+    args.setdefault('--threads', 4)
+    if not img_mask:
+        img_mask = '../data/left??.jpg'  # default
+    else:
+        img_mask = img_mask[0]
+
+    img_names = glob(img_mask)
+    debug_dir = args.get('--debug')
+    if debug_dir and not os.path.isdir(debug_dir):
+        os.mkdir(debug_dir)
+    square_size = float(args.get('--square_size'))
+
+    pattern_size = (9, 6)
+    pattern_points = np.zeros((np.prod(pattern_size), 3), np.float32)
+    pattern_points[:, :2] = np.indices(pattern_size).T.reshape(-1, 2)
+    pattern_points *= square_size
+
+    obj_points = []
+    img_points = []
+    h, w = cv.imread(img_names[0], cv.IMREAD_GRAYSCALE).shape[:2]  # TODO: use imquery call to retrieve results
+
+    def processImage(fn):
+        print('processing %s... ' % fn)
+        img = cv.imread(fn, 0)
+        if img is None:
+            print("Failed to load", fn)
+            return None
+
+        assert w == img.shape[1] and h == img.shape[0], ("size: %d x %d ... " % (img.shape[1], img.shape[0]))
+        found, corners = cv.findChessboardCorners(img, pattern_size)
+        if found:
+            term = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_COUNT, 30, 0.1)
+            cv.cornerSubPix(img, corners, (5, 5), (-1, -1), term)
+
+        if debug_dir:
+            vis = cv.cvtColor(img, cv.COLOR_GRAY2BGR)
+            cv.drawChessboardCorners(vis, pattern_size, corners, found)
+            _path, name, _ext = splitfn(fn)
+            outfile = os.path.join(debug_dir, name + '_chess.png')
+            cv.imwrite(outfile, vis)
+
+        if not found:
+            print('chessboard not found')
+            return None
+
+        print('           %s... OK' % fn)
+        return (corners.reshape(-1, 2), pattern_points)
+
+    threads_num = int(args.get('--threads'))
+    if threads_num <= 1:
+        chessboards = [processImage(fn) for fn in img_names]
+    else:
+        print("Run with %d threads..." % threads_num)
+        from multiprocessing.dummy import Pool as ThreadPool
+        pool = ThreadPool(threads_num)
+        chessboards = pool.map(processImage, img_names)
+
+    chessboards = [x for x in chessboards if x is not None]
+    for (corners, pattern_points) in chessboards:
+        img_points.append(corners)
+        obj_points.append(pattern_points)
+
+    # calculate camera distortion
+    rms, camera_matrix, dist_coefs, _rvecs, _tvecs = cv.calibrateCamera(obj_points, img_points, (w, h), None, None)
+
+    print("\nRMS:", rms)
+    print("camera matrix:\n", camera_matrix)
+    print("distortion coefficients: ", dist_coefs.ravel())
+
+    # undistort the image with the calibration
+    print('')
+    for fn in img_names if debug_dir else []:
+        _path, name, _ext = splitfn(fn)
+        img_found = os.path.join(debug_dir, name + '_chess.png')
+        outfile = os.path.join(debug_dir, name + '_undistorted.png')
+
+        img = cv.imread(img_found)
+        if img is None:
+            continue
+
+        h, w = img.shape[:2]
+        newcameramtx, roi = cv.getOptimalNewCameraMatrix(camera_matrix, dist_coefs, (w, h), 1, (w, h))
+
+        dst = cv.undistort(img, camera_matrix, dist_coefs, None, newcameramtx)
+
+        # crop and save the image
+        x, y, w, h = roi
+        dst = dst[y:y+h, x:x+w]
+
+        print('Undistorted image written to: %s' % outfile)
+        cv.imwrite(outfile, dst)
+
+    print('Done')
+
+
+if __name__ == '__main__':
+    print(__doc__)
+    main()
+    cv.destroyAllWindows()