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/features2D/Homography/panorama_stitching_rotating_camera.py

@@ -0,0 +1,71 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import numpy as np
+import cv2 as cv
+
+def basicPanoramaStitching(img1Path, img2Path):
+    img1 = cv.imread(cv.samples.findFile(img1Path))
+    img2 = cv.imread(cv.samples.findFile(img2Path))
+
+    # [camera-pose-from-Blender-at-location-1]
+    c1Mo = np.array([[0.9659258723258972, 0.2588190734386444, 0.0, 1.5529145002365112],
+                     [ 0.08852133899927139, -0.3303661346435547, -0.9396926164627075, -0.10281121730804443],
+                     [-0.24321036040782928, 0.9076734185218811, -0.342020183801651, 6.130080699920654],
+                     [0, 0, 0, 1]],dtype=np.float64)
+    # [camera-pose-from-Blender-at-location-1]
+
+    # [camera-pose-from-Blender-at-location-2]
+    c2Mo = np.array([[0.9659258723258972, -0.2588190734386444, 0.0, -1.5529145002365112],
+                     [-0.08852133899927139, -0.3303661346435547, -0.9396926164627075, -0.10281121730804443],
+                     [0.24321036040782928, 0.9076734185218811, -0.342020183801651, 6.130080699920654],
+                     [0, 0, 0, 1]],dtype=np.float64)
+    # [camera-pose-from-Blender-at-location-2]
+
+    # [camera-intrinsics-from-Blender]
+    cameraMatrix = np.array([[700.0, 0.0, 320.0], [0.0, 700.0, 240.0], [0, 0, 1]], dtype=np.float32)
+    # [camera-intrinsics-from-Blender]
+
+    # [extract-rotation]
+    R1 = c1Mo[0:3, 0:3]
+    R2 = c2Mo[0:3, 0:3]
+    #[extract-rotation]
+
+    # [compute-rotation-displacement]
+    R2 = R2.transpose()
+    R_2to1 = np.dot(R1,R2)
+    # [compute-rotation-displacement]
+
+    # [compute-homography]
+    H = cameraMatrix.dot(R_2to1).dot(np.linalg.inv(cameraMatrix))
+    H = H / H[2][2]
+    # [compute-homography]
+
+    # [stitch]
+    img_stitch = cv.warpPerspective(img2, H, (img2.shape[1]*2, img2.shape[0]))
+    img_stitch[0:img1.shape[0], 0:img1.shape[1]] = img1
+    # [stitch]
+
+    img_space = np.zeros((img1.shape[0],50,3), dtype=np.uint8)
+    img_compare = cv.hconcat([img1,img_space, img2])
+
+    cv.imshow("Final", img_compare)
+    cv.imshow("Panorama", img_stitch)
+    cv.waitKey(0)
+
+def main():
+    import argparse
+    parser = argparse.ArgumentParser(description="Code for homography tutorial. Example 5: basic panorama stitching from a rotating camera.")
+    parser.add_argument("-I1","--image1", help = "path to first image", default="Blender_Suzanne1.jpg")
+    parser.add_argument("-I2","--image2", help = "path to second image", default="Blender_Suzanne2.jpg")
+    args = parser.parse_args()
+    print("Panorama Stitching Started")
+    basicPanoramaStitching(args.image1, args.image2)
+    print("Panorama Stitching Completed Successfully")
+
+
+if __name__ == '__main__':
+    main()

3rdparty/opencv-4.5.4/samples/python/tutorial_code/features2D/Homography/perspective_correction.py

@@ -0,0 +1,74 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import numpy as np
+import cv2 as cv
+import sys
+
+
+def randomColor():
+    color = np.random.randint(0, 255,(1, 3))
+    return color[0].tolist()
+
+def  perspectiveCorrection(img1Path, img2Path ,patternSize ):
+    img1 = cv.imread(cv.samples.findFile(img1Path))
+    img2 = cv.imread(cv.samples.findFile(img2Path))
+
+    # [find-corners]
+    ret1, corners1 = cv.findChessboardCorners(img1, patternSize)
+    ret2, corners2 = cv.findChessboardCorners(img2, patternSize)
+    # [find-corners]
+
+    if not ret1 or not ret2:
+        print("Error, cannot find the chessboard corners in both images.")
+        sys.exit(-1)
+
+    # [estimate-homography]
+    H, _ = cv.findHomography(corners1, corners2)
+    print(H)
+    # [estimate-homography]
+
+    # [warp-chessboard]
+    img1_warp = cv.warpPerspective(img1, H, (img1.shape[1], img1.shape[0]))
+    # [warp-chessboard]
+
+    img_draw_warp = cv.hconcat([img2, img1_warp])
+    cv.imshow("Desired chessboard view / Warped source chessboard view", img_draw_warp )
+
+    corners1 = corners1.tolist()
+    corners1 = [a[0] for a in corners1]
+
+    # [compute-transformed-corners]
+    img_draw_matches = cv.hconcat([img1, img2])
+    for i in range(len(corners1)):
+        pt1 = np.array([corners1[i][0], corners1[i][1], 1])
+        pt1 = pt1.reshape(3, 1)
+        pt2 = np.dot(H, pt1)
+        pt2 = pt2/pt2[2]
+        end = (int(img1.shape[1] + pt2[0]), int(pt2[1]))
+        cv.line(img_draw_matches, tuple([int(j) for j in corners1[i]]), end, randomColor(), 2)
+
+    cv.imshow("Draw matches", img_draw_matches)
+    cv.waitKey(0)
+    # [compute-transformed-corners]
+
+def main():
+    import argparse
+    parser = argparse.ArgumentParser()
+    parser.add_argument('-I1', "--image1", help="Path to the first image", default="left02.jpg")
+    parser.add_argument('-I2', "--image2", help="Path to the second image", default="left01.jpg")
+    parser.add_argument('-H', "--height", help="Height of pattern size", default=6)
+    parser.add_argument('-W', "--width", help="Width of pattern size", default=9)
+    args = parser.parse_args()
+
+    img1Path = args.image1
+    img2Path = args.image2
+    h = args.height
+    w = args.width
+    perspectiveCorrection(img1Path, img2Path, (w, h))
+
+if __name__ == "__main__":
+    main()