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/calib3d/misc/python/test/test_calibration.py

@@ -0,0 +1,73 @@
+#!/usr/bin/env python
+
+'''
+camera calibration for distorted images with chess board samples
+reads distorted images, calculates the calibration and write undistorted images
+'''
+
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import numpy as np
+import cv2 as cv
+
+from tests_common import NewOpenCVTests
+
+class calibration_test(NewOpenCVTests):
+
+    def test_calibration(self):
+        img_names = []
+        for i in range(1, 15):
+            if i < 10:
+                img_names.append('samples/data/left0{}.jpg'.format(str(i)))
+            elif i != 10:
+                img_names.append('samples/data/left{}.jpg'.format(str(i)))
+
+        square_size = 1.0
+        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 = 0, 0
+        for fn in img_names:
+            img = self.get_sample(fn, 0)
+            if img is None:
+                continue
+
+            h, w = img.shape[:2]
+            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 not found:
+                continue
+
+            img_points.append(corners.reshape(-1, 2))
+            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, flags = 0)
+
+        eps = 0.01
+        normCamEps = 10.0
+        normDistEps = 0.05
+
+        cameraMatrixTest = [[ 532.80992189,    0.,          342.4952186 ],
+         [   0.,         532.93346422,  233.8879292 ],
+         [   0.,            0.,            1.        ]]
+
+        distCoeffsTest = [ -2.81325576e-01,   2.91130406e-02,
+           1.21234330e-03,  -1.40825372e-04, 1.54865844e-01]
+
+        self.assertLess(abs(rms - 0.196334638034), eps)
+        self.assertLess(cv.norm(camera_matrix - cameraMatrixTest, cv.NORM_L1), normCamEps)
+        self.assertLess(cv.norm(dist_coefs - distCoeffsTest, cv.NORM_L1), normDistEps)
+
+
+
+if __name__ == '__main__':
+    NewOpenCVTests.bootstrap()

3rdparty/opencv-4.5.4/modules/calib3d/misc/python/test/test_solvepnp.py

@@ -0,0 +1,64 @@
+#!/usr/bin/env python
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import numpy as np
+import cv2 as cv
+
+from tests_common import NewOpenCVTests
+
+class solvepnp_test(NewOpenCVTests):
+
+    def test_regression_16040(self):
+        obj_points = np.array([[0, 0, 0], [0, 1, 0], [1, 1, 0], [1, 0, 0]], dtype=np.float32)
+        img_points = np.array(
+            [[700, 400], [700, 600], [900, 600], [900, 400]], dtype=np.float32
+        )
+
+        cameraMatrix = np.array(
+            [[712.0634, 0, 800], [0, 712.540, 500], [0, 0, 1]], dtype=np.float32
+        )
+        distCoeffs = np.array([[0, 0, 0, 0]], dtype=np.float32)
+        r = np.array([], dtype=np.float32)
+        x, r, t, e = cv.solvePnPGeneric(
+            obj_points, img_points, cameraMatrix, distCoeffs, reprojectionError=r
+        )
+
+    def test_regression_16040_2(self):
+        obj_points = np.array([[0, 0, 0], [0, 1, 0], [1, 1, 0], [1, 0, 0]], dtype=np.float32)
+        img_points = np.array(
+            [[[700, 400], [700, 600], [900, 600], [900, 400]]], dtype=np.float32
+        )
+
+        cameraMatrix = np.array(
+            [[712.0634, 0, 800], [0, 712.540, 500], [0, 0, 1]], dtype=np.float32
+        )
+        distCoeffs = np.array([[0, 0, 0, 0]], dtype=np.float32)
+        r = np.array([], dtype=np.float32)
+        x, r, t, e = cv.solvePnPGeneric(
+            obj_points, img_points, cameraMatrix, distCoeffs, reprojectionError=r
+        )
+
+    def test_regression_16049(self):
+        obj_points = np.array([[0, 0, 0], [0, 1, 0], [1, 1, 0], [1, 0, 0]], dtype=np.float32)
+        img_points = np.array(
+            [[[700, 400], [700, 600], [900, 600], [900, 400]]], dtype=np.float32
+        )
+
+        cameraMatrix = np.array(
+            [[712.0634, 0, 800], [0, 712.540, 500], [0, 0, 1]], dtype=np.float32
+        )
+        distCoeffs = np.array([[0, 0, 0, 0]], dtype=np.float32)
+        x, r, t, e = cv.solvePnPGeneric(
+            obj_points, img_points, cameraMatrix, distCoeffs
+        )
+        if e is None:
+            # noArray() is supported, see https://github.com/opencv/opencv/issues/16049
+            pass
+        else:
+            eDump = cv.utils.dumpInputArray(e)
+            self.assertEqual(eDump, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=1 dims(-1)=2 size(-1)=1x1 type(-1)=CV_32FC1")
+
+
+if __name__ == '__main__':
+    NewOpenCVTests.bootstrap()