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/objdetect/misc/python/test/test_facedetect.py

@@ -0,0 +1,92 @@
+#!/usr/bin/env python
+
+'''
+face detection using haar cascades
+'''
+
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import numpy as np
+import cv2 as cv
+
+def detect(img, cascade):
+    rects = cascade.detectMultiScale(img, scaleFactor=1.275, minNeighbors=4, minSize=(30, 30),
+                                     flags=cv.CASCADE_SCALE_IMAGE)
+    if len(rects) == 0:
+        return []
+    rects[:,2:] += rects[:,:2]
+    return rects
+
+from tests_common import NewOpenCVTests, intersectionRate
+
+class facedetect_test(NewOpenCVTests):
+
+    def test_facedetect(self):
+        cascade_fn = self.repoPath + '/data/haarcascades/haarcascade_frontalface_alt.xml'
+        nested_fn  = self.repoPath + '/data/haarcascades/haarcascade_eye.xml'
+
+        cascade = cv.CascadeClassifier(cascade_fn)
+        nested = cv.CascadeClassifier(nested_fn)
+
+        samples = ['samples/data/lena.jpg', 'cv/cascadeandhog/images/mona-lisa.png']
+
+        faces = []
+        eyes = []
+
+        testFaces = [
+        #lena
+        [[218, 200, 389, 371],
+        [ 244, 240, 294, 290],
+        [ 309, 246, 352, 289]],
+
+        #lisa
+        [[167, 119, 307, 259],
+        [188, 153, 229, 194],
+        [236, 153, 277, 194]]
+        ]
+
+        for sample in samples:
+
+            img = self.get_sample(  sample)
+            gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
+            gray = cv.GaussianBlur(gray, (5, 5), 0)
+
+            rects = detect(gray, cascade)
+            faces.append(rects)
+
+            if not nested.empty():
+                for x1, y1, x2, y2 in rects:
+                    roi = gray[y1:y2, x1:x2]
+                    subrects = detect(roi.copy(), nested)
+
+                    for rect in subrects:
+                        rect[0] += x1
+                        rect[2] += x1
+                        rect[1] += y1
+                        rect[3] += y1
+
+                    eyes.append(subrects)
+
+        faces_matches = 0
+        eyes_matches = 0
+
+        eps = 0.8
+
+        for i in range(len(faces)):
+            for j in range(len(testFaces)):
+                if intersectionRate(faces[i][0], testFaces[j][0]) > eps:
+                    faces_matches += 1
+                    #check eyes
+                    if len(eyes[i]) == 2:
+                        if intersectionRate(eyes[i][0], testFaces[j][1]) > eps and intersectionRate(eyes[i][1] , testFaces[j][2]) > eps:
+                            eyes_matches += 1
+                        elif intersectionRate(eyes[i][1], testFaces[j][1]) > eps and intersectionRate(eyes[i][0], testFaces[j][2]) > eps:
+                            eyes_matches += 1
+
+        self.assertEqual(faces_matches, 2)
+        self.assertEqual(eyes_matches, 2)
+
+
+if __name__ == '__main__':
+    NewOpenCVTests.bootstrap()

3rdparty/opencv-4.5.4/modules/objdetect/misc/python/test/test_peopledetect.py

@@ -0,0 +1,65 @@
+#!/usr/bin/env python
+
+'''
+example to detect upright people in images using HOG features
+'''
+
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import numpy as np
+import cv2 as cv
+
+
+def inside(r, q):
+    rx, ry, rw, rh = r
+    qx, qy, qw, qh = q
+    return rx > qx and ry > qy and rx + rw < qx + qw and ry + rh < qy + qh
+
+from tests_common import NewOpenCVTests, intersectionRate
+
+class peopledetect_test(NewOpenCVTests):
+    def test_peopledetect(self):
+
+        hog = cv.HOGDescriptor()
+        hog.setSVMDetector( cv.HOGDescriptor_getDefaultPeopleDetector() )
+
+        dirPath = 'samples/data/'
+        samples = ['basketball1.png', 'basketball2.png']
+
+        testPeople = [
+        [[23, 76, 164, 477], [440, 22, 637, 478]],
+        [[23, 76, 164, 477], [440, 22, 637, 478]]
+        ]
+
+        eps = 0.5
+
+        for sample in samples:
+
+            img = self.get_sample(dirPath + sample, 0)
+
+            found, _w = hog.detectMultiScale(img, winStride=(8,8), padding=(32,32), scale=1.05)
+            found_filtered = []
+            for ri, r in enumerate(found):
+                for qi, q in enumerate(found):
+                    if ri != qi and inside(r, q):
+                        break
+                else:
+                    found_filtered.append(r)
+
+            matches = 0
+
+            for i in range(len(found_filtered)):
+                for j in range(len(testPeople)):
+
+                    found_rect = (found_filtered[i][0], found_filtered[i][1],
+                        found_filtered[i][0] + found_filtered[i][2],
+                        found_filtered[i][1] + found_filtered[i][3])
+
+                    if intersectionRate(found_rect, testPeople[j][0]) > eps or intersectionRate(found_rect, testPeople[j][1]) > eps:
+                        matches += 1
+
+            self.assertGreater(matches, 0)
+
+if __name__ == '__main__':
+    NewOpenCVTests.bootstrap()

3rdparty/opencv-4.5.4/modules/objdetect/misc/python/test/test_qrcode_detect.py

@@ -0,0 +1,52 @@
+#!/usr/bin/env python
+'''
+===============================================================================
+QR code detect and decode pipeline.
+===============================================================================
+'''
+import os
+import numpy as np
+import cv2 as cv
+
+from tests_common import NewOpenCVTests
+
+class qrcode_detector_test(NewOpenCVTests):
+
+    def test_detect(self):
+        img = cv.imread(os.path.join(self.extraTestDataPath, 'cv/qrcode/link_ocv.jpg'))
+        self.assertFalse(img is None)
+        detector = cv.QRCodeDetector()
+        retval, points = detector.detect(img)
+        self.assertTrue(retval)
+        self.assertEqual(points.shape, (1, 4, 2))
+
+    def test_detect_and_decode(self):
+        img = cv.imread(os.path.join(self.extraTestDataPath, 'cv/qrcode/link_ocv.jpg'))
+        self.assertFalse(img is None)
+        detector = cv.QRCodeDetector()
+        retval, points, straight_qrcode = detector.detectAndDecode(img)
+        self.assertEqual(retval, "https://opencv.org/")
+        self.assertEqual(points.shape, (1, 4, 2))
+
+    def test_detect_multi(self):
+        img = cv.imread(os.path.join(self.extraTestDataPath, 'cv/qrcode/multiple/6_qrcodes.png'))
+        self.assertFalse(img is None)
+        detector = cv.QRCodeDetector()
+        retval, points = detector.detectMulti(img)
+        self.assertTrue(retval)
+        self.assertEqual(points.shape, (6, 4, 2))
+
+    def test_detect_and_decode_multi(self):
+        img = cv.imread(os.path.join(self.extraTestDataPath, 'cv/qrcode/multiple/6_qrcodes.png'))
+        self.assertFalse(img is None)
+        detector = cv.QRCodeDetector()
+        retval, decoded_data, points, straight_qrcode = detector.detectAndDecodeMulti(img)
+        self.assertTrue(retval)
+        self.assertEqual(len(decoded_data), 6)
+        self.assertEqual(decoded_data[0], "TWO STEPS FORWARD")
+        self.assertEqual(decoded_data[1], "EXTRA")
+        self.assertEqual(decoded_data[2], "SKIP")
+        self.assertEqual(decoded_data[3], "STEP FORWARD")
+        self.assertEqual(decoded_data[4], "STEP BACK")
+        self.assertEqual(decoded_data[5], "QUESTION")
+        self.assertEqual(points.shape, (6, 4, 2))