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/python/test/test_camshift.py

@@ -0,0 +1,96 @@
+#!/usr/bin/env python
+
+'''
+Camshift tracker
+================
+
+This is a demo that shows mean-shift based tracking
+You select a color objects such as your face and it tracks it.
+This reads from video camera (0 by default, or the camera number the user enters)
+
+http://www.robinhewitt.com/research/track/camshift.html
+
+'''
+
+# Python 2/3 compatibility
+from __future__ import print_function
+import sys
+PY3 = sys.version_info[0] == 3
+
+if PY3:
+    xrange = range
+
+import numpy as np
+import cv2 as cv
+from tst_scene_render import TestSceneRender
+
+from tests_common import NewOpenCVTests, intersectionRate
+
+class camshift_test(NewOpenCVTests):
+
+    framesNum = 300
+    frame = None
+    selection = None
+    drag_start = None
+    show_backproj = False
+    track_window = None
+    render = None
+    errors = 0
+
+    def prepareRender(self):
+
+        self.render = TestSceneRender(self.get_sample('samples/data/pca_test1.jpg'), deformation = True)
+
+    def runTracker(self):
+
+        framesCounter = 0
+        self.selection = True
+
+        xmin, ymin, xmax, ymax = self.render.getCurrentRect()
+
+        self.track_window = (xmin, ymin, xmax - xmin, ymax - ymin)
+
+        while True:
+            framesCounter += 1
+            self.frame = self.render.getNextFrame()
+            hsv = cv.cvtColor(self.frame, cv.COLOR_BGR2HSV)
+            mask = cv.inRange(hsv, np.array((0., 60., 32.)), np.array((180., 255., 255.)))
+
+            if self.selection:
+                x0, y0, x1, y1 = self.render.getCurrentRect() + 50
+                x0 -= 100
+                y0 -= 100
+
+                hsv_roi = hsv[y0:y1, x0:x1]
+                mask_roi = mask[y0:y1, x0:x1]
+                hist = cv.calcHist( [hsv_roi], [0], mask_roi, [16], [0, 180] )
+                cv.normalize(hist, hist, 0, 255, cv.NORM_MINMAX)
+                self.hist = hist.reshape(-1)
+                self.selection = False
+
+            if self.track_window and self.track_window[2] > 0 and self.track_window[3] > 0:
+                self.selection = None
+                prob = cv.calcBackProject([hsv], [0], self.hist, [0, 180], 1)
+                prob &= mask
+                term_crit = ( cv.TERM_CRITERIA_EPS | cv.TERM_CRITERIA_COUNT, 10, 1 )
+                _track_box, self.track_window = cv.CamShift(prob, self.track_window, term_crit)
+
+            trackingRect = np.array(self.track_window)
+            trackingRect[2] += trackingRect[0]
+            trackingRect[3] += trackingRect[1]
+
+            if intersectionRate(self.render.getCurrentRect(), trackingRect) < 0.4:
+                self.errors += 1
+
+            if framesCounter > self.framesNum:
+                break
+
+        self.assertLess(float(self.errors) / self.framesNum, 0.4)
+
+    def test_camshift(self):
+        self.prepareRender()
+        self.runTracker()
+
+
+if __name__ == '__main__':
+    NewOpenCVTests.bootstrap()