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/video/meanshift/camshift.py

@@ -0,0 +1,50 @@
+import numpy as np
+import cv2 as cv
+import argparse
+
+parser = argparse.ArgumentParser(description='This sample demonstrates the camshift algorithm. \
+                                              The example file can be downloaded from: \
+                                              https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4')
+parser.add_argument('image', type=str, help='path to image file')
+args = parser.parse_args()
+
+cap = cv.VideoCapture(args.image)
+
+# take first frame of the video
+ret,frame = cap.read()
+
+# setup initial location of window
+x, y, w, h = 300, 200, 100, 50 # simply hardcoded the values
+track_window = (x, y, w, h)
+
+# set up the ROI for tracking
+roi = frame[y:y+h, x:x+w]
+hsv_roi =  cv.cvtColor(roi, cv.COLOR_BGR2HSV)
+mask = cv.inRange(hsv_roi, np.array((0., 60.,32.)), np.array((180.,255.,255.)))
+roi_hist = cv.calcHist([hsv_roi],[0],mask,[180],[0,180])
+cv.normalize(roi_hist,roi_hist,0,255,cv.NORM_MINMAX)
+
+# Setup the termination criteria, either 10 iteration or move by atleast 1 pt
+term_crit = ( cv.TERM_CRITERIA_EPS | cv.TERM_CRITERIA_COUNT, 10, 1 )
+
+while(1):
+    ret, frame = cap.read()
+
+    if ret == True:
+        hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV)
+        dst = cv.calcBackProject([hsv],[0],roi_hist,[0,180],1)
+
+        # apply camshift to get the new location
+        ret, track_window = cv.CamShift(dst, track_window, term_crit)
+
+        # Draw it on image
+        pts = cv.boxPoints(ret)
+        pts = np.int0(pts)
+        img2 = cv.polylines(frame,[pts],True, 255,2)
+        cv.imshow('img2',img2)
+
+        k = cv.waitKey(30) & 0xff
+        if k == 27:
+            break
+    else:
+        break

3rdparty/opencv-4.5.4/samples/python/tutorial_code/video/meanshift/meanshift.py

@@ -0,0 +1,49 @@
+import numpy as np
+import cv2 as cv
+import argparse
+
+parser = argparse.ArgumentParser(description='This sample demonstrates the meanshift algorithm. \
+                                              The example file can be downloaded from: \
+                                              https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4')
+parser.add_argument('image', type=str, help='path to image file')
+args = parser.parse_args()
+
+cap = cv.VideoCapture(args.image)
+
+# take first frame of the video
+ret,frame = cap.read()
+
+# setup initial location of window
+x, y, w, h = 300, 200, 100, 50 # simply hardcoded the values
+track_window = (x, y, w, h)
+
+# set up the ROI for tracking
+roi = frame[y:y+h, x:x+w]
+hsv_roi =  cv.cvtColor(roi, cv.COLOR_BGR2HSV)
+mask = cv.inRange(hsv_roi, np.array((0., 60.,32.)), np.array((180.,255.,255.)))
+roi_hist = cv.calcHist([hsv_roi],[0],mask,[180],[0,180])
+cv.normalize(roi_hist,roi_hist,0,255,cv.NORM_MINMAX)
+
+# Setup the termination criteria, either 10 iteration or move by atleast 1 pt
+term_crit = ( cv.TERM_CRITERIA_EPS | cv.TERM_CRITERIA_COUNT, 10, 1 )
+
+while(1):
+    ret, frame = cap.read()
+
+    if ret == True:
+        hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV)
+        dst = cv.calcBackProject([hsv],[0],roi_hist,[0,180],1)
+
+        # apply meanshift to get the new location
+        ret, track_window = cv.meanShift(dst, track_window, term_crit)
+
+        # Draw it on image
+        x,y,w,h = track_window
+        img2 = cv.rectangle(frame, (x,y), (x+w,y+h), 255,2)
+        cv.imshow('img2',img2)
+
+        k = cv.waitKey(30) & 0xff
+        if k == 27:
+            break
+    else:
+        break