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/cpp/tutorial_code/video/bg_sub.cpp

@@ -0,0 +1,87 @@
+/**
+ * @file bg_sub.cpp
+ * @brief Background subtraction tutorial sample code
+ * @author Domenico D. Bloisi
+ */
+
+#include <iostream>
+#include <sstream>
+#include <opencv2/imgcodecs.hpp>
+#include <opencv2/imgproc.hpp>
+#include <opencv2/videoio.hpp>
+#include <opencv2/highgui.hpp>
+#include <opencv2/video.hpp>
+
+using namespace cv;
+using namespace std;
+
+const char* params
+    = "{ help h         |           | Print usage }"
+      "{ input          | vtest.avi | Path to a video or a sequence of image }"
+      "{ algo           | MOG2      | Background subtraction method (KNN, MOG2) }";
+
+int main(int argc, char* argv[])
+{
+    CommandLineParser parser(argc, argv, params);
+    parser.about( "This program shows how to use background subtraction methods provided by "
+                  " OpenCV. You can process both videos and images.\n" );
+    if (parser.has("help"))
+    {
+        //print help information
+        parser.printMessage();
+    }
+
+    //! [create]
+    //create Background Subtractor objects
+    Ptr<BackgroundSubtractor> pBackSub;
+    if (parser.get<String>("algo") == "MOG2")
+        pBackSub = createBackgroundSubtractorMOG2();
+    else
+        pBackSub = createBackgroundSubtractorKNN();
+    //! [create]
+
+    //! [capture]
+    VideoCapture capture( samples::findFile( parser.get<String>("input") ) );
+    if (!capture.isOpened()){
+        //error in opening the video input
+        cerr << "Unable to open: " << parser.get<String>("input") << endl;
+        return 0;
+    }
+    //! [capture]
+
+    Mat frame, fgMask;
+    while (true) {
+        capture >> frame;
+        if (frame.empty())
+            break;
+
+        //! [apply]
+        //update the background model
+        pBackSub->apply(frame, fgMask);
+        //! [apply]
+
+        //! [display_frame_number]
+        //get the frame number and write it on the current frame
+        rectangle(frame, cv::Point(10, 2), cv::Point(100,20),
+                  cv::Scalar(255,255,255), -1);
+        stringstream ss;
+        ss << capture.get(CAP_PROP_POS_FRAMES);
+        string frameNumberString = ss.str();
+        putText(frame, frameNumberString.c_str(), cv::Point(15, 15),
+                FONT_HERSHEY_SIMPLEX, 0.5 , cv::Scalar(0,0,0));
+        //! [display_frame_number]
+
+        //! [show]
+        //show the current frame and the fg masks
+        imshow("Frame", frame);
+        imshow("FG Mask", fgMask);
+        //! [show]
+
+        //get the input from the keyboard
+        int keyboard = waitKey(30);
+        if (keyboard == 'q' || keyboard == 27)
+            break;
+    }
+
+    return 0;
+}

3rdparty/opencv-4.5.4/samples/cpp/tutorial_code/video/meanshift/camshift.cpp

@@ -0,0 +1,86 @@
+#include <iostream>
+#include <opencv2/imgcodecs.hpp>
+#include <opencv2/imgproc.hpp>
+#include <opencv2/videoio.hpp>
+#include <opencv2/highgui.hpp>
+#include <opencv2/video.hpp>
+
+using namespace cv;
+using namespace std;
+
+int main(int argc, char **argv)
+{
+    const string about =
+        "This sample demonstrates the camshift algorithm.\n"
+        "The example file can be downloaded from:\n"
+        "  https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4";
+    const string keys =
+        "{ h help |      | print this help message }"
+        "{ @image |<none>| path to image file }";
+    CommandLineParser parser(argc, argv, keys);
+    parser.about(about);
+    if (parser.has("help"))
+    {
+        parser.printMessage();
+        return 0;
+    }
+    string filename = parser.get<string>("@image");
+    if (!parser.check())
+    {
+        parser.printErrors();
+        return 0;
+    }
+
+    VideoCapture capture(filename);
+    if (!capture.isOpened()){
+        //error in opening the video input
+        cerr << "Unable to open file!" << endl;
+        return 0;
+    }
+
+    Mat frame, roi, hsv_roi, mask;
+    // take first frame of the video
+    capture >> frame;
+
+    // setup initial location of window
+    Rect track_window(300, 200, 100, 50); // simply hardcoded the values
+
+    // set up the ROI for tracking
+    roi = frame(track_window);
+    cvtColor(roi, hsv_roi, COLOR_BGR2HSV);
+    inRange(hsv_roi, Scalar(0, 60, 32), Scalar(180, 255, 255), mask);
+
+    float range_[] = {0, 180};
+    const float* range[] = {range_};
+    Mat roi_hist;
+    int histSize[] = {180};
+    int channels[] = {0};
+    calcHist(&hsv_roi, 1, channels, mask, roi_hist, 1, histSize, range);
+    normalize(roi_hist, roi_hist, 0, 255, NORM_MINMAX);
+
+    // Setup the termination criteria, either 10 iteration or move by atleast 1 pt
+    TermCriteria term_crit(TermCriteria::EPS | TermCriteria::COUNT, 10, 1);
+
+    while(true){
+        Mat hsv, dst;
+        capture >> frame;
+        if (frame.empty())
+            break;
+        cvtColor(frame, hsv, COLOR_BGR2HSV);
+        calcBackProject(&hsv, 1, channels, roi_hist, dst, range);
+
+        // apply camshift to get the new location
+        RotatedRect rot_rect = CamShift(dst, track_window, term_crit);
+
+        // Draw it on image
+        Point2f points[4];
+        rot_rect.points(points);
+        for (int i = 0; i < 4; i++)
+            line(frame, points[i], points[(i+1)%4], 255, 2);
+        imshow("img2", frame);
+
+        int keyboard = waitKey(30);
+        if (keyboard == 'q' || keyboard == 27)
+            break;
+    }
+}

3rdparty/opencv-4.5.4/samples/cpp/tutorial_code/video/meanshift/meanshift.cpp

@@ -0,0 +1,83 @@
+#include <iostream>
+#include <opencv2/imgcodecs.hpp>
+#include <opencv2/imgproc.hpp>
+#include <opencv2/videoio.hpp>
+#include <opencv2/highgui.hpp>
+#include <opencv2/video.hpp>
+
+using namespace cv;
+using namespace std;
+
+int main(int argc, char **argv)
+{
+    const string about =
+        "This sample demonstrates the meanshift algorithm.\n"
+        "The example file can be downloaded from:\n"
+        "  https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4";
+    const string keys =
+        "{ h help |      | print this help message }"
+        "{ @image |<none>| path to image file }";
+    CommandLineParser parser(argc, argv, keys);
+    parser.about(about);
+    if (parser.has("help"))
+    {
+        parser.printMessage();
+        return 0;
+    }
+    string filename = parser.get<string>("@image");
+    if (!parser.check())
+    {
+        parser.printErrors();
+        return 0;
+    }
+
+    VideoCapture capture(filename);
+    if (!capture.isOpened()){
+        //error in opening the video input
+        cerr << "Unable to open file!" << endl;
+        return 0;
+    }
+
+    Mat frame, roi, hsv_roi, mask;
+    // take first frame of the video
+    capture >> frame;
+
+    // setup initial location of window
+    Rect track_window(300, 200, 100, 50); // simply hardcoded the values
+
+    // set up the ROI for tracking
+    roi = frame(track_window);
+    cvtColor(roi, hsv_roi, COLOR_BGR2HSV);
+    inRange(hsv_roi, Scalar(0, 60, 32), Scalar(180, 255, 255), mask);
+
+    float range_[] = {0, 180};
+    const float* range[] = {range_};
+    Mat roi_hist;
+    int histSize[] = {180};
+    int channels[] = {0};
+    calcHist(&hsv_roi, 1, channels, mask, roi_hist, 1, histSize, range);
+    normalize(roi_hist, roi_hist, 0, 255, NORM_MINMAX);
+
+    // Setup the termination criteria, either 10 iteration or move by atleast 1 pt
+    TermCriteria term_crit(TermCriteria::EPS | TermCriteria::COUNT, 10, 1);
+
+    while(true){
+        Mat hsv, dst;
+        capture >> frame;
+        if (frame.empty())
+            break;
+        cvtColor(frame, hsv, COLOR_BGR2HSV);
+        calcBackProject(&hsv, 1, channels, roi_hist, dst, range);
+
+        // apply meanshift to get the new location
+        meanShift(dst, track_window, term_crit);
+
+        // Draw it on image
+        rectangle(frame, track_window, 255, 2);
+        imshow("img2", frame);
+
+        int keyboard = waitKey(30);
+        if (keyboard == 'q' || keyboard == 27)
+            break;
+    }
+}

3rdparty/opencv-4.5.4/samples/cpp/tutorial_code/video/optical_flow/optical_flow.cpp

@@ -0,0 +1,101 @@
+#include <iostream>
+#include <opencv2/core.hpp>
+#include <opencv2/highgui.hpp>
+#include <opencv2/imgproc.hpp>
+#include <opencv2/videoio.hpp>
+#include <opencv2/video.hpp>
+
+using namespace cv;
+using namespace std;
+
+int main(int argc, char **argv)
+{
+    const string about =
+        "This sample demonstrates Lucas-Kanade Optical Flow calculation.\n"
+        "The example file can be downloaded from:\n"
+        "  https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4";
+    const string keys =
+        "{ h help |      | print this help message }"
+        "{ @image | vtest.avi | path to image file }";
+    CommandLineParser parser(argc, argv, keys);
+    parser.about(about);
+    if (parser.has("help"))
+    {
+        parser.printMessage();
+        return 0;
+    }
+    string filename = samples::findFile(parser.get<string>("@image"));
+    if (!parser.check())
+    {
+        parser.printErrors();
+        return 0;
+    }
+
+    VideoCapture capture(filename);
+    if (!capture.isOpened()){
+        //error in opening the video input
+        cerr << "Unable to open file!" << endl;
+        return 0;
+    }
+
+    // Create some random colors
+    vector<Scalar> colors;
+    RNG rng;
+    for(int i = 0; i < 100; i++)
+    {
+        int r = rng.uniform(0, 256);
+        int g = rng.uniform(0, 256);
+        int b = rng.uniform(0, 256);
+        colors.push_back(Scalar(r,g,b));
+    }
+
+    Mat old_frame, old_gray;
+    vector<Point2f> p0, p1;
+
+    // Take first frame and find corners in it
+    capture >> old_frame;
+    cvtColor(old_frame, old_gray, COLOR_BGR2GRAY);
+    goodFeaturesToTrack(old_gray, p0, 100, 0.3, 7, Mat(), 7, false, 0.04);
+
+    // Create a mask image for drawing purposes
+    Mat mask = Mat::zeros(old_frame.size(), old_frame.type());
+
+    while(true){
+        Mat frame, frame_gray;
+
+        capture >> frame;
+        if (frame.empty())
+            break;
+        cvtColor(frame, frame_gray, COLOR_BGR2GRAY);
+
+        // calculate optical flow
+        vector<uchar> status;
+        vector<float> err;
+        TermCriteria criteria = TermCriteria((TermCriteria::COUNT) + (TermCriteria::EPS), 10, 0.03);
+        calcOpticalFlowPyrLK(old_gray, frame_gray, p0, p1, status, err, Size(15,15), 2, criteria);
+
+        vector<Point2f> good_new;
+        for(uint i = 0; i < p0.size(); i++)
+        {
+            // Select good points
+            if(status[i] == 1) {
+                good_new.push_back(p1[i]);
+                // draw the tracks
+                line(mask,p1[i], p0[i], colors[i], 2);
+                circle(frame, p1[i], 5, colors[i], -1);
+            }
+        }
+        Mat img;
+        add(frame, mask, img);
+
+        imshow("Frame", img);
+
+        int keyboard = waitKey(30);
+        if (keyboard == 'q' || keyboard == 27)
+            break;
+
+        // Now update the previous frame and previous points
+        old_gray = frame_gray.clone();
+        p0 = good_new;
+    }
+}

3rdparty/opencv-4.5.4/samples/cpp/tutorial_code/video/optical_flow/optical_flow_dense.cpp

@@ -0,0 +1,59 @@
+#include <iostream>
+#include <opencv2/core.hpp>
+#include <opencv2/highgui.hpp>
+#include <opencv2/imgproc.hpp>
+#include <opencv2/videoio.hpp>
+#include <opencv2/video.hpp>
+
+using namespace cv;
+using namespace std;
+
+int main()
+{
+    VideoCapture capture(samples::findFile("vtest.avi"));
+    if (!capture.isOpened()){
+        //error in opening the video input
+        cerr << "Unable to open file!" << endl;
+        return 0;
+    }
+
+    Mat frame1, prvs;
+    capture >> frame1;
+    cvtColor(frame1, prvs, COLOR_BGR2GRAY);
+
+    while(true){
+        Mat frame2, next;
+        capture >> frame2;
+        if (frame2.empty())
+            break;
+        cvtColor(frame2, next, COLOR_BGR2GRAY);
+
+        Mat flow(prvs.size(), CV_32FC2);
+        calcOpticalFlowFarneback(prvs, next, flow, 0.5, 3, 15, 3, 5, 1.2, 0);
+
+        // visualization
+        Mat flow_parts[2];
+        split(flow, flow_parts);
+        Mat magnitude, angle, magn_norm;
+        cartToPolar(flow_parts[0], flow_parts[1], magnitude, angle, true);
+        normalize(magnitude, magn_norm, 0.0f, 1.0f, NORM_MINMAX);
+        angle *= ((1.f / 360.f) * (180.f / 255.f));
+
+        //build hsv image
+        Mat _hsv[3], hsv, hsv8, bgr;
+        _hsv[0] = angle;
+        _hsv[1] = Mat::ones(angle.size(), CV_32F);
+        _hsv[2] = magn_norm;
+        merge(_hsv, 3, hsv);
+        hsv.convertTo(hsv8, CV_8U, 255.0);
+        cvtColor(hsv8, bgr, COLOR_HSV2BGR);
+
+        imshow("frame2", bgr);
+
+        int keyboard = waitKey(30);
+        if (keyboard == 'q' || keyboard == 27)
+            break;
+
+        prvs = next;
+    }
+}