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/video/src/tracking/tracker_goturn.cpp

@@ -0,0 +1,140 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#include "../precomp.hpp"
+
+#ifdef HAVE_OPENCV_DNN
+#include "opencv2/dnn.hpp"
+#endif
+
+namespace cv {
+
+TrackerGOTURN::TrackerGOTURN()
+{
+    // nothing
+}
+
+TrackerGOTURN::~TrackerGOTURN()
+{
+    // nothing
+}
+
+TrackerGOTURN::Params::Params()
+{
+    modelTxt = "goturn.prototxt";
+    modelBin = "goturn.caffemodel";
+}
+
+#ifdef HAVE_OPENCV_DNN
+
+class TrackerGOTURNImpl : public TrackerGOTURN
+{
+public:
+    TrackerGOTURNImpl(const TrackerGOTURN::Params& parameters)
+        : params(parameters)
+    {
+        // Load GOTURN architecture from *.prototxt and pretrained weights from *.caffemodel
+        net = dnn::readNetFromCaffe(params.modelTxt, params.modelBin);
+        CV_Assert(!net.empty());
+    }
+
+    void init(InputArray image, const Rect& boundingBox) CV_OVERRIDE;
+    bool update(InputArray image, Rect& boundingBox) CV_OVERRIDE;
+
+    void setBoudingBox(Rect boundingBox)
+    {
+        if (image_.empty())
+            CV_Error(Error::StsInternal, "Set image first");
+        boundingBox_ = boundingBox & Rect(Point(0, 0), image_.size());
+    }
+
+    TrackerGOTURN::Params params;
+
+    dnn::Net net;
+    Rect boundingBox_;
+    Mat image_;
+};
+
+void TrackerGOTURNImpl::init(InputArray image, const Rect& boundingBox)
+{
+    image_ = image.getMat().clone();
+    setBoudingBox(boundingBox);
+}
+
+bool TrackerGOTURNImpl::update(InputArray image, Rect& boundingBox)
+{
+    int INPUT_SIZE = 227;
+    //Using prevFrame & prevBB from model and curFrame GOTURN calculating curBB
+    InputArray curFrame = image;
+    Mat prevFrame = image_;
+    Rect2d prevBB = boundingBox_;
+    Rect curBB;
+
+    float padTargetPatch = 2.0;
+    Rect2f searchPatchRect, targetPatchRect;
+    Point2f currCenter, prevCenter;
+    Mat prevFramePadded, curFramePadded;
+    Mat searchPatch, targetPatch;
+
+    prevCenter.x = (float)(prevBB.x + prevBB.width / 2);
+    prevCenter.y = (float)(prevBB.y + prevBB.height / 2);
+
+    targetPatchRect.width = (float)(prevBB.width * padTargetPatch);
+    targetPatchRect.height = (float)(prevBB.height * padTargetPatch);
+    targetPatchRect.x = (float)(prevCenter.x - prevBB.width * padTargetPatch / 2.0 + targetPatchRect.width);
+    targetPatchRect.y = (float)(prevCenter.y - prevBB.height * padTargetPatch / 2.0 + targetPatchRect.height);
+
+    targetPatchRect.width = std::min(targetPatchRect.width, (float)prevFrame.cols);
+    targetPatchRect.height = std::min(targetPatchRect.height, (float)prevFrame.rows);
+    targetPatchRect.x = std::max(-prevFrame.cols * 0.5f, std::min(targetPatchRect.x, prevFrame.cols * 1.5f));
+    targetPatchRect.y = std::max(-prevFrame.rows * 0.5f, std::min(targetPatchRect.y, prevFrame.rows * 1.5f));
+
+    copyMakeBorder(prevFrame, prevFramePadded, (int)targetPatchRect.height, (int)targetPatchRect.height, (int)targetPatchRect.width, (int)targetPatchRect.width, BORDER_REPLICATE);
+    targetPatch = prevFramePadded(targetPatchRect).clone();
+
+    copyMakeBorder(curFrame, curFramePadded, (int)targetPatchRect.height, (int)targetPatchRect.height, (int)targetPatchRect.width, (int)targetPatchRect.width, BORDER_REPLICATE);
+    searchPatch = curFramePadded(targetPatchRect).clone();
+
+    // Preprocess
+    // Resize
+    resize(targetPatch, targetPatch, Size(INPUT_SIZE, INPUT_SIZE), 0, 0, INTER_LINEAR_EXACT);
+    resize(searchPatch, searchPatch, Size(INPUT_SIZE, INPUT_SIZE), 0, 0, INTER_LINEAR_EXACT);
+
+    // Convert to Float type and subtract mean
+    Mat targetBlob = dnn::blobFromImage(targetPatch, 1.0f, Size(), Scalar::all(128), false);
+    Mat searchBlob = dnn::blobFromImage(searchPatch, 1.0f, Size(), Scalar::all(128), false);
+
+    net.setInput(targetBlob, "data1");
+    net.setInput(searchBlob, "data2");
+
+    Mat resMat = net.forward("scale").reshape(1, 1);
+
+    curBB.x = cvRound(targetPatchRect.x + (resMat.at<float>(0) * targetPatchRect.width / INPUT_SIZE) - targetPatchRect.width);
+    curBB.y = cvRound(targetPatchRect.y + (resMat.at<float>(1) * targetPatchRect.height / INPUT_SIZE) - targetPatchRect.height);
+    curBB.width = cvRound((resMat.at<float>(2) - resMat.at<float>(0)) * targetPatchRect.width / INPUT_SIZE);
+    curBB.height = cvRound((resMat.at<float>(3) - resMat.at<float>(1)) * targetPatchRect.height / INPUT_SIZE);
+
+    // Predicted BB
+    boundingBox = curBB & Rect(Point(0, 0), image_.size());
+
+    // Set new model image and BB from current frame
+    image_ = image.getMat().clone();
+    setBoudingBox(curBB);
+    return true;
+}
+
+Ptr<TrackerGOTURN> TrackerGOTURN::create(const TrackerGOTURN::Params& parameters)
+{
+    return makePtr<TrackerGOTURNImpl>(parameters);
+}
+
+#else  // OPENCV_HAVE_DNN
+Ptr<TrackerGOTURN> TrackerGOTURN::create(const TrackerGOTURN::Params& parameters)
+{
+    (void)(parameters);
+    CV_Error(cv::Error::StsNotImplemented, "to use GOTURN, the tracking module needs to be built with opencv_dnn !");
+}
+#endif  // OPENCV_HAVE_DNN
+
+}  // namespace cv