tracker_goturn.cpp
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// 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