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remove goturn related code
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modules/tracking/include/opencv2/tracking/tracking_legacy.hpp

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@@ -286,45 +286,6 @@ class CV_EXPORTS_W TrackerKCF : public cv::legacy::Tracker
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virtual ~TrackerKCF() CV_OVERRIDE {}
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};
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#if 0 // legacy variant is not available
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/** @brief the GOTURN (Generic Object Tracking Using Regression Networks) tracker
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* GOTURN (@cite GOTURN) is kind of trackers based on Convolutional Neural Networks (CNN). While taking all advantages of CNN trackers,
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* GOTURN is much faster due to offline training without online fine-tuning nature.
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* GOTURN tracker addresses the problem of single target tracking: given a bounding box label of an object in the first frame of the video,
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* we track that object through the rest of the video. NOTE: Current method of GOTURN does not handle occlusions; however, it is fairly
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* robust to viewpoint changes, lighting changes, and deformations.
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* Inputs of GOTURN are two RGB patches representing Target and Search patches resized to 227x227.
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* Outputs of GOTURN are predicted bounding box coordinates, relative to Search patch coordinate system, in format X1,Y1,X2,Y2.
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* Original paper is here: <http://davheld.github.io/GOTURN/GOTURN.pdf>
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* As long as original authors implementation: <https://github.com/davheld/GOTURN#train-the-tracker>
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* Implementation of training algorithm is placed in separately here due to 3d-party dependencies:
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* <https://github.com/Auron-X/GOTURN_Training_Toolkit>
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* GOTURN architecture goturn.prototxt and trained model goturn.caffemodel are accessible on opencv_extra GitHub repository.
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*/
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class CV_EXPORTS_W TrackerGOTURN : public cv::legacy::Tracker
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{
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public:
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struct CV_EXPORTS Params
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{
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Params();
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void read(const FileNode& /*fn*/);
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void write(FileStorage& /*fs*/) const;
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String modelTxt;
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String modelBin;
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};
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/** @brief Constructor
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@param parameters GOTURN parameters TrackerGOTURN::Params
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*/
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static Ptr<legacy::TrackerGOTURN> create(const TrackerGOTURN::Params &parameters);
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CV_WRAP static Ptr<legacy::TrackerGOTURN> create();
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virtual ~TrackerGOTURN() CV_OVERRIDE {}
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};
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#endif
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/** @brief the MOSSE (Minimum Output Sum of Squared %Error) tracker
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The implementation is based on @cite MOSSE Visual Object Tracking using Adaptive Correlation Filters

modules/tracking/misc/java/test/TrackerCreateTest.java

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@@ -5,7 +5,6 @@
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import org.opencv.test.OpenCVTestCase;
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import org.opencv.video.Tracker;
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import org.opencv.video.TrackerGOTURN;
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import org.opencv.tracking.TrackerKCF;
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import org.opencv.video.TrackerMIL;
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@@ -16,16 +15,6 @@ protected void setUp() throws Exception {
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super.setUp();
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}
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public void testCreateTrackerGOTURN() {
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try {
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Tracker tracker = TrackerGOTURN.create();
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assert(tracker != null);
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} catch (CvException e) {
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// expected, model files may be missing
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}
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}
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public void testCreateTrackerKCF() {
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Tracker tracker = TrackerKCF.create();
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}

modules/tracking/misc/python/test/test_tracking_contrib.py

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@@ -11,18 +11,13 @@ def test_createTracker(self):
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t = cv.TrackerMIL_create()
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t = cv.TrackerKCF_create()
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try:
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t = cv.TrackerGOTURN_create()
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except cv.error as e:
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pass # may fail due to missing DL model files
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def test_createLegacyTracker(self):
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t = cv.legacy.TrackerBoosting_create()
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t = cv.legacy.TrackerMIL_create()
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t = cv.legacy.TrackerKCF_create()
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t = cv.legacy.TrackerMedianFlow_create()
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#t = cv.legacy.TrackerGOTURN_create()
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t = cv.legacy.TrackerMOSSE_create()
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t = cv.legacy.TrackerCSRT_create()
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modules/tracking/samples/goturnTracker.cpp

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This file was deleted.

modules/tracking/samples/samples_utility.hpp

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@@ -20,8 +20,6 @@ inline cv::Ptr<cv::Tracker> createTrackerByName(const std::string& name)
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tracker = legacy::upgradeTrackingAPI(legacy::TrackerMedianFlow::create());
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else if (name == "MIL")
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tracker = cv::TrackerMIL::create();
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else if (name == "GOTURN")
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tracker = cv::TrackerGOTURN::create();
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else if (name == "MOSSE")
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tracker = legacy::upgradeTrackingAPI(legacy::TrackerMOSSE::create());
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else if (name == "CSRT")
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tracker = legacy::TrackerMedianFlow::create();
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else if (name == "MIL")
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tracker = legacy::TrackerMIL::create();
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else if (name == "GOTURN")
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CV_Error(cv::Error::StsNotImplemented, "FIXIT: migration on new API is required");
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else if (name == "MOSSE")
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tracker = legacy::TrackerMOSSE::create();
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else if (name == "CSRT")

modules/tracking/samples/tracker.cpp

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@@ -22,7 +22,7 @@ static void help()
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"Example of <video_name> is in opencv_extra/testdata/cv/tracking/\n"
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"Call:\n"
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"./tracker <tracker_algorithm> <video_name> <start_frame> [<bounding_frame>]\n"
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"tracker_algorithm can be: MIL, BOOSTING, MEDIANFLOW, TLD, KCF, GOTURN, MOSSE.\n"
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"tracker_algorithm can be: MIL, BOOSTING, MEDIANFLOW, TLD, KCF, MOSSE.\n"
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<< endl;
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cout << "\n\nHot keys: \n"

modules/tracking/tutorials/tutorial_introduction_to_tracker.markdown

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@@ -50,7 +50,6 @@ Explanation
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+ MEDIANFLOW
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+ TLD
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+ KCF
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+ GOTURN
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+ MOSSE
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Each tracker algorithm has their own advantages and disadvantages, please refer the documentation of @ref cv::Tracker for more detailed information.

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