remove goturn related code

modules/tracking/include/opencv2/tracking/tracking_legacy.hpp

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

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

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

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

@@ -11,10 +11,6 @@ class tracking_contrib_test(NewOpenCVTests):
 
         t = cv.TrackerMIL_create()
         t = cv.TrackerKCF_create()
-        try:
-            t = cv.TrackerGOTURN_create()
-        except cv.error as e:
-            pass  # may fail due to missing DL model files
 
     def test_createLegacyTracker(self):
 
@@ -22,7 +18,6 @@ class tracking_contrib_test(NewOpenCVTests):
         t = cv.legacy.TrackerMIL_create()
         t = cv.legacy.TrackerKCF_create()
         t = cv.legacy.TrackerMedianFlow_create()
-        #t = cv.legacy.TrackerGOTURN_create()
         t = cv.legacy.TrackerMOSSE_create()
         t = cv.legacy.TrackerCSRT_create()
 

modules/tracking/samples/goturnTracker.cpp

@@ -1,230 +0,0 @@
-/*M///////////////////////////////////////////////////////////////////////////////////////
-//
-//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
-//
-//  By downloading, copying, installing or using the software you agree to this license.
-//  If you do not agree to this license, do not download, install,
-//  copy or use the software.
-//
-//
-//                           License Agreement
-//                For Open Source Computer Vision Library
-//
-// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
-// Third party copyrights are property of their respective owners.
-//
-// Redistribution and use in source and binary forms, with or without modification,
-// are permitted provided that the following conditions are met:
-//
-//   * Redistribution's of source code must retain the above copyright notice,
-//     this list of conditions and the following disclaimer.
-//
-//   * Redistribution's in binary form must reproduce the above copyright notice,
-//     this list of conditions and the following disclaimer in the documentation
-//     and/or other materials provided with the distribution.
-//
-//   * The name of the copyright holders may not be used to endorse or promote products
-//     derived from this software without specific prior written permission.
-//
-// This software is provided by the copyright holders and contributors "as is" and
-// any express or implied warranties, including, but not limited to, the implied
-// warranties of merchantability and fitness for a particular purpose are disclaimed.
-// In no event shall the Intel Corporation or contributors be liable for any direct,
-// indirect, incidental, special, exemplary, or consequential damages
-// (including, but not limited to, procurement of substitute goods or services;
-// loss of use, data, or profits; or business interruption) however caused
-// and on any theory of liability, whether in contract, strict liability,
-// or tort (including negligence or otherwise) arising in any way out of
-// the use of this software, even if advised of the possibility of such damage.
-//
-//M*/
-
-//Demo of GOTURN tracker
-//In order to use GOTURN tracker, GOTURN architecture goturn.prototxt and goturn.caffemodel are required to exist in root folder.
-//There are 2 ways to get caffemodel:
-//1 - Train you own GOTURN model using <https://github.com/Auron-X/GOTURN_Training_Toolkit>
-//2 - Download pretrained caffemodel from <https://github.com/opencv/opencv_extra>
-
-#include "opencv2/opencv_modules.hpp"
-#if defined(HAVE_OPENCV_DNN) && defined(HAVE_OPENCV_DATASETS)
-
-#include "opencv2/datasets/track_alov.hpp"
-#include <opencv2/core/utility.hpp>
-#include <opencv2/imgproc.hpp>
-#include <opencv2/tracking.hpp>
-#include <opencv2/videoio.hpp>
-#include <opencv2/highgui.hpp>
-#include <iostream>
-
-using namespace std;
-using namespace cv;
-using namespace cv::datasets;
-
-#define NUM_TEST_FRAMES 1000
-
-static Mat image;
-static bool paused;
-static bool selectObjects = false;
-static bool startSelection = false;
-static Rect boundingBox;
-
-static const char* keys =
-{ "{@dataset_path     || Dataset path   }"
-  "{@dataset_id      |1| Dataset ID     }"
-};
-
-static void onMouse(int event, int x, int y, int, void*)
-{
-    if (!selectObjects)
-    {
-        switch (event)
-        {
-        case EVENT_LBUTTONDOWN:
-            //set origin of the bounding box
-            startSelection = true;
-            boundingBox.x = x;
-            boundingBox.y = y;
-            boundingBox.width = boundingBox.height = 0;
-            break;
-        case EVENT_LBUTTONUP:
-            //sei with and height of the bounding box
-            boundingBox.width = std::abs(x - boundingBox.x);
-            boundingBox.height = std::abs(y - boundingBox.y);
-            paused = false;
-            selectObjects = true;
-            startSelection = false;
-            break;
-        case EVENT_MOUSEMOVE:
-
-            if (startSelection && !selectObjects)
-            {
-                //draw the bounding box
-                Mat currentFrame;
-                image.copyTo(currentFrame);
-                rectangle(currentFrame, Point((int)boundingBox.x, (int)boundingBox.y), Point(x, y), Scalar(255, 0, 0), 2, 1);
-                imshow("GOTURN Tracking", currentFrame);
-            }
-            break;
-        }
-    }
-}
-
-static void help()
-{
-    cout << "\nThis example is a simple demo of GOTURN tracking on ALOV300++ dataset"
-        "ALOV dataset contains videos with ID range: 1~314\n"
-        "-- pause video [p] and draw a bounding boxes around the targets to start the tracker\n"
-        "Example:\n"
-        "./goturnTracker <dataset_path> <dataset_id>\n"
-        << endl;
-
-    cout << "\n\nHot keys: \n"
-        "\tq - quit the program\n"
-        "\tp - pause video\n";
-}
-
-int main(int argc, char *argv[])
-{
-    CommandLineParser parser(argc, argv, keys);
-    string datasetRootPath = parser.get<string>(0);
-    int datasetID = parser.get<int>(1);
-
-    if (datasetRootPath.empty())
-    {
-        help();
-        return -1;
-    }
-
-    Mat frame;
-    paused = false;
-    namedWindow("GOTURN Tracking", 0);
-    setMouseCallback("GOTURN Tracking", onMouse, 0);
-
-    //Create GOTURN tracker
-    auto tracker = TrackerGOTURN::create();
-
-    //Load and init full ALOV300++ dataset with a given datasetID, as alternative you can use loadAnnotatedOnly(..)
-    //to load only frames with labelled ground truth ~ every 5-th frame
-    Ptr<cv::datasets::TRACK_alov> dataset = TRACK_alov::create();
-    dataset->load(datasetRootPath);
-    dataset->initDataset(datasetID);
-    //Read first frame
-    dataset->getNextFrame(frame);
-    if (frame.empty())
-    {
-        cout << "invalid dataset: " << datasetRootPath << endl;
-        return -2;
-    }
-
-    frame.copyTo(image);
-    rectangle(image, boundingBox, Scalar(255, 0, 0), 2, 1);
-    imshow("GOTURN Tracking", image);
-
-    bool initialized = false;
-    paused = true;
-    int frameCounter = 0;
-
-    //Time measurment
-    int64 e3 = getTickCount();
-
-    for (;;)
-    {
-        if (!paused)
-        {
-            //Time measurment
-            int64 e1 = getTickCount();
-            if (initialized){
-                if (!dataset->getNextFrame(frame))
-                    break;
-                frame.copyTo(image);
-            }
-
-            if (!initialized && selectObjects)
-            {
-                //Initialize the tracker and add targets
-                tracker->init(frame, boundingBox);
-                rectangle(frame, boundingBox, Scalar(0, 0, 255), 2, 1);
-                initialized = true;
-            }
-            else if (initialized)
-            {
-                //Update all targets
-                if (tracker->update(frame, boundingBox))
-                {
-                    rectangle(frame, boundingBox, Scalar(0, 0, 255), 2, 1);
-                }
-            }
-            imshow("GOTURN Tracking", frame);
-            frameCounter++;
-            //Time measurment
-            int64 e2 = getTickCount();
-            double t1 = (e2 - e1) / getTickFrequency();
-            cout << frameCounter << "\tframe :  " << t1 * 1000.0 << "ms" << endl;
-        }
-
-        char c = (char)waitKey(2);
-        if (c == 'q')
-            break;
-        if (c == 'p')
-            paused = !paused;
-    }
-
-    //Time measurment
-    int64 e4 = getTickCount();
-    double t2 = (e4 - e3) / getTickFrequency();
-    cout << "Average Time for Frame:  " << t2 * 1000.0 / frameCounter << "ms" << endl;
-    cout << "Average FPS:  " << 1.0 / t2*frameCounter << endl;
-
-
-    waitKey(0);
-
-    return 0;
-}
-
-#else // ! HAVE_OPENCV_DNN && HAVE_OPENCV_DATASETS
-#include <opencv2/core.hpp>
-int main() {
-    CV_Error(cv::Error::StsNotImplemented , "this sample needs to be built with opencv_datasets and opencv_dnn !");
-    return -1;
-}
-#endif

modules/tracking/samples/samples_utility.hpp

@@ -20,8 +20,6 @@ inline cv::Ptr<cv::Tracker> createTrackerByName(const std::string& name)
         tracker = legacy::upgradeTrackingAPI(legacy::TrackerMedianFlow::create());
     else if (name == "MIL")
         tracker = cv::TrackerMIL::create();
-    else if (name == "GOTURN")
-        tracker = cv::TrackerGOTURN::create();
     else if (name == "MOSSE")
         tracker = legacy::upgradeTrackingAPI(legacy::TrackerMOSSE::create());
     else if (name == "CSRT")
@@ -48,8 +46,6 @@ inline cv::Ptr<cv::legacy::Tracker> createTrackerByName_legacy(const std::string
         tracker = legacy::TrackerMedianFlow::create();
     else if (name == "MIL")
         tracker = legacy::TrackerMIL::create();
-    else if (name == "GOTURN")
-        CV_Error(cv::Error::StsNotImplemented, "FIXIT: migration on new API is required");
     else if (name == "MOSSE")
         tracker = legacy::TrackerMOSSE::create();
     else if (name == "CSRT")

modules/tracking/samples/tracker.cpp

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

modules/tracking/tutorials/tutorial_introduction_to_tracker.markdown

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