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// Targeted by JavaCPP version 1.5.2: DO NOT EDIT THIS FILE

package org.bytedeco.opencv.opencv_tracking;

import org.bytedeco.javacpp.annotation.Index;
import java.nio.*;
import org.bytedeco.javacpp.*;
import org.bytedeco.javacpp.annotation.*;

import static org.bytedeco.openblas.global.openblas_nolapack.*;
import static org.bytedeco.openblas.global.openblas.*;
import org.bytedeco.opencv.opencv_core.*;
import static org.bytedeco.opencv.global.opencv_core.*;
import org.bytedeco.opencv.opencv_imgproc.*;
import static org.bytedeco.opencv.global.opencv_imgproc.*;
import org.bytedeco.opencv.opencv_plot.*;
import static org.bytedeco.opencv.global.opencv_plot.*;
import static org.bytedeco.opencv.global.opencv_imgcodecs.*;
import org.bytedeco.opencv.opencv_videoio.*;
import static org.bytedeco.opencv.global.opencv_videoio.*;
import org.bytedeco.opencv.opencv_highgui.*;
import static org.bytedeco.opencv.global.opencv_highgui.*;
import org.bytedeco.opencv.opencv_flann.*;
import static org.bytedeco.opencv.global.opencv_flann.*;
import org.bytedeco.opencv.opencv_features2d.*;
import static org.bytedeco.opencv.global.opencv_features2d.*;
import org.bytedeco.opencv.opencv_calib3d.*;
import static org.bytedeco.opencv.global.opencv_calib3d.*;
import org.bytedeco.opencv.opencv_video.*;
import static org.bytedeco.opencv.global.opencv_video.*;
import org.bytedeco.opencv.opencv_dnn.*;
import static org.bytedeco.opencv.global.opencv_dnn.*;

import static org.bytedeco.opencv.global.opencv_tracking.*;


/** \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: 
 *  As long as original authors implementation: 
 *  Implementation of training algorithm is placed in separately here due to 3d-party dependencies:
 *  
 *  GOTURN architecture goturn.prototxt and trained model goturn.caffemodel are accessible on opencv_extra GitHub repository.
*/
@Namespace("cv") @Properties(inherit = org.bytedeco.opencv.presets.opencv_tracking.class)
public class TrackerGOTURN extends Tracker {
    static { Loader.load(); }
    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
    public TrackerGOTURN(Pointer p) { super(p); }

  public static class Params extends Pointer {
      static { Loader.load(); }
      /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
      public Params(Pointer p) { super(p); }
      /** Native array allocator. Access with {@link Pointer#position(long)}. */
      public Params(long size) { super((Pointer)null); allocateArray(size); }
      private native void allocateArray(long size);
      @Override public Params position(long position) {
          return (Params)super.position(position);
      }
  
    public Params() { super((Pointer)null); allocate(); }
    private native void allocate();
    public native void read(@Const @ByRef FileNode arg0);
    public native void write(@ByRef FileStorage arg0);
  }

  /** \brief Constructor
  @param parameters GOTURN parameters TrackerGOTURN::Params
  */
  public static native @Ptr TrackerGOTURN create(@Const @ByRef Params parameters);

  public static native @Ptr TrackerGOTURN create();
}