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Merge pull request #4 from Auron-X/TLD/VOT-2015-Dataset-Support
Tld/vot 2015 dataset support
2 parents c2525ae + 94447d5 commit c11abeb

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12 files changed

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‎modules/tracking/include/opencv2/tracking/tldDataset.hpp‎

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@@ -48,7 +48,7 @@ namespace cv
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{
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namespace tld
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{
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CV_EXPORTS cv::Rect2d tld_InitDataset(int datasetInd, const char* rootPath = "TLD_dataset");
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CV_EXPORTS cv::Rect2d tld_InitDataset(int videoInd, const char* rootPath = "TLD_dataset", int datasetInd = 0);
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CV_EXPORTS cv::Mat tld_getNextDatasetFrame();
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}
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}

‎modules/tracking/include/opencv2/tracking/tracker.hpp‎

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@@ -49,6 +49,7 @@
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#include "onlineBoosting.hpp"
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#include <iostream>
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#define BOILERPLATE_CODE(name,classname) \
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static Ptr<classname> createTracker(const classname::Params &parameters=classname::Params());\
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virtual ~classname(){};
@@ -564,6 +565,11 @@ class CV_EXPORTS_W Tracker : public virtual Algorithm
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virtual void read( const FileNode& fn )=0;
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virtual void write( FileStorage& fs ) const=0;
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Ptr<TrackerModel> getModel()
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{
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return model;
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}
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protected:
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virtual bool initImpl( const Mat& image, const Rect2d& boundingBox ) = 0;
@@ -576,6 +582,7 @@ class CV_EXPORTS_W Tracker : public virtual Algorithm
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Ptr<TrackerModel> model;
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};
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/************************************ Specific TrackerStateEstimator Classes ************************************/
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/** @brief TrackerStateEstimator based on Boosting
@@ -1243,6 +1250,85 @@ class CV_EXPORTS_W TrackerKCF : public Tracker
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BOILERPLATE_CODE("KCF",TrackerKCF);
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};
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/************************************ Multi-Tracker Classes ************************************/
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/** @brief Base abstract class for the long-term Multi Object Trackers:
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@sa Tracker, MultiTrackerTLD
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*/
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class CV_EXPORTS_W MultiTracker
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{
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public:
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/** @brief Constructor for Multitracker
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*/
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MultiTracker()
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{
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targetNum = 0;
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}
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/** @brief Add a new target to a tracking-list and initialize the tracker with a know bounding box that surrounding the target
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@param image The initial frame
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@param boundingBox The initial boundig box of target
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@param tracker_algorithm_name Multi-tracker algorithm name
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@return True if new target initialization went succesfully, false otherwise
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*/
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bool addTarget(const Mat& image, const Rect2d& boundingBox, char* tracker_algorithm_name);
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/** @brief Update all trackers from the tracking-list, find a new most likely bounding boxes for the targets
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@param image The current frame
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@return True means that all targets were located and false means that tracker couldn't locate one of the targets in
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current frame. Note, that latter *does not* imply that tracker has failed, maybe target is indeed
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missing from the frame (say, out of sight)
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*/
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bool update(const Mat& image);
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/** @brief Current number of targets in tracking-list
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*/
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int targetNum;
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/** @brief Trackers list for Multi-Object-Tracker
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*/
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std::vector <Ptr<Tracker> > trackers;
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/** @brief Bounding Boxes list for Multi-Object-Tracker
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*/
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std::vector <Rect2d> boundingBoxes;
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/** @brief List of randomly generated colors for bounding boxes display
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*/
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std::vector<Scalar> colors;
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};
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/** @brief Multi Object Tracker for TLD. TLD is a novel tracking framework that explicitly decomposes
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the long-term tracking task into tracking, learning and detection.
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The tracker follows the object from frame to frame. The detector localizes all appearances that
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have been observed so far and corrects the tracker if necessary. The learning estimates detector’s
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errors and updates it to avoid these errors in the future. The implementation is based on @cite TLD .
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The Median Flow algorithm (see cv::TrackerMedianFlow) was chosen as a tracking component in this
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implementation, following authors. Tracker is supposed to be able to handle rapid motions, partial
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occlusions, object absence etc.
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@sa Tracker, MultiTracker, TrackerTLD
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*/
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class CV_EXPORTS_W MultiTrackerTLD : public MultiTracker
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{
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public:
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/** @brief Update all trackers from the tracking-list, find a new most likely bounding boxes for the targets by
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optimized update method using some techniques to speedup calculations specifically for MO TLD. The only limitation
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is that all target bounding boxes should have approximately same aspect ratios. Speed boost is around 20%
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@param image The current frame.
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@return True means that all targets were located and false means that tracker couldn't locate one of the targets in
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current frame. Note, that latter *does not* imply that tracker has failed, maybe target is indeed
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missing from the frame (say, out of sight)
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*/
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bool update_opt(const Mat& image);
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};
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//! @}
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} /* namespace cv */

‎modules/tracking/samples/multiTracker_test.cpp‎

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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include <opencv2/core/utility.hpp>
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#include <opencv2/tracking.hpp>
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#include <opencv2/videoio.hpp>
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#include <opencv2/highgui.hpp>
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#include <iostream>
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using namespace std;
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using namespace cv;
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#define NUM_TEST_FRAMES 100
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#define TEST_VIDEO_INDEX 15 //TLD Dataset Video Index from 1-10 for TLD and 1-60 for VOT
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//#define RECORD_VIDEO_FLG
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static Mat image;
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static bool paused;
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static bool selectObject = false;
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static bool startSelection = false;
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Rect2d boundingBox;
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static void onMouse(int event, int x, int y, int, void*)
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{
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if (!selectObject)
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{
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switch (event)
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{
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case EVENT_LBUTTONDOWN:
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//set origin of the bounding box
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startSelection = true;
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boundingBox.x = x;
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boundingBox.y = y;
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boundingBox.width = boundingBox.height = 0;
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break;
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case EVENT_LBUTTONUP:
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//sei with and height of the bounding box
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boundingBox.width = std::abs(x - boundingBox.x);
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boundingBox.height = std::abs(y - boundingBox.y);
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paused = false;
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selectObject = true;
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break;
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case EVENT_MOUSEMOVE:
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83+
if (startSelection && !selectObject)
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{
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//draw the bounding box
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Mat currentFrame;
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image.copyTo(currentFrame);
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rectangle(currentFrame, Point((int)boundingBox.x, (int)boundingBox.y), Point(x, y), Scalar(255, 0, 0), 2, 1);
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imshow("Tracking API", currentFrame);
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}
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break;
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}
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}
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}
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int main()
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{
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//
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// "MIL", "BOOSTING", "MEDIANFLOW", "TLD"
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//
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char* tracker_algorithm_name = (char*)"TLD";
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Mat frame;
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paused = false;
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namedWindow("Tracking API", 0);
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setMouseCallback("Tracking API", onMouse, 0);
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MultiTrackerTLD mt;
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//Get the first frame
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////Open the capture
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// VideoCapture cap(0);
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// if( !cap.isOpened() )
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// {
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// cout << "Video stream error";
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// return;
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// }
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//cap >> frame;
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//From TLD dataset
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selectObject = true;
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Rect2d boundingBox1 = tld::tld_InitDataset(TEST_VIDEO_INDEX, "D:/opencv/VOT 2015", 1);
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Rect2d boundingBox2(470, 490, 50, 120);
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frame = tld::tld_getNextDatasetFrame();
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frame.copyTo(image);
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// Setup output video
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#ifdef RECORD_VIDEO_FLG
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String outputFilename = "test.avi";
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VideoWriter outputVideo;
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outputVideo.open(outputFilename, -1, 15, Size(image.cols, image.rows));
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if (!outputVideo.isOpened())
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{
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std::cout << "!!! Output video could not be opened" << std::endl;
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getchar();
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return 0;
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}
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#endif
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rectangle(image, boundingBox, Scalar(255, 0, 0), 2, 1);
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imshow("Tracking API", image);
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bool initialized = false;
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int frameCounter = 0;
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//Time measurment
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int64 e3 = getTickCount();
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for (;;)
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{
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//Time measurment
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int64 e1 = getTickCount();
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//Frame num
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frameCounter++;
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if (frameCounter == NUM_TEST_FRAMES) break;
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char c = (char)waitKey(2);
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if (c == 'q' || c == 27)
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break;
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if (c == 'p')
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paused = !paused;
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if (!paused)
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{
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//cap >> frame;
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frame = tld::tld_getNextDatasetFrame();
171+
if (frame.empty())
172+
{
173+
break;
174+
}
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frame.copyTo(image);
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if (selectObject)
178+
{
179+
if (!initialized)
180+
{
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//initializes the tracker
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mt.addTarget(frame, boundingBox1, tracker_algorithm_name);
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rectangle(frame, boundingBox1, mt.colors[0], 2, 1);
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mt.addTarget(frame, boundingBox2, tracker_algorithm_name);
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rectangle(frame, boundingBox2, mt.colors[1], 2, 1);
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initialized = true;
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}
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else
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{
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//updates the tracker
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if (mt.update(frame))
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{
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for (int i = 0; i < mt.targetNum; i++)
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rectangle(frame, mt.boundingBoxes[i], mt.colors[i], 2, 1);
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}
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}
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}
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imshow("Tracking API", frame);
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#ifdef RECORD_VIDEO_FLG
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outputVideo << frame;
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#endif
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//Time measurment
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int64 e2 = getTickCount();
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double t1 = (e2 - e1) / getTickFrequency();
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cout << frameCounter << "\tframe : " << t1 * 1000.0 << "ms" << endl;
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//waitKey(0);
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}
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}
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//Time measurment
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int64 e4 = getTickCount();
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double t2 = (e4 - e3) / getTickFrequency();
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cout << "Average Time for Frame: " << t2 * 1000.0 / frameCounter << "ms" << endl;
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cout << "Average FPS: " << 1.0 / t2*frameCounter << endl;
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waitKey(0);
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return 0;
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}

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