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Tetragramm
GitHub Repository: Tetragramm/opencv
Path: blob/master/modules/objdetect/src/detection_based_tracker.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) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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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 "precomp.hpp"
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#include "opencv2/core/utility.hpp"
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#include <thread>
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#include <mutex>
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#include <condition_variable>
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#if defined(DEBUG) || defined(_DEBUG)
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#undef DEBUGLOGS
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#define DEBUGLOGS 1
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#endif
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#ifndef DEBUGLOGS
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#define DEBUGLOGS 0
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#endif
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#ifdef __ANDROID__
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#include <android/log.h>
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#define LOG_TAG "OBJECT_DETECTOR"
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#define LOGD0(...) ((void)__android_log_print(ANDROID_LOG_DEBUG, LOG_TAG, __VA_ARGS__))
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#define LOGI0(...) ((void)__android_log_print(ANDROID_LOG_INFO, LOG_TAG, __VA_ARGS__))
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#define LOGW0(...) ((void)__android_log_print(ANDROID_LOG_WARN, LOG_TAG, __VA_ARGS__))
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#define LOGE0(...) ((void)__android_log_print(ANDROID_LOG_ERROR, LOG_TAG, __VA_ARGS__))
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#else
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#include <stdio.h>
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#define LOGD0(_str, ...) (printf(_str , ## __VA_ARGS__), printf("\n"), fflush(stdout))
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#define LOGI0(_str, ...) (printf(_str , ## __VA_ARGS__), printf("\n"), fflush(stdout))
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#define LOGW0(_str, ...) (printf(_str , ## __VA_ARGS__), printf("\n"), fflush(stdout))
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#define LOGE0(_str, ...) (printf(_str , ## __VA_ARGS__), printf("\n"), fflush(stdout))
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#endif //__ANDROID__
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#if DEBUGLOGS
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#define LOGD(_str, ...) LOGD0(_str , ## __VA_ARGS__)
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#define LOGI(_str, ...) LOGI0(_str , ## __VA_ARGS__)
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#define LOGW(_str, ...) LOGW0(_str , ## __VA_ARGS__)
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#define LOGE(_str, ...) LOGE0(_str , ## __VA_ARGS__)
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#else
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#define LOGD(...)
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#define LOGI(...)
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#define LOGW(...)
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#define LOGE(...)
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#endif //DEBUGLOGS
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using namespace cv;
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static inline cv::Point2f centerRect(const cv::Rect& r)
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{
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return cv::Point2f(r.x+((float)r.width)/2, r.y+((float)r.height)/2);
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}
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static inline cv::Rect scale_rect(const cv::Rect& r, float scale)
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{
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cv::Point2f m=centerRect(r);
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float width = r.width * scale;
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float height = r.height * scale;
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int x=cvRound(m.x - width/2);
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int y=cvRound(m.y - height/2);
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return cv::Rect(x, y, cvRound(width), cvRound(height));
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}
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namespace cv
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{
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void* workcycleObjectDetectorFunction(void* p);
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}
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class cv::DetectionBasedTracker::SeparateDetectionWork
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{
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public:
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SeparateDetectionWork(cv::DetectionBasedTracker& _detectionBasedTracker, cv::Ptr<DetectionBasedTracker::IDetector> _detector,
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const cv::DetectionBasedTracker::Parameters& params);
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virtual ~SeparateDetectionWork();
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bool communicateWithDetectingThread(const Mat& imageGray, std::vector<Rect>& rectsWhereRegions);
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bool run();
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void stop();
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void resetTracking();
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inline bool isWorking()
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{
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return (stateThread==STATE_THREAD_WORKING_SLEEPING) || (stateThread==STATE_THREAD_WORKING_WITH_IMAGE);
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}
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void setParameters(const cv::DetectionBasedTracker::Parameters& params)
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{
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std::unique_lock<std::mutex> mtx_lock(mtx);
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parameters = params;
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}
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inline void init()
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{
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std::unique_lock<std::mutex> mtx_lock(mtx);
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stateThread = STATE_THREAD_STOPPED;
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isObjectDetectingReady = false;
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shouldObjectDetectingResultsBeForgot = false;
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objectDetectorThreadStartStop.notify_one();
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}
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protected:
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DetectionBasedTracker& detectionBasedTracker;
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cv::Ptr<DetectionBasedTracker::IDetector> cascadeInThread;
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std::thread second_workthread;
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std::mutex mtx;
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std::condition_variable objectDetectorRun;
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std::condition_variable objectDetectorThreadStartStop;
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std::vector<cv::Rect> resultDetect;
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volatile bool isObjectDetectingReady;
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volatile bool shouldObjectDetectingResultsBeForgot;
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enum StateSeparatedThread {
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STATE_THREAD_STOPPED=0,
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STATE_THREAD_WORKING_SLEEPING,
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STATE_THREAD_WORKING_WITH_IMAGE,
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STATE_THREAD_WORKING,
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STATE_THREAD_STOPPING
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};
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volatile StateSeparatedThread stateThread;
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cv::Mat imageSeparateDetecting;
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void workcycleObjectDetector();
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friend void* workcycleObjectDetectorFunction(void* p);
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long long timeWhenDetectingThreadStartedWork;
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cv::DetectionBasedTracker::Parameters parameters;
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};
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cv::DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, cv::Ptr<DetectionBasedTracker::IDetector> _detector,
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const cv::DetectionBasedTracker::Parameters& params)
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:detectionBasedTracker(_detectionBasedTracker),
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cascadeInThread(),
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isObjectDetectingReady(false),
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shouldObjectDetectingResultsBeForgot(false),
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stateThread(STATE_THREAD_STOPPED),
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timeWhenDetectingThreadStartedWork(-1),
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parameters(params)
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{
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CV_Assert(_detector);
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cascadeInThread = _detector;
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}
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cv::DetectionBasedTracker::SeparateDetectionWork::~SeparateDetectionWork()
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{
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if(stateThread!=STATE_THREAD_STOPPED) {
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LOGE("\n\n\nATTENTION!!! dangerous algorithm error: destructor DetectionBasedTracker::DetectionBasedTracker::~SeparateDetectionWork is called before stopping the workthread");
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}
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second_workthread.join();
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}
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bool cv::DetectionBasedTracker::SeparateDetectionWork::run()
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{
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LOGD("DetectionBasedTracker::SeparateDetectionWork::run() --- start");
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std::unique_lock<std::mutex> mtx_lock(mtx);
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// unlocked when leaving scope
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if (stateThread != STATE_THREAD_STOPPED) {
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LOGE("DetectionBasedTracker::SeparateDetectionWork::run is called while the previous run is not stopped");
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return false;
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}
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stateThread=STATE_THREAD_WORKING_SLEEPING;
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second_workthread = std::thread(workcycleObjectDetectorFunction, (void*)this); //TODO: add attributes?
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objectDetectorThreadStartStop.wait(mtx_lock);
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LOGD("DetectionBasedTracker::SeparateDetectionWork::run --- end");
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return true;
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}
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#define CATCH_ALL_AND_LOG(_block) \
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CV_TRY { \
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_block; \
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} \
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CV_CATCH(cv::Exception, e) { \
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LOGE0("\n %s: ERROR: OpenCV Exception caught: \n'%s'\n\n", CV_Func, e.what()); \
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} CV_CATCH(std::exception, e) { \
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LOGE0("\n %s: ERROR: Exception caught: \n'%s'\n\n", CV_Func, e.what()); \
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} CV_CATCH_ALL { \
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LOGE0("\n %s: ERROR: UNKNOWN Exception caught\n\n", CV_Func); \
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}
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void* cv::workcycleObjectDetectorFunction(void* p)
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{
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CATCH_ALL_AND_LOG({ ((cv::DetectionBasedTracker::SeparateDetectionWork*)p)->workcycleObjectDetector(); });
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CV_TRY{
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((cv::DetectionBasedTracker::SeparateDetectionWork*)p)->init();
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} CV_CATCH_ALL {
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LOGE0("DetectionBasedTracker: workcycleObjectDetectorFunction: ERROR concerning pointer, received as the function parameter");
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}
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return NULL;
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}
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void cv::DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector()
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{
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static double freq = getTickFrequency();
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LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- start");
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std::vector<Rect> objects;
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CV_Assert(stateThread==STATE_THREAD_WORKING_SLEEPING);
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std::unique_lock<std::mutex> mtx_lock(mtx);
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{
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objectDetectorThreadStartStop.notify_one();
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LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- before waiting");
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CV_Assert(stateThread==STATE_THREAD_WORKING_SLEEPING);
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objectDetectorRun.wait(mtx_lock);
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if (isWorking()) {
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stateThread=STATE_THREAD_WORKING_WITH_IMAGE;
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}
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LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- after waiting");
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}
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mtx_lock.unlock();
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bool isFirstStep=true;
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isObjectDetectingReady=false;
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while(isWorking())
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{
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LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- next step");
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if (! isFirstStep) {
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LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- before waiting");
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CV_Assert(stateThread==STATE_THREAD_WORKING_SLEEPING);
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mtx_lock.lock();
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if (!isWorking()) {//it is a rare case, but may cause a crash
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LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- go out from the workcycle from inner part of lock just before waiting");
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mtx_lock.unlock();
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break;
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}
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CV_Assert(stateThread==STATE_THREAD_WORKING_SLEEPING);
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objectDetectorRun.wait(mtx_lock);
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if (isWorking()) {
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stateThread=STATE_THREAD_WORKING_WITH_IMAGE;
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}
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mtx_lock.unlock();
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LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- after waiting");
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} else {
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isFirstStep=false;
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}
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if (!isWorking()) {
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LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- go out from the workcycle just after waiting");
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break;
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}
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if (imageSeparateDetecting.empty()) {
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LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- imageSeparateDetecting is empty, continue");
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continue;
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}
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LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- start handling imageSeparateDetecting, img.size=%dx%d, img.data=0x%p",
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imageSeparateDetecting.size().width, imageSeparateDetecting.size().height, (void*)imageSeparateDetecting.data);
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int64 t1_detect=getTickCount();
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cascadeInThread->detect(imageSeparateDetecting, objects);
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/*cascadeInThread.detectMultiScale( imageSeparateDetecting, objects,
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detectionBasedTracker.parameters.scaleFactor, detectionBasedTracker.parameters.minNeighbors, 0
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|CV_HAAR_SCALE_IMAGE
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,
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min_objectSize,
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max_objectSize
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);
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*/
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LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- end handling imageSeparateDetecting");
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if (!isWorking()) {
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LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- go out from the workcycle just after detecting");
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break;
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}
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int64 t2_detect = getTickCount();
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int64 dt_detect = t2_detect-t1_detect;
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double dt_detect_ms=((double)dt_detect)/freq * 1000.0;
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(void)(dt_detect_ms);
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LOGI("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- objects num==%d, t_ms=%.4f", (int)objects.size(), dt_detect_ms);
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mtx_lock.lock();
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if (!shouldObjectDetectingResultsBeForgot) {
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resultDetect=objects;
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isObjectDetectingReady=true;
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} else { //shouldObjectDetectingResultsBeForgot==true
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resultDetect.clear();
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isObjectDetectingReady=false;
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shouldObjectDetectingResultsBeForgot=false;
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}
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if(isWorking()) {
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stateThread=STATE_THREAD_WORKING_SLEEPING;
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}
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mtx_lock.unlock();
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objects.clear();
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}// while(isWorking())
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LOGI("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector: Returning");
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}
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void cv::DetectionBasedTracker::SeparateDetectionWork::stop()
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{
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//FIXME: TODO: should add quickStop functionality
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std::unique_lock<std::mutex> mtx_lock(mtx);
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if (!isWorking()) {
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mtx_lock.unlock();
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LOGE("SimpleHighguiDemoCore::stop is called but the SimpleHighguiDemoCore pthread is not active");
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stateThread = STATE_THREAD_STOPPING;
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return;
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}
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stateThread=STATE_THREAD_STOPPING;
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LOGD("DetectionBasedTracker::SeparateDetectionWork::stop: before going to sleep to wait for the signal from the workthread");
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objectDetectorRun.notify_one();
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objectDetectorThreadStartStop.wait(mtx_lock);
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LOGD("DetectionBasedTracker::SeparateDetectionWork::stop: after receiving the signal from the workthread, stateThread=%d", (int)stateThread);
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mtx_lock.unlock();
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}
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void cv::DetectionBasedTracker::SeparateDetectionWork::resetTracking()
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{
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LOGD("DetectionBasedTracker::SeparateDetectionWork::resetTracking");
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std::unique_lock<std::mutex> mtx_lock(mtx);
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if (stateThread == STATE_THREAD_WORKING_WITH_IMAGE) {
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LOGD("DetectionBasedTracker::SeparateDetectionWork::resetTracking: since workthread is detecting objects at the moment, we should make cascadeInThread stop detecting and forget the detecting results");
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shouldObjectDetectingResultsBeForgot=true;
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//cascadeInThread.setStopFlag();//FIXME: TODO: this feature also should be contributed to OpenCV
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} else {
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LOGD("DetectionBasedTracker::SeparateDetectionWork::resetTracking: since workthread is NOT detecting objects at the moment, we should NOT make any additional actions");
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}
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resultDetect.clear();
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isObjectDetectingReady=false;
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mtx_lock.unlock();
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}
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bool cv::DetectionBasedTracker::SeparateDetectionWork::communicateWithDetectingThread(const Mat& imageGray, std::vector<Rect>& rectsWhereRegions)
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{
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static double freq = getTickFrequency();
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bool shouldCommunicateWithDetectingThread = (stateThread==STATE_THREAD_WORKING_SLEEPING);
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LOGD("DetectionBasedTracker::SeparateDetectionWork::communicateWithDetectingThread: shouldCommunicateWithDetectingThread=%d", (shouldCommunicateWithDetectingThread?1:0));
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if (!shouldCommunicateWithDetectingThread) {
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return false;
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}
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bool shouldHandleResult = false;
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std::unique_lock<std::mutex> mtx_lock(mtx);
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if (isObjectDetectingReady) {
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shouldHandleResult=true;
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rectsWhereRegions = resultDetect;
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isObjectDetectingReady=false;
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double lastBigDetectionDuration = 1000.0 * (((double)(getTickCount() - timeWhenDetectingThreadStartedWork )) / freq);
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(void)(lastBigDetectionDuration);
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LOGD("DetectionBasedTracker::SeparateDetectionWork::communicateWithDetectingThread: lastBigDetectionDuration=%f ms", (double)lastBigDetectionDuration);
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}
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bool shouldSendNewDataToWorkThread = true;
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if (timeWhenDetectingThreadStartedWork > 0) {
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double time_from_previous_launch_in_ms=1000.0 * (((double)(getTickCount() - timeWhenDetectingThreadStartedWork )) / freq); //the same formula as for lastBigDetectionDuration
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shouldSendNewDataToWorkThread = (time_from_previous_launch_in_ms >= detectionBasedTracker.parameters.minDetectionPeriod);
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LOGD("DetectionBasedTracker::SeparateDetectionWork::communicateWithDetectingThread: shouldSendNewDataToWorkThread was 1, now it is %d, since time_from_previous_launch_in_ms=%.2f, minDetectionPeriod=%d",
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(shouldSendNewDataToWorkThread?1:0), time_from_previous_launch_in_ms, detectionBasedTracker.parameters.minDetectionPeriod);
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}
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if (shouldSendNewDataToWorkThread) {
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imageSeparateDetecting.create(imageGray.size(), CV_8UC1);
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imageGray.copyTo(imageSeparateDetecting);//may change imageSeparateDetecting ptr. But should not.
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timeWhenDetectingThreadStartedWork = getTickCount() ;
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objectDetectorRun.notify_one();
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}
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mtx_lock.unlock();
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LOGD("DetectionBasedTracker::SeparateDetectionWork::communicateWithDetectingThread: result: shouldHandleResult=%d", (shouldHandleResult?1:0));
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return shouldHandleResult;
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}
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cv::DetectionBasedTracker::Parameters::Parameters()
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{
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maxTrackLifetime = 5;
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minDetectionPeriod = 0;
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}
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cv::DetectionBasedTracker::InnerParameters::InnerParameters()
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{
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numLastPositionsToTrack=4;
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numStepsToWaitBeforeFirstShow=6;
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numStepsToTrackWithoutDetectingIfObjectHasNotBeenShown=3;
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numStepsToShowWithoutDetecting=3;
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coeffTrackingWindowSize=2.0;
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coeffObjectSizeToTrack=0.85f;
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coeffObjectSpeedUsingInPrediction=0.8f;
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}
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cv::DetectionBasedTracker::DetectionBasedTracker(cv::Ptr<IDetector> mainDetector, cv::Ptr<IDetector> trackingDetector, const Parameters& params)
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:separateDetectionWork(),
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parameters(params),
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innerParameters(),
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numTrackedSteps(0),
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cascadeForTracking(trackingDetector)
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{
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CV_Assert( (params.maxTrackLifetime >= 0)
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// && mainDetector
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&& trackingDetector );
460
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if (mainDetector) {
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Ptr<SeparateDetectionWork> tmp(new SeparateDetectionWork(*this, mainDetector, params));
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separateDetectionWork.swap(tmp);
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}
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weightsPositionsSmoothing.push_back(1);
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weightsSizesSmoothing.push_back(0.5);
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weightsSizesSmoothing.push_back(0.3f);
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weightsSizesSmoothing.push_back(0.2f);
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}
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cv::DetectionBasedTracker::~DetectionBasedTracker()
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{
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}
475
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void DetectionBasedTracker::process(const Mat& imageGray)
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{
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CV_INSTRUMENT_REGION();
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CV_Assert(imageGray.type()==CV_8UC1);
481
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if ( separateDetectionWork && !separateDetectionWork->isWorking() ) {
483
separateDetectionWork->run();
484
}
485
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static double freq = getTickFrequency();
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static long long time_when_last_call_started=getTickCount();
488
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{
490
double delta_time_from_prev_call=1000.0 * (((double)(getTickCount() - time_when_last_call_started)) / freq);
491
(void)(delta_time_from_prev_call);
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LOGD("DetectionBasedTracker::process: time from the previous call is %f ms", (double)delta_time_from_prev_call);
493
time_when_last_call_started=getTickCount();
494
}
495
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Mat imageDetect=imageGray;
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std::vector<Rect> rectsWhereRegions;
499
bool shouldHandleResult=false;
500
if (separateDetectionWork) {
501
shouldHandleResult = separateDetectionWork->communicateWithDetectingThread(imageGray, rectsWhereRegions);
502
}
503
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if (shouldHandleResult) {
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LOGD("DetectionBasedTracker::process: get _rectsWhereRegions were got from resultDetect");
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} else {
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LOGD("DetectionBasedTracker::process: get _rectsWhereRegions from previous positions");
508
for(size_t i = 0; i < trackedObjects.size(); i++) {
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size_t n = trackedObjects[i].lastPositions.size();
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CV_Assert(n > 0);
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Rect r = trackedObjects[i].lastPositions[n-1];
513
if(r.empty()) {
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LOGE("DetectionBasedTracker::process: ERROR: ATTENTION: strange algorithm's behavior: trackedObjects[i].rect() is empty");
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continue;
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}
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//correction by speed of rectangle
519
if (n > 1) {
520
Point2f center = centerRect(r);
521
Point2f center_prev = centerRect(trackedObjects[i].lastPositions[n-2]);
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Point2f shift = (center - center_prev) * innerParameters.coeffObjectSpeedUsingInPrediction;
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r.x += cvRound(shift.x);
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r.y += cvRound(shift.y);
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}
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rectsWhereRegions.push_back(r);
530
}
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}
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LOGI("DetectionBasedTracker::process: tracked objects num==%d", (int)trackedObjects.size());
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std::vector<Rect> detectedObjectsInRegions;
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LOGD("DetectionBasedTracker::process: rectsWhereRegions.size()=%d", (int)rectsWhereRegions.size());
537
for(size_t i=0; i < rectsWhereRegions.size(); i++) {
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Rect r = rectsWhereRegions[i];
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detectInRegion(imageDetect, r, detectedObjectsInRegions);
541
}
542
LOGD("DetectionBasedTracker::process: detectedObjectsInRegions.size()=%d", (int)detectedObjectsInRegions.size());
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updateTrackedObjects(detectedObjectsInRegions);
545
}
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void cv::DetectionBasedTracker::getObjects(std::vector<cv::Rect>& result) const
548
{
549
result.clear();
550
551
for(size_t i=0; i < trackedObjects.size(); i++) {
552
Rect r=calcTrackedObjectPositionToShow((int)i);
553
if (r.empty()) {
554
continue;
555
}
556
result.push_back(r);
557
LOGD("DetectionBasedTracker::process: found a object with SIZE %d x %d, rect={%d, %d, %d x %d}", r.width, r.height, r.x, r.y, r.width, r.height);
558
}
559
}
560
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void cv::DetectionBasedTracker::getObjects(std::vector<Object>& result) const
562
{
563
result.clear();
564
565
for(size_t i=0; i < trackedObjects.size(); i++) {
566
Rect r=calcTrackedObjectPositionToShow((int)i);
567
if (r.empty()) {
568
continue;
569
}
570
result.push_back(Object(r, trackedObjects[i].id));
571
LOGD("DetectionBasedTracker::process: found a object with SIZE %d x %d, rect={%d, %d, %d x %d}", r.width, r.height, r.x, r.y, r.width, r.height);
572
}
573
}
574
void cv::DetectionBasedTracker::getObjects(std::vector<ExtObject>& result) const
575
{
576
result.clear();
577
578
for(size_t i=0; i < trackedObjects.size(); i++) {
579
ObjectStatus status;
580
Rect r=calcTrackedObjectPositionToShow((int)i, status);
581
result.push_back(ExtObject(trackedObjects[i].id, r, status));
582
LOGD("DetectionBasedTracker::process: found a object with SIZE %d x %d, rect={%d, %d, %d x %d}, status = %d", r.width, r.height, r.x, r.y, r.width, r.height, (int)status);
583
}
584
}
585
586
bool cv::DetectionBasedTracker::run()
587
{
588
if (separateDetectionWork) {
589
return separateDetectionWork->run();
590
}
591
return false;
592
}
593
594
void cv::DetectionBasedTracker::stop()
595
{
596
if (separateDetectionWork) {
597
separateDetectionWork->stop();
598
}
599
}
600
601
void cv::DetectionBasedTracker::resetTracking()
602
{
603
if (separateDetectionWork) {
604
separateDetectionWork->resetTracking();
605
}
606
trackedObjects.clear();
607
}
608
609
void cv::DetectionBasedTracker::updateTrackedObjects(const std::vector<Rect>& detectedObjects)
610
{
611
enum {
612
NEW_RECTANGLE=-1,
613
INTERSECTED_RECTANGLE=-2
614
};
615
616
int N1=(int)trackedObjects.size();
617
int N2=(int)detectedObjects.size();
618
LOGD("DetectionBasedTracker::updateTrackedObjects: N1=%d, N2=%d", N1, N2);
619
620
for(int i=0; i < N1; i++) {
621
trackedObjects[i].numDetectedFrames++;
622
}
623
624
std::vector<int> correspondence(detectedObjects.size(), NEW_RECTANGLE);
625
correspondence.clear();
626
correspondence.resize(detectedObjects.size(), NEW_RECTANGLE);
627
628
for(int i=0; i < N1; i++) {
629
LOGD("DetectionBasedTracker::updateTrackedObjects: i=%d", i);
630
TrackedObject& curObject=trackedObjects[i];
631
632
int bestIndex=-1;
633
int bestArea=-1;
634
635
int numpositions=(int)curObject.lastPositions.size();
636
CV_Assert(numpositions > 0);
637
Rect prevRect=curObject.lastPositions[numpositions-1];
638
LOGD("DetectionBasedTracker::updateTrackedObjects: prevRect[%d]={%d, %d, %d x %d}", i, prevRect.x, prevRect.y, prevRect.width, prevRect.height);
639
640
for(int j=0; j < N2; j++) {
641
LOGD("DetectionBasedTracker::updateTrackedObjects: j=%d", j);
642
if (correspondence[j] >= 0) {
643
LOGD("DetectionBasedTracker::updateTrackedObjects: j=%d is rejected, because it has correspondence=%d", j, correspondence[j]);
644
continue;
645
}
646
if (correspondence[j] !=NEW_RECTANGLE) {
647
LOGD("DetectionBasedTracker::updateTrackedObjects: j=%d is rejected, because it is intersected with another rectangle", j);
648
continue;
649
}
650
LOGD("DetectionBasedTracker::updateTrackedObjects: detectedObjects[%d]={%d, %d, %d x %d}",
651
j, detectedObjects[j].x, detectedObjects[j].y, detectedObjects[j].width, detectedObjects[j].height);
652
653
Rect r=prevRect & detectedObjects[j];
654
if ( (r.width > 0) && (r.height > 0) ) {
655
LOGD("DetectionBasedTracker::updateTrackedObjects: There is intersection between prevRect and detectedRect, r={%d, %d, %d x %d}",
656
r.x, r.y, r.width, r.height);
657
correspondence[j]=INTERSECTED_RECTANGLE;
658
659
if ( r.area() > bestArea) {
660
LOGD("DetectionBasedTracker::updateTrackedObjects: The area of intersection is %d, it is better than bestArea=%d", r.area(), bestArea);
661
bestIndex=j;
662
bestArea=r.area();
663
}
664
}
665
}
666
if (bestIndex >= 0) {
667
LOGD("DetectionBasedTracker::updateTrackedObjects: The best correspondence for i=%d is j=%d", i, bestIndex);
668
correspondence[bestIndex]=i;
669
670
for(int j=0; j < N2; j++) {
671
if (correspondence[j] >= 0)
672
continue;
673
674
Rect r=detectedObjects[j] & detectedObjects[bestIndex];
675
if ( (r.width > 0) && (r.height > 0) ) {
676
LOGD("DetectionBasedTracker::updateTrackedObjects: Found intersection between "
677
"rectangles j=%d and bestIndex=%d, rectangle j=%d is marked as intersected", j, bestIndex, j);
678
correspondence[j]=INTERSECTED_RECTANGLE;
679
}
680
}
681
} else {
682
LOGD("DetectionBasedTracker::updateTrackedObjects: There is no correspondence for i=%d ", i);
683
curObject.numFramesNotDetected++;
684
}
685
}
686
687
LOGD("DetectionBasedTracker::updateTrackedObjects: start second cycle");
688
for(int j=0; j < N2; j++) {
689
LOGD("DetectionBasedTracker::updateTrackedObjects: j=%d", j);
690
int i=correspondence[j];
691
if (i >= 0) {//add position
692
LOGD("DetectionBasedTracker::updateTrackedObjects: add position");
693
trackedObjects[i].lastPositions.push_back(detectedObjects[j]);
694
while ((int)trackedObjects[i].lastPositions.size() > (int) innerParameters.numLastPositionsToTrack) {
695
trackedObjects[i].lastPositions.erase(trackedObjects[i].lastPositions.begin());
696
}
697
trackedObjects[i].numFramesNotDetected=0;
698
} else if (i==NEW_RECTANGLE){ //new object
699
LOGD("DetectionBasedTracker::updateTrackedObjects: new object");
700
trackedObjects.push_back(detectedObjects[j]);
701
} else {
702
LOGD("DetectionBasedTracker::updateTrackedObjects: was auxiliary intersection");
703
}
704
}
705
706
std::vector<TrackedObject>::iterator it=trackedObjects.begin();
707
while( it != trackedObjects.end() ) {
708
if ( (it->numFramesNotDetected > parameters.maxTrackLifetime)
709
||
710
(
711
(it->numDetectedFrames <= innerParameters.numStepsToWaitBeforeFirstShow)
712
&&
713
(it->numFramesNotDetected > innerParameters.numStepsToTrackWithoutDetectingIfObjectHasNotBeenShown)
714
)
715
)
716
{
717
int numpos=(int)it->lastPositions.size();
718
CV_Assert(numpos > 0);
719
Rect r = it->lastPositions[numpos-1];
720
(void)(r);
721
LOGD("DetectionBasedTracker::updateTrackedObjects: deleted object {%d, %d, %d x %d}",
722
r.x, r.y, r.width, r.height);
723
it=trackedObjects.erase(it);
724
} else {
725
it++;
726
}
727
}
728
}
729
730
int cv::DetectionBasedTracker::addObject(const Rect& location)
731
{
732
LOGD("DetectionBasedTracker::addObject: new object {%d, %d %dx%d}",location.x, location.y, location.width, location.height);
733
trackedObjects.push_back(TrackedObject(location));
734
int newId = trackedObjects.back().id;
735
LOGD("DetectionBasedTracker::addObject: newId = %d", newId);
736
return newId;
737
}
738
739
Rect cv::DetectionBasedTracker::calcTrackedObjectPositionToShow(int i) const
740
{
741
ObjectStatus status;
742
return calcTrackedObjectPositionToShow(i, status);
743
}
744
Rect cv::DetectionBasedTracker::calcTrackedObjectPositionToShow(int i, ObjectStatus& status) const
745
{
746
if ( (i < 0) || (i >= (int)trackedObjects.size()) ) {
747
LOGE("DetectionBasedTracker::calcTrackedObjectPositionToShow: ERROR: wrong i=%d", i);
748
status = WRONG_OBJECT;
749
return Rect();
750
}
751
if (trackedObjects[i].numDetectedFrames <= innerParameters.numStepsToWaitBeforeFirstShow){
752
LOGI("DetectionBasedTracker::calcTrackedObjectPositionToShow: trackedObjects[%d].numDetectedFrames=%d <= numStepsToWaitBeforeFirstShow=%d --- return empty Rect()",
753
i, trackedObjects[i].numDetectedFrames, innerParameters.numStepsToWaitBeforeFirstShow);
754
status = DETECTED_NOT_SHOWN_YET;
755
return Rect();
756
}
757
if (trackedObjects[i].numFramesNotDetected > innerParameters.numStepsToShowWithoutDetecting) {
758
status = DETECTED_TEMPORARY_LOST;
759
return Rect();
760
}
761
762
const TrackedObject::PositionsVector& lastPositions=trackedObjects[i].lastPositions;
763
764
int N=(int)lastPositions.size();
765
if (N<=0) {
766
LOGE("DetectionBasedTracker::calcTrackedObjectPositionToShow: ERROR: no positions for i=%d", i);
767
status = WRONG_OBJECT;
768
return Rect();
769
}
770
771
int Nsize=std::min(N, (int)weightsSizesSmoothing.size());
772
int Ncenter= std::min(N, (int)weightsPositionsSmoothing.size());
773
774
Point2f center;
775
double w=0, h=0;
776
if (Nsize > 0) {
777
double sum=0;
778
for(int j=0; j < Nsize; j++) {
779
int k=N-j-1;
780
w += lastPositions[k].width * weightsSizesSmoothing[j];
781
h += lastPositions[k].height * weightsSizesSmoothing[j];
782
sum+=weightsSizesSmoothing[j];
783
}
784
w /= sum;
785
h /= sum;
786
} else {
787
w=lastPositions[N-1].width;
788
h=lastPositions[N-1].height;
789
}
790
791
if (Ncenter > 0) {
792
double sum=0;
793
for(int j=0; j < Ncenter; j++) {
794
int k=N-j-1;
795
Point tl(lastPositions[k].tl());
796
Point br(lastPositions[k].br());
797
Point2f c1;
798
c1=tl;
799
c1=c1* 0.5f;
800
Point2f c2;
801
c2=br;
802
c2=c2*0.5f;
803
c1=c1+c2;
804
805
center=center+ (c1 * weightsPositionsSmoothing[j]);
806
sum+=weightsPositionsSmoothing[j];
807
}
808
center *= (float)(1 / sum);
809
} else {
810
int k=N-1;
811
Point tl(lastPositions[k].tl());
812
Point br(lastPositions[k].br());
813
Point2f c1;
814
c1=tl;
815
c1=c1* 0.5f;
816
Point2f c2;
817
c2=br;
818
c2=c2*0.5f;
819
820
center=c1+c2;
821
}
822
Point2f tl=center-Point2f((float)w*0.5f,(float)h*0.5f);
823
Rect res(cvRound(tl.x), cvRound(tl.y), cvRound(w), cvRound(h));
824
LOGD("DetectionBasedTracker::calcTrackedObjectPositionToShow: Result for i=%d: {%d, %d, %d x %d}", i, res.x, res.y, res.width, res.height);
825
826
status = DETECTED;
827
return res;
828
}
829
830
void cv::DetectionBasedTracker::detectInRegion(const Mat& img, const Rect& r, std::vector<Rect>& detectedObjectsInRegions)
831
{
832
Rect r0(Point(), img.size());
833
Rect r1 = scale_rect(r, innerParameters.coeffTrackingWindowSize);
834
r1 = r1 & r0;
835
836
if ( (r1.width <=0) || (r1.height <= 0) ) {
837
LOGD("DetectionBasedTracker::detectInRegion: Empty intersection");
838
return;
839
}
840
841
int d = cvRound(std::min(r.width, r.height) * innerParameters.coeffObjectSizeToTrack);
842
843
std::vector<Rect> tmpobjects;
844
845
Mat img1(img, r1);//subimage for rectangle -- without data copying
846
LOGD("DetectionBasedTracker::detectInRegion: img1.size()=%d x %d, d=%d",
847
img1.size().width, img1.size().height, d);
848
849
cascadeForTracking->setMinObjectSize(Size(d, d));
850
cascadeForTracking->detect(img1, tmpobjects);
851
/*
852
detectMultiScale( img1, tmpobjects,
853
parameters.scaleFactor, parameters.minNeighbors, 0
854
|CV_HAAR_FIND_BIGGEST_OBJECT
855
|CV_HAAR_SCALE_IMAGE
856
,
857
Size(d,d),
858
max_objectSize
859
);*/
860
861
for(size_t i=0; i < tmpobjects.size(); i++) {
862
Rect curres(tmpobjects[i].tl() + r1.tl(), tmpobjects[i].size());
863
detectedObjectsInRegions.push_back(curres);
864
}
865
}
866
867
bool cv::DetectionBasedTracker::setParameters(const Parameters& params)
868
{
869
if ( params.maxTrackLifetime < 0 )
870
{
871
LOGE("DetectionBasedTracker::setParameters: ERROR: wrong parameters value");
872
return false;
873
}
874
875
if (separateDetectionWork) {
876
separateDetectionWork->setParameters(params);
877
}
878
parameters=params;
879
return true;
880
}
881
882
const cv::DetectionBasedTracker::Parameters& DetectionBasedTracker::getParameters() const
883
{
884
return parameters;
885
}
886
887