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Reverted changes breaking Android build
This commit is contained in:
Andrey Kamaev
parent
a497e1b37e
commit
e8d158a5c8
@ -12,66 +12,17 @@ class DetectionBasedTracker
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public:
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struct Parameters
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{
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int minObjectSize;
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int maxObjectSize;
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double scaleFactor;
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int maxTrackLifetime;
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int minNeighbors;
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int minDetectionPeriod; //the minimal time between run of the big object detector (on the whole frame) in ms (1000 mean 1 sec), default=0
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Parameters();
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};
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class IDetector
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{
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public:
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IDetector():
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minObjSize(96, 96),
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maxObjSize(INT_MAX, INT_MAX),
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scaleFactor(1.1f),
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minNeighbours(2)
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{}
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virtual void detect(const cv::Mat& Image, std::vector<cv::Rect>& objects) = 0;
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void setMinObjectSize(const cv::Size& min)
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{
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minObjSize = min;
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}
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void setMaxObjectSize(const cv::Size& max)
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{
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maxObjSize = max;
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}
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cv::Size getMinObjectSize() const
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{
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return minObjSize;
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}
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cv::Size getMaxObjectSize() const
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{
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return maxObjSize;
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}
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float getScaleFactor()
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{
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return scaleFactor;
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}
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void setScaleFactor(float value)
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{
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scaleFactor = value;
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}
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int getMinNeighbours()
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{
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return minNeighbours;
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}
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void setMinNeighbours(int value)
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{
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minNeighbours = value;
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}
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virtual ~IDetector() {}
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protected:
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cv::Size minObjSize;
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cv::Size maxObjSize;
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int minNeighbours;
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float scaleFactor;
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};
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DetectionBasedTracker(cv::Ptr<IDetector> MainDetector, cv::Ptr<IDetector> TrackingDetector, const Parameters& params);
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DetectionBasedTracker(const std::string& cascadeFilename, const Parameters& params);
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virtual ~DetectionBasedTracker();
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virtual bool run();
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@ -93,6 +44,7 @@ class DetectionBasedTracker
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cv::Ptr<SeparateDetectionWork> separateDetectionWork;
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friend void* workcycleObjectDetectorFunction(void* p);
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struct InnerParameters
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{
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int numLastPositionsToTrack;
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@ -138,7 +90,8 @@ class DetectionBasedTracker
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std::vector<float> weightsPositionsSmoothing;
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std::vector<float> weightsSizesSmoothing;
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cv::Ptr<IDetector> cascadeForTracking;
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cv::CascadeClassifier cascadeForTracking;
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void updateTrackedObjects(const std::vector<cv::Rect>& detectedObjects);
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cv::Rect calcTrackedObjectPositionToShow(int i) const;
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@ -52,11 +52,10 @@ static inline cv::Rect scale_rect(const cv::Rect& r, float scale)
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};
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void* workcycleObjectDetectorFunction(void* p);
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class DetectionBasedTracker::SeparateDetectionWork
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{
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public:
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SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, cv::Ptr<DetectionBasedTracker::IDetector> _detector);
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SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, const std::string& cascadeFilename);
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virtual ~SeparateDetectionWork();
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bool communicateWithDetectingThread(const Mat& imageGray, vector<Rect>& rectsWhereRegions);
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bool run();
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@ -78,7 +77,7 @@ class DetectionBasedTracker::SeparateDetectionWork
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protected:
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DetectionBasedTracker& detectionBasedTracker;
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cv::Ptr<DetectionBasedTracker::IDetector> cascadeInThread;
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cv::CascadeClassifier cascadeInThread;
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pthread_t second_workthread;
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pthread_mutex_t mutex;
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@ -106,7 +105,7 @@ class DetectionBasedTracker::SeparateDetectionWork
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long long timeWhenDetectingThreadStartedWork;
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};
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DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, cv::Ptr<DetectionBasedTracker::IDetector> _detector)
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DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, const std::string& cascadeFilename)
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:detectionBasedTracker(_detectionBasedTracker),
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cascadeInThread(),
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isObjectDetectingReady(false),
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@ -114,10 +113,9 @@ DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork(DetectionBas
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stateThread(STATE_THREAD_STOPPED),
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timeWhenDetectingThreadStartedWork(-1)
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{
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CV_Assert(!_detector.empty());
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cascadeInThread = _detector;
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if(!cascadeInThread.load(cascadeFilename)) {
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CV_Error(CV_StsBadArg, "DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork: Cannot load a cascade from the file '"+cascadeFilename+"'");
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}
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int res=0;
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res=pthread_mutex_init(&mutex, NULL);//TODO: should be attributes?
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if (res) {
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@ -276,17 +274,20 @@ void DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector()
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int64 t1_detect=getTickCount();
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cascadeInThread->detect(imageSeparateDetecting, objects);
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int minObjectSize=detectionBasedTracker.parameters.minObjectSize;
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Size min_objectSize=Size(minObjectSize, minObjectSize);
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/*cascadeInThread.detectMultiScale( imageSeparateDetecting, objects,
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int maxObjectSize=detectionBasedTracker.parameters.maxObjectSize;
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Size max_objectSize(maxObjectSize, maxObjectSize);
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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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@ -421,10 +422,16 @@ bool DetectionBasedTracker::SeparateDetectionWork::communicateWithDetectingThrea
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DetectionBasedTracker::Parameters::Parameters()
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{
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minObjectSize=96;
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maxObjectSize=INT_MAX;
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scaleFactor=1.1;
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maxTrackLifetime=5;
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minNeighbors=2;
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minDetectionPeriod=0;
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}
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DetectionBasedTracker::InnerParameters::InnerParameters()
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{
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numLastPositionsToTrack=4;
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@ -437,32 +444,39 @@ DetectionBasedTracker::InnerParameters::InnerParameters()
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coeffObjectSpeedUsingInPrediction=0.8;
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}
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DetectionBasedTracker::DetectionBasedTracker(cv::Ptr<IDetector> MainDetector, cv::Ptr<IDetector> TrackingDetector, const Parameters& params)
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DetectionBasedTracker::DetectionBasedTracker(const std::string& cascadeFilename, const Parameters& params)
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:separateDetectionWork(),
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innerParameters(),
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cascadeForTracking(TrackingDetector),
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parameters(params),
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numTrackedSteps(0)
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{
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CV_Assert( (params.maxTrackLifetime >= 0)
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&& (!MainDetector.empty())
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&& (!TrackingDetector.empty()) );
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CV_Assert( (params.minObjectSize > 0)
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&& (params.maxObjectSize >= 0)
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&& (params.scaleFactor > 1.0)
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&& (params.maxTrackLifetime >= 0) );
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separateDetectionWork = new SeparateDetectionWork(*this, MainDetector);
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if (!cascadeForTracking.load(cascadeFilename)) {
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CV_Error(CV_StsBadArg, "DetectionBasedTracker::DetectionBasedTracker: Cannot load a cascade from the file '"+cascadeFilename+"'");
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}
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parameters=params;
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separateDetectionWork=new SeparateDetectionWork(*this, cascadeFilename);
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weightsPositionsSmoothing.push_back(1);
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weightsSizesSmoothing.push_back(0.5);
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weightsSizesSmoothing.push_back(0.3);
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weightsSizesSmoothing.push_back(0.2);
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}
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}
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DetectionBasedTracker::~DetectionBasedTracker()
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{
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}
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void DetectionBasedTracker::process(const Mat& imageGray)
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{
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CV_Assert(imageGray.type()==CV_8UC1);
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if (!separateDetectionWork->isWorking()) {
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@ -480,9 +494,15 @@ void DetectionBasedTracker::process(const Mat& imageGray)
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Mat imageDetect=imageGray;
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int D=parameters.minObjectSize;
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if (D < 1)
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D=1;
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vector<Rect> rectsWhereRegions;
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bool shouldHandleResult=separateDetectionWork->communicateWithDetectingThread(imageGray, rectsWhereRegions);
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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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@ -497,6 +517,7 @@ void DetectionBasedTracker::process(const Mat& imageGray)
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continue;
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}
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//correction by speed of rectangle
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if (n > 1) {
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Point2f center=centerRect(r);
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@ -539,7 +560,6 @@ void DetectionBasedTracker::getObjects(std::vector<cv::Rect>& result) const
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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);
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}
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}
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void DetectionBasedTracker::getObjects(std::vector<Object>& result) const
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{
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result.clear();
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@ -554,6 +574,8 @@ void DetectionBasedTracker::getObjects(std::vector<Object>& result) const
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}
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}
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bool DetectionBasedTracker::run()
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{
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return separateDetectionWork->run();
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@ -689,7 +711,6 @@ void DetectionBasedTracker::updateTrackedObjects(const vector<Rect>& detectedObj
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}
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}
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}
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Rect DetectionBasedTracker::calcTrackedObjectPositionToShow(int i) const
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{
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if ( (i < 0) || (i >= (int)trackedObjects.size()) ) {
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@ -722,8 +743,8 @@ Rect DetectionBasedTracker::calcTrackedObjectPositionToShow(int i) const
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double sum=0;
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for(int j=0; j < Nsize; j++) {
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int k=N-j-1;
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w += lastPositions[k].width * weightsSizesSmoothing[j];
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h += lastPositions[k].height * weightsSizesSmoothing[j];
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w+= lastPositions[k].width * weightsSizesSmoothing[j];
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h+= lastPositions[k].height * weightsSizesSmoothing[j];
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sum+=weightsSizesSmoothing[j];
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}
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w /= sum;
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@ -741,7 +762,7 @@ Rect DetectionBasedTracker::calcTrackedObjectPositionToShow(int i) const
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Point br(lastPositions[k].br());
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Point2f c1;
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c1=tl;
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c1=c1* 0.5f;
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c1=c1* 0.5f;
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Point2f c2;
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c2=br;
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c2=c2*0.5f;
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@ -781,7 +802,8 @@ void DetectionBasedTracker::detectInRegion(const Mat& img, const Rect& r, vector
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return;
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}
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int d = cvRound(std::min(r.width, r.height) * innerParameters.coeffObjectSizeToTrack);
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int d=std::min(r.width, r.height);
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d=cvRound(d * innerParameters.coeffObjectSizeToTrack);
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vector<Rect> tmpobjects;
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@ -789,17 +811,17 @@ void DetectionBasedTracker::detectInRegion(const Mat& img, const Rect& r, vector
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LOGD("DetectionBasedTracker::detectInRegion: img1.size()=%d x %d, d=%d",
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img1.size().width, img1.size().height, d);
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cascadeForTracking->setMinObjectSize(Size(d, d));
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cascadeForTracking->detect(img1, tmpobjects);
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/*
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detectMultiScale( img1, tmpobjects,
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int maxObjectSize=parameters.maxObjectSize;
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Size max_objectSize(maxObjectSize, maxObjectSize);
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cascadeForTracking.detectMultiScale( img1, tmpobjects,
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parameters.scaleFactor, parameters.minNeighbors, 0
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|CV_HAAR_FIND_BIGGEST_OBJECT
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|CV_HAAR_SCALE_IMAGE
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,
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Size(d,d),
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max_objectSize
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);*/
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);
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for(size_t i=0; i < tmpobjects.size(); i++) {
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Rect curres(tmpobjects[i].tl() + r1.tl(), tmpobjects[i].size());
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@ -809,7 +831,10 @@ void DetectionBasedTracker::detectInRegion(const Mat& img, const Rect& r, vector
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bool DetectionBasedTracker::setParameters(const Parameters& params)
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{
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if ( params.maxTrackLifetime < 0 )
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if ( (params.minObjectSize <= 0)
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|| (params.maxObjectSize < 0)
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|| (params.scaleFactor <= 1.0)
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|| (params.maxTrackLifetime < 0) )
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{
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LOGE("DetectionBasedTracker::setParameters: ERROR: wrong parameters value");
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return false;
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@ -1,104 +0,0 @@
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#if defined(__linux__) || defined(LINUX) || defined(__APPLE__) || defined(ANDROID)
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#include <opencv2/imgproc/imgproc.hpp> // Gaussian Blur
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#include <opencv2/core/core.hpp> // Basic OpenCV structures (cv::Mat, Scalar)
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#include <opencv2/highgui/highgui.hpp> // OpenCV window I/O
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#include <opencv2/features2d/features2d.hpp>
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#include <opencv2/contrib/detection_based_tracker.hpp>
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#include <stdio.h>
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#include <string>
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#include <vector>
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using namespace std;
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using namespace cv;
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const string WindowName = "Face Detection example";
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class CascadeDetectorAdapter: public DetectionBasedTracker::IDetector
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{
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public:
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CascadeDetectorAdapter(cv::Ptr<cv::CascadeClassifier> detector):
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IDetector(),
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Detector(detector)
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{
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CV_Assert(!detector.empty());
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}
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void detect(const cv::Mat &Image, std::vector<cv::Rect> &objects)
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{
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Detector->detectMultiScale(Image, objects, scaleFactor, minNeighbours, 0, minObjSize, maxObjSize);
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}
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virtual ~CascadeDetectorAdapter()
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{}
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private:
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CascadeDetectorAdapter();
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cv::Ptr<cv::CascadeClassifier> Detector;
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};
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int main(int argc, char* argv[])
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{
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namedWindow(WindowName);
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VideoCapture VideoStream(0);
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if (!VideoStream.isOpened())
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{
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printf("Error: Cannot open video stream from camera\n");
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return 1;
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}
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std::string cascadeFrontalfilename = "../../data/lbpcascades/lbpcascade_frontalface.xml";
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cv::Ptr<cv::CascadeClassifier> cascade = new cv::CascadeClassifier(cascadeFrontalfilename);
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cv::Ptr<DetectionBasedTracker::IDetector> MainDetector = new CascadeDetectorAdapter(cascade);
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cascade = new cv::CascadeClassifier(cascadeFrontalfilename);
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cv::Ptr<DetectionBasedTracker::IDetector> TrackingDetector = new CascadeDetectorAdapter(cascade);
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DetectionBasedTracker::Parameters params;
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DetectionBasedTracker Detector(MainDetector, TrackingDetector, params);
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if (!Detector.run())
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{
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printf("Error: Detector initialization failed\n");
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return 2;
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}
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Mat ReferenceFrame;
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Mat GrayFrame;
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vector<Rect> Faces;
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while(true)
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{
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VideoStream >> ReferenceFrame;
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cvtColor(ReferenceFrame, GrayFrame, COLOR_RGB2GRAY);
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Detector.process(GrayFrame);
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Detector.getObjects(Faces);
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for (size_t i = 0; i < Faces.size(); i++)
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{
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rectangle(ReferenceFrame, Faces[i], CV_RGB(0,255,0));
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}
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imshow(WindowName, ReferenceFrame);
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if (cvWaitKey(30) >= 0) break;
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}
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Detector.stop();
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return 0;
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}
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#else
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#include <stdio.h>
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int main()
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{
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printf("This sample works for UNIX or ANDROID only\n");
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return 0;
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}
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#endif
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@ -43,6 +43,8 @@
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#define LOGE(...) do{} while(0)
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#endif
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using namespace cv;
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using namespace std;
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@ -61,32 +63,9 @@ static void usage()
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LOGE0("\t (e.g.\"opencv/data/lbpcascades/lbpcascade_frontalface.xml\" ");
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}
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class CascadeDetectorAdapter: public DetectionBasedTracker::IDetector
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{
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public:
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CascadeDetectorAdapter(cv::Ptr<cv::CascadeClassifier> detector):
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IDetector(),
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Detector(detector)
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{
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CV_Assert(!detector.empty());
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}
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void detect(const cv::Mat &Image, std::vector<cv::Rect> &objects)
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{
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Detector->detectMultiScale(Image, objects, 1.1, 3, 0, minObjSize, maxObjSize);
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}
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virtual ~CascadeDetectorAdapter()
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{}
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private:
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CascadeDetectorAdapter();
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cv::Ptr<cv::CascadeClassifier> Detector;
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};
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static int test_FaceDetector(int argc, char *argv[])
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{
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if (argc < 4)
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{
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if (argc < 4) {
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usage();
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return -1;
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}
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@ -101,14 +80,12 @@ static int test_FaceDetector(int argc, char *argv[])
|
||||
vector<Mat> images;
|
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{
|
||||
char filename[256];
|
||||
for(int n=1; ; n++)
|
||||
{
|
||||
for(int n=1; ; n++) {
|
||||
snprintf(filename, sizeof(filename), filepattern, n);
|
||||
LOGD("filename='%s'", filename);
|
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Mat m0;
|
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m0=imread(filename);
|
||||
if (m0.empty())
|
||||
{
|
||||
if (m0.empty()) {
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LOGI0("Cannot read the file --- break");
|
||||
break;
|
||||
}
|
||||
@ -117,15 +94,10 @@ static int test_FaceDetector(int argc, char *argv[])
|
||||
LOGD("read %d images", (int)images.size());
|
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}
|
||||
|
||||
std::string cascadeFrontalfilename=cascadefile;
|
||||
cv::Ptr<cv::CascadeClassifier> cascade = new cv::CascadeClassifier(cascadeFrontalfilename);
|
||||
cv::Ptr<DetectionBasedTracker::IDetector> MainDetector = new CascadeDetectorAdapter(cascade);
|
||||
|
||||
cascade = new cv::CascadeClassifier(cascadeFrontalfilename);
|
||||
cv::Ptr<DetectionBasedTracker::IDetector> TrackingDetector = new CascadeDetectorAdapter(cascade);
|
||||
|
||||
DetectionBasedTracker::Parameters params;
|
||||
DetectionBasedTracker fd(MainDetector, TrackingDetector, params);
|
||||
std::string cascadeFrontalfilename=cascadefile;
|
||||
|
||||
DetectionBasedTracker fd(cascadeFrontalfilename, params);
|
||||
|
||||
fd.run();
|
||||
|
||||
@ -136,13 +108,12 @@ static int test_FaceDetector(int argc, char *argv[])
|
||||
double freq=getTickFrequency();
|
||||
|
||||
int num_images=images.size();
|
||||
for(int n=1; n <= num_images; n++)
|
||||
{
|
||||
for(int n=1; n <= num_images; n++) {
|
||||
int64 tcur=getTickCount();
|
||||
int64 dt=tcur-tprev;
|
||||
tprev=tcur;
|
||||
double t_ms=((double)dt)/freq * 1000.0;
|
||||
LOGD("\n\nSTEP n=%d from prev step %f ms\n", n, t_ms);
|
||||
LOGD("\n\nSTEP n=%d from prev step %f ms\n\n", n, t_ms);
|
||||
m=images[n-1];
|
||||
CV_Assert(! m.empty());
|
||||
cvtColor(m, gray, CV_BGR2GRAY);
|
||||
@ -152,8 +123,11 @@ static int test_FaceDetector(int argc, char *argv[])
|
||||
vector<Rect> result;
|
||||
fd.getObjects(result);
|
||||
|
||||
for(size_t i=0; i < result.size(); i++)
|
||||
{
|
||||
|
||||
|
||||
|
||||
|
||||
for(size_t i=0; i < result.size(); i++) {
|
||||
Rect r=result[i];
|
||||
CV_Assert(r.area() > 0);
|
||||
Point tl=r.tl();
|
||||
@ -162,14 +136,14 @@ static int test_FaceDetector(int argc, char *argv[])
|
||||
rectangle(m, tl, br, color, 3);
|
||||
}
|
||||
}
|
||||
|
||||
char outfilename[256];
|
||||
for(int n=1; n <= num_images; n++)
|
||||
{
|
||||
snprintf(outfilename, sizeof(outfilename), outfilepattern, n);
|
||||
LOGD("outfilename='%s'", outfilename);
|
||||
m=images[n-1];
|
||||
imwrite(outfilename, m);
|
||||
char outfilename[256];
|
||||
for(int n=1; n <= num_images; n++) {
|
||||
snprintf(outfilename, sizeof(outfilename), outfilepattern, n);
|
||||
LOGD("outfilename='%s'", outfilename);
|
||||
m=images[n-1];
|
||||
imwrite(outfilename, m);
|
||||
}
|
||||
}
|
||||
|
||||
fd.stop();
|
||||
@ -177,6 +151,8 @@ static int test_FaceDetector(int argc, char *argv[])
|
||||
return 0;
|
||||
}
|
||||
|
||||
|
||||
|
||||
int main(int argc, char *argv[])
|
||||
{
|
||||
return test_FaceDetector(argc, argv);
|
||||
|
||||
Loading…
Reference in New Issue
Block a user