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Commit 7c160cdc authored by Alexander Smorkalov's avatar Alexander Smorkalov
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Detection based tracker was refactored. Detector interface added.

parent a20837fb
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Showing with 224 additions and 89 deletions
modules/contrib/include/opencv2/contrib/detection_based_tracker.hpp
View file @ 7c160cdc
......@@ -12,17 +12,66 @@ class DetectionBasedTracker
public:
struct Parameters
{
int minObjectSize;
int maxObjectSize;
double scaleFactor;
int maxTrackLifetime;
int minNeighbors;
int minDetectionPeriod; //the minimal time between run of the big object detector (on the whole frame) in ms (1000 mean 1 sec), default=0
Parameters();
};
DetectionBasedTracker(const std::string& cascadeFilename, const Parameters& params);
class IDetector
{
public:
IDetector():
MinObjSize(96, 96),
MaxObjSize(INT_MAX, INT_MAX),
ScaleFactor(1.1f),
MinNeighbours(2)
{}
virtual void detect(const cv::Mat& Image, std::vector<cv::Rect>& objects) = 0;
void setMinObjectSize(const cv::Size& min)
{
MinObjSize = min;
}
void setMaxObjectSize(const cv::Size& max)
{
MaxObjSize = max;
}
cv::Size getMinObjectSize() const
{
return MinObjSize;
}
cv::Size getMaxObjectSize() const
{
return MaxObjSize;
}
float getScaleFactor()
{
return ScaleFactor;
}
void setScaleFactor(float value)
{
ScaleFactor = value;
}
int getMinNeighbours()
{
return ScaleFactor;
}
void setMinNeighbours(int value)
{
}
virtual ~IDetector() {}
protected:
cv::Size MinObjSize;
cv::Size MaxObjSize;
int MinNeighbours;
float ScaleFactor;
};
DetectionBasedTracker(cv::Ptr<IDetector> MainDetector, cv::Ptr<IDetector> TrackingDetector, const Parameters& params);
virtual ~DetectionBasedTracker();
virtual bool run();
......@@ -44,7 +93,6 @@ class DetectionBasedTracker
cv::Ptr<SeparateDetectionWork> separateDetectionWork;
friend void* workcycleObjectDetectorFunction(void* p);
struct InnerParameters
{
int numLastPositionsToTrack;
......@@ -90,8 +138,7 @@ class DetectionBasedTracker
std::vector<float> weightsPositionsSmoothing;
std::vector<float> weightsSizesSmoothing;
cv::CascadeClassifier cascadeForTracking;
cv::Ptr<IDetector> cascadeForTracking;
void updateTrackedObjects(const std::vector<cv::Rect>& detectedObjects);
cv::Rect calcTrackedObjectPositionToShow(int i) const;
......
modules/contrib/src/detection_based_tracker.cpp
View file @ 7c160cdc
......@@ -52,10 +52,11 @@ static inline cv::Rect scale_rect(const cv::Rect& r, float scale)
};
void* workcycleObjectDetectorFunction(void* p);
class DetectionBasedTracker::SeparateDetectionWork
{
public:
SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, const std::string& cascadeFilename);
SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, cv::Ptr<DetectionBasedTracker::IDetector> _detector);
virtual ~SeparateDetectionWork();
bool communicateWithDetectingThread(const Mat& imageGray, vector<Rect>& rectsWhereRegions);
bool run();
......@@ -77,7 +78,7 @@ class DetectionBasedTracker::SeparateDetectionWork
protected:
DetectionBasedTracker& detectionBasedTracker;
cv::CascadeClassifier cascadeInThread;
cv::Ptr<DetectionBasedTracker::IDetector> cascadeInThread;
pthread_t second_workthread;
pthread_mutex_t mutex;
......@@ -105,7 +106,7 @@ class DetectionBasedTracker::SeparateDetectionWork
long long timeWhenDetectingThreadStartedWork;
};
DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, const std::string& cascadeFilename)
DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, cv::Ptr<DetectionBasedTracker::IDetector> _detector)
:detectionBasedTracker(_detectionBasedTracker),
cascadeInThread(),
isObjectDetectingReady(false),
......@@ -113,9 +114,10 @@ DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork(DetectionBas
stateThread(STATE_THREAD_STOPPED),
timeWhenDetectingThreadStartedWork(-1)
{
if(!cascadeInThread.load(cascadeFilename)) {
CV_Error(CV_StsBadArg, "DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork: Cannot load a cascade from the file '"+cascadeFilename+"'");
}
CV_Assert(!_detector.empty());
cascadeInThread = _detector;
int res=0;
res=pthread_mutex_init(&mutex, NULL);//TODO: should be attributes?
if (res) {
......@@ -274,20 +276,17 @@ void DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector()
int64 t1_detect=getTickCount();
int minObjectSize=detectionBasedTracker.parameters.minObjectSize;
Size min_objectSize=Size(minObjectSize, minObjectSize);
cascadeInThread->detect(imageSeparateDetecting, objects);
int maxObjectSize=detectionBasedTracker.parameters.maxObjectSize;
Size max_objectSize(maxObjectSize, maxObjectSize);
cascadeInThread.detectMultiScale( imageSeparateDetecting, objects,
/*cascadeInThread.detectMultiScale( imageSeparateDetecting, objects,
detectionBasedTracker.parameters.scaleFactor, detectionBasedTracker.parameters.minNeighbors, 0
|CV_HAAR_SCALE_IMAGE
,
min_objectSize,
max_objectSize
);
*/
LOGD("DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector() --- end handling imageSeparateDetecting");
if (!isWorking()) {
......@@ -422,16 +421,10 @@ bool DetectionBasedTracker::SeparateDetectionWork::communicateWithDetectingThrea
DetectionBasedTracker::Parameters::Parameters()
{
minObjectSize=96;
maxObjectSize=INT_MAX;
scaleFactor=1.1;
maxTrackLifetime=5;
minNeighbors=2;
minDetectionPeriod=0;
}
DetectionBasedTracker::InnerParameters::InnerParameters()
{
numLastPositionsToTrack=4;
......@@ -444,39 +437,32 @@ DetectionBasedTracker::InnerParameters::InnerParameters()
coeffObjectSpeedUsingInPrediction=0.8;
}
DetectionBasedTracker::DetectionBasedTracker(const std::string& cascadeFilename, const Parameters& params)
DetectionBasedTracker::DetectionBasedTracker(cv::Ptr<IDetector> MainDetector, cv::Ptr<IDetector> TrackingDetector, const Parameters& params)
:separateDetectionWork(),
innerParameters(),
cascadeForTracking(TrackingDetector),
parameters(params),
numTrackedSteps(0)
{
CV_Assert( (params.minObjectSize > 0)
&& (params.maxObjectSize >= 0)
&& (params.scaleFactor > 1.0)
&& (params.maxTrackLifetime >= 0) );
if (!cascadeForTracking.load(cascadeFilename)) {
CV_Error(CV_StsBadArg, "DetectionBasedTracker::DetectionBasedTracker: Cannot load a cascade from the file '"+cascadeFilename+"'");
}
parameters=params;
CV_Assert( (params.maxTrackLifetime >= 0)
&& (!MainDetector.empty())
&& (!TrackingDetector.empty()) );
separateDetectionWork=new SeparateDetectionWork(*this, cascadeFilename);
separateDetectionWork = new SeparateDetectionWork(*this, MainDetector);
weightsPositionsSmoothing.push_back(1);
weightsSizesSmoothing.push_back(0.5);
weightsSizesSmoothing.push_back(0.3);
weightsSizesSmoothing.push_back(0.2);
}
DetectionBasedTracker::~DetectionBasedTracker()
{
}
void DetectionBasedTracker::process(const Mat& imageGray)
{
CV_Assert(imageGray.type()==CV_8UC1);
if (!separateDetectionWork->isWorking()) {
......@@ -494,15 +480,9 @@ void DetectionBasedTracker::process(const Mat& imageGray)
Mat imageDetect=imageGray;
int D=parameters.minObjectSize;
if (D < 1)
D=1;
vector<Rect> rectsWhereRegions;
bool shouldHandleResult=separateDetectionWork->communicateWithDetectingThread(imageGray, rectsWhereRegions);
if (shouldHandleResult) {
LOGD("DetectionBasedTracker::process: get _rectsWhereRegions were got from resultDetect");
} else {
......@@ -517,7 +497,6 @@ void DetectionBasedTracker::process(const Mat& imageGray)
continue;
}
//correction by speed of rectangle
if (n > 1) {
Point2f center=centerRect(r);
......@@ -560,6 +539,7 @@ void DetectionBasedTracker::getObjects(std::vector<cv::Rect>& result) const
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);
}
}
void DetectionBasedTracker::getObjects(std::vector<Object>& result) const
{
result.clear();
......@@ -574,8 +554,6 @@ void DetectionBasedTracker::getObjects(std::vector<Object>& result) const
}
}
bool DetectionBasedTracker::run()
{
return separateDetectionWork->run();
......@@ -711,6 +689,7 @@ void DetectionBasedTracker::updateTrackedObjects(const vector<Rect>& detectedObj
}
}
}
Rect DetectionBasedTracker::calcTrackedObjectPositionToShow(int i) const
{
if ( (i < 0) || (i >= (int)trackedObjects.size()) ) {
......@@ -743,8 +722,8 @@ Rect DetectionBasedTracker::calcTrackedObjectPositionToShow(int i) const
double sum=0;
for(int j=0; j < Nsize; j++) {
int k=N-j-1;
w+= lastPositions[k].width * weightsSizesSmoothing[j];
h+= lastPositions[k].height * weightsSizesSmoothing[j];
w += lastPositions[k].width * weightsSizesSmoothing[j];
h += lastPositions[k].height * weightsSizesSmoothing[j];
sum+=weightsSizesSmoothing[j];
}
w /= sum;
......@@ -762,7 +741,7 @@ Rect DetectionBasedTracker::calcTrackedObjectPositionToShow(int i) const
Point br(lastPositions[k].br());
Point2f c1;
c1=tl;
c1=c1* 0.5f;
c1=c1* 0.5f;
Point2f c2;
c2=br;
c2=c2*0.5f;
......@@ -802,8 +781,7 @@ void DetectionBasedTracker::detectInRegion(const Mat& img, const Rect& r, vector
return;
}
int d=std::min(r.width, r.height);
d=cvRound(d * innerParameters.coeffObjectSizeToTrack);
int d = cvRound(std::min(r.width, r.height) * innerParameters.coeffObjectSizeToTrack);
vector<Rect> tmpobjects;
......@@ -811,17 +789,17 @@ void DetectionBasedTracker::detectInRegion(const Mat& img, const Rect& r, vector
LOGD("DetectionBasedTracker::detectInRegion: img1.size()=%d x %d, d=%d",
img1.size().width, img1.size().height, d);
int maxObjectSize=parameters.maxObjectSize;
Size max_objectSize(maxObjectSize, maxObjectSize);
cascadeForTracking.detectMultiScale( img1, tmpobjects,
cascadeForTracking->setMinObjectSize(Size(d, d));
cascadeForTracking->detect(img1, tmpobjects);
/*
detectMultiScale( img1, tmpobjects,
parameters.scaleFactor, parameters.minNeighbors, 0
|CV_HAAR_FIND_BIGGEST_OBJECT
|CV_HAAR_SCALE_IMAGE
,
Size(d,d),
max_objectSize
);
);*/
for(size_t i=0; i < tmpobjects.size(); i++) {
Rect curres(tmpobjects[i].tl() + r1.tl(), tmpobjects[i].size());
......@@ -831,10 +809,7 @@ void DetectionBasedTracker::detectInRegion(const Mat& img, const Rect& r, vector
bool DetectionBasedTracker::setParameters(const Parameters& params)
{
if ( (params.minObjectSize <= 0)
|| (params.maxObjectSize < 0)
|| (params.scaleFactor <= 1.0)
|| (params.maxTrackLifetime < 0) )
if ( params.maxTrackLifetime < 0 )
{
LOGE("DetectionBasedTracker::setParameters: ERROR: wrong parameters value");
return false;
......
samples/cpp/dbt_face_detection.cpp 0 → 100644
View file @ 7c160cdc
#include <opencv2/imgproc/imgproc.hpp> // Gaussian Blur
#include <opencv2/core/core.hpp> // Basic OpenCV structures (cv::Mat, Scalar)
#include <opencv2/highgui/highgui.hpp> // OpenCV window I/O
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/contrib/detection_based_tracker.hpp>
#include <stdio.h>
#include <string>
#include <vector>
using namespace std;
using namespace cv;
const string WindowName = "Face Detection example";
class CascadeDetectorAdapter: public DetectionBasedTracker::IDetector
{
public:
CascadeDetectorAdapter(cv::Ptr<cv::CascadeClassifier> detector):
Detector(detector)
{
CV_Assert(!detector.empty());
}
void detect(const cv::Mat &Image, std::vector<cv::Rect> &objects)
{
Detector->detectMultiScale(Image, objects, ScaleFactor, MinNeighbours, 0, MinObjSize, MaxObjSize);
}
virtual ~CascadeDetectorAdapter()
{}
private:
CascadeDetectorAdapter();
cv::Ptr<cv::CascadeClassifier> Detector;
};
int main(int argc, char* argv[])
{
namedWindow(WindowName);
VideoCapture VideoStream(0);
if (!VideoStream.isOpened())
{
printf("Error: Cannot open video stream from camera\n");
return 1;
}
std::string cascadeFrontalfilename = "../../data/lbpcascades/lbpcascade_frontalface.xml";
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 Detector(MainDetector, TrackingDetector, params);
if (!Detector.run())
{
printf("Error: Detector initialization failed\n");
return 2;
}
Mat ReferenceFrame;
Mat GrayFrame;
vector<Rect> Faces;
while(true)
{
VideoStream >> ReferenceFrame;
cvtColor(ReferenceFrame, GrayFrame, COLOR_RGB2GRAY);
Detector.process(GrayFrame);
Detector.getObjects(Faces);
for (size_t i = 0; i < Faces.size(); i++)
{
rectangle(ReferenceFrame, Faces[i], CV_RGB(0,255,0));
}
imshow(WindowName, ReferenceFrame);
if (cvWaitKey(30) >= 0) break;
}
Detector.stop();
return 0;
}
samples/cpp/detection_based_tracker_sample.cpp
View file @ 7c160cdc
......@@ -43,8 +43,6 @@
#define LOGE(...) do{} while(0)
#endif
using namespace cv;
using namespace std;
......@@ -63,9 +61,31 @@ static void usage()
LOGE0("\t (e.g.\"opencv/data/lbpcascades/lbpcascade_frontalface.xml\" ");
}
class CascadeDetectorAdapter: public DetectionBasedTracker::IDetector
{
public:
CascadeDetectorAdapter(cv::Ptr<cv::CascadeClassifier> detector):
Detector(detector)
{
CV_Assert(!detector.empty());
}
void detect(const cv::Mat &Image, std::vector<cv::Rect> &objects)
{
Detector->detectMultiScale(Image, objects, 1.1, 3, 0, MinObjSize, MaxObjSize);
}
virtual ~CascadeDetectorAdapter()
{}
private:
CascadeDetectorAdapter();
cv::Ptr<cv::CascadeClassifier> Detector;
};
static int test_FaceDetector(int argc, char *argv[])
{
if (argc < 4) {
if (argc < 4)
{
usage();
return -1;
}
......@@ -80,12 +100,14 @@ static int test_FaceDetector(int argc, char *argv[])
vector<Mat> images;
{
char filename[256];
for(int n=1; ; n++) {
for(int n=1; ; n++)
{
snprintf(filename, sizeof(filename), filepattern, n);
LOGD("filename='%s'", filename);
Mat m0;
m0=imread(filename);
if (m0.empty()) {
if (m0.empty())
{
LOGI0("Cannot read the file --- break");
break;
}
......@@ -94,10 +116,15 @@ static int test_FaceDetector(int argc, char *argv[])
LOGD("read %d images", (int)images.size());
}
DetectionBasedTracker::Parameters params;
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 fd(cascadeFrontalfilename, params);
DetectionBasedTracker::Parameters params;
DetectionBasedTracker fd(MainDetector, TrackingDetector, params);
fd.run();
......@@ -108,12 +135,13 @@ 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", n, t_ms);
LOGD("\n\nSTEP n=%d from prev step %f ms\n", n, t_ms);
m=images[n-1];
CV_Assert(! m.empty());
cvtColor(m, gray, CV_BGR2GRAY);
......@@ -123,11 +151,8 @@ 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();
......@@ -136,14 +161,14 @@ 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++)
{
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);
}
snprintf(outfilename, sizeof(outfilename), outfilepattern, n);
LOGD("outfilename='%s'", outfilename);
m=images[n-1];
imwrite(outfilename, m);
}
fd.stop();
......@@ -151,8 +176,6 @@ static int test_FaceDetector(int argc, char *argv[])
return 0;
}
int main(int argc, char *argv[])
{
return test_FaceDetector(argc, argv);
......
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