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Commit bd901eb5 authored by Andrey Kamaev's avatar Andrey Kamaev
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Reverted r8721 and r8725 (issue #2080)

parent 74707ec7
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Showing with 51 additions and 344 deletions
modules/contrib/include/opencv2/contrib/detection_based_tracker.hpp
View file @ bd901eb5
......@@ -7,73 +7,22 @@
#include <vector>
namespace cv
{
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();
};
class IDetector
{
public:
IDetector():
minObjSize(96, 96),
maxObjSize(INT_MAX, INT_MAX),
minNeighbours(2),
scaleFactor(1.1f)
{}
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 minNeighbours;
}
void setMinNeighbours(int value)
{
minNeighbours = 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);
DetectionBasedTracker(const std::string& cascadeFilename, const Parameters& params);
virtual ~DetectionBasedTracker();
virtual bool run();
......@@ -95,6 +44,7 @@ class DetectionBasedTracker
cv::Ptr<SeparateDetectionWork> separateDetectionWork;
friend void* workcycleObjectDetectorFunction(void* p);
struct InnerParameters
{
int numLastPositionsToTrack;
......@@ -140,11 +90,13 @@ class DetectionBasedTracker
std::vector<float> weightsPositionsSmoothing;
std::vector<float> weightsSizesSmoothing;
cv::Ptr<IDetector> cascadeForTracking;
cv::CascadeClassifier cascadeForTracking;
void updateTrackedObjects(const std::vector<cv::Rect>& detectedObjects);
cv::Rect calcTrackedObjectPositionToShow(int i) const;
void detectInRegion(const cv::Mat& img, const cv::Rect& r, std::vector<cv::Rect>& detectedObjectsInRegions);
};
} //end of cv namespace
#endif
samples/android/face-detection/jni/DetectionBasedTracker_jni.cpp
View file @ bd901eb5
......@@ -18,53 +18,6 @@ inline void vector_Rect_to_Mat(vector<Rect>& v_rect, Mat& mat)
mat = Mat(v_rect, true);
}
class CascadeDetectorAdapter: public DetectionBasedTracker::IDetector
{
public:
CascadeDetectorAdapter(cv::Ptr<cv::CascadeClassifier> detector):
IDetector(),
Detector(detector)
{
LOGD("CascadeDetectorAdapter::Detect::Detect");
CV_Assert(!detector.empty());
}
void detect(const cv::Mat &Image, std::vector<cv::Rect> &objects)
{
LOGD("CascadeDetectorAdapter::Detect: begin");
LOGD("CascadeDetectorAdapter::Detect: scaleFactor=%.2f, minNeighbours=%d, minObjSize=(%dx%d), maxObjSize=(%dx%d)", scaleFactor, minNeighbours, minObjSize.width, minObjSize.height, maxObjSize.width, maxObjSize.height);
Detector->detectMultiScale(Image, objects, scaleFactor, minNeighbours, 0, minObjSize, maxObjSize);
LOGD("CascadeDetectorAdapter::Detect: end");
}
virtual ~CascadeDetectorAdapter()
{
LOGD("CascadeDetectorAdapter::Detect::~Detect");
}
private:
CascadeDetectorAdapter();
cv::Ptr<cv::CascadeClassifier> Detector;
};
struct DetectorAgregator
{
cv::Ptr<CascadeDetectorAdapter> mainDetector;
cv::Ptr<CascadeDetectorAdapter> trackingDetector;
cv::Ptr<DetectionBasedTracker> tracker;
DetectorAgregator(cv::Ptr<CascadeDetectorAdapter>& _mainDetector, cv::Ptr<CascadeDetectorAdapter>& _trackingDetector):
mainDetector(_mainDetector),
trackingDetector(_trackingDetector)
{
CV_Assert(!_mainDetector.empty());
CV_Assert(!_trackingDetector.empty());
DetectionBasedTracker::Parameters DetectorParams;
tracker = new DetectionBasedTracker(mainDetector.ptr<DetectionBasedTracker::IDetector>(), trackingDetector.ptr<DetectionBasedTracker::IDetector>(), DetectorParams);
}
};
JNIEXPORT jlong JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeCreateObject
(JNIEnv * jenv, jclass, jstring jFileName, jint faceSize)
{
......@@ -72,18 +25,12 @@ JNIEXPORT jlong JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeC
string stdFileName(jnamestr);
jlong result = 0;
LOGD("Java_org_opencv_samples_fd_DetectionBasedTracker_nativeCreateObject");
try
{
cv::Ptr<CascadeDetectorAdapter> mainDetector = new CascadeDetectorAdapter(new CascadeClassifier(stdFileName));
cv::Ptr<CascadeDetectorAdapter> trackingDetector = new CascadeDetectorAdapter(new CascadeClassifier(stdFileName));
result = (jlong)new DetectorAgregator(mainDetector, trackingDetector);
DetectionBasedTracker::Parameters DetectorParams;
if (faceSize > 0)
{
mainDetector->setMinObjectSize(Size(faceSize, faceSize));
//trackingDetector->setMinObjectSize(Size(faceSize, faceSize));
}
DetectorParams.minObjectSize = faceSize;
result = (jlong)new DetectionBasedTracker(stdFileName, DetectorParams);
}
catch(cv::Exception e)
{
......@@ -97,7 +44,7 @@ JNIEXPORT jlong JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeC
{
LOGD("nativeCreateObject catched unknown exception");
jclass je = jenv->FindClass("java/lang/Exception");
jenv->ThrowNew(je, "Unknown exception in JNI code {Java_org_opencv_samples_fd_DetectionBasedTracker_nativeCreateObject(...)}");
jenv->ThrowNew(je, "Unknown exception in JNI code {highgui::VideoCapture_n_1VideoCapture__()}");
return 0;
}
......@@ -107,12 +54,10 @@ JNIEXPORT jlong JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeC
JNIEXPORT void JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeDestroyObject
(JNIEnv * jenv, jclass, jlong thiz)
{
LOGD("Java_org_opencv_samples_fd_DetectionBasedTracker_nativeDestroyObject");
try
{
((DetectorAgregator*)thiz)->tracker->stop();
delete (DetectorAgregator*)thiz;
((DetectionBasedTracker*)thiz)->stop();
delete (DetectionBasedTracker*)thiz;
}
catch(cv::Exception e)
{
......@@ -126,18 +71,16 @@ JNIEXPORT void JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeDe
{
LOGD("nativeDestroyObject catched unknown exception");
jclass je = jenv->FindClass("java/lang/Exception");
jenv->ThrowNew(je, "Unknown exception in JNI code {Java_org_opencv_samples_fd_DetectionBasedTracker_nativeDestroyObject(...)}");
jenv->ThrowNew(je, "Unknown exception in JNI code {highgui::VideoCapture_n_1VideoCapture__()}");
}
}
JNIEXPORT void JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeStart
(JNIEnv * jenv, jclass, jlong thiz)
{
LOGD("Java_org_opencv_samples_fd_DetectionBasedTracker_nativeStart");
try
{
((DetectorAgregator*)thiz)->tracker->run();
((DetectionBasedTracker*)thiz)->run();
}
catch(cv::Exception e)
{
......@@ -151,18 +94,16 @@ JNIEXPORT void JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeSt
{
LOGD("nativeStart catched unknown exception");
jclass je = jenv->FindClass("java/lang/Exception");
jenv->ThrowNew(je, "Unknown exception in JNI code {Java_org_opencv_samples_fd_DetectionBasedTracker_nativeStart(...)}");
jenv->ThrowNew(je, "Unknown exception in JNI code {highgui::VideoCapture_n_1VideoCapture__()}");
}
}
JNIEXPORT void JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeStop
(JNIEnv * jenv, jclass, jlong thiz)
{
LOGD("Java_org_opencv_samples_fd_DetectionBasedTracker_nativeStop");
try
{
((DetectorAgregator*)thiz)->tracker->stop();
((DetectionBasedTracker*)thiz)->stop();
}
catch(cv::Exception e)
{
......@@ -176,22 +117,23 @@ JNIEXPORT void JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeSt
{
LOGD("nativeStop catched unknown exception");
jclass je = jenv->FindClass("java/lang/Exception");
jenv->ThrowNew(je, "Unknown exception in JNI code {Java_org_opencv_samples_fd_DetectionBasedTracker_nativeStop(...)}");
jenv->ThrowNew(je, "Unknown exception in JNI code {highgui::VideoCapture_n_1VideoCapture__()}");
}
}
JNIEXPORT void JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeSetFaceSize
(JNIEnv * jenv, jclass, jlong thiz, jint faceSize)
{
LOGD("Java_org_opencv_samples_fd_DetectionBasedTracker_nativeSetFaceSize -- BEGIN");
try
{
if (faceSize > 0)
{
((DetectorAgregator*)thiz)->mainDetector->setMinObjectSize(Size(faceSize, faceSize));
//((DetectorAgregator*)thiz)->trackingDetector->setMinObjectSize(Size(faceSize, faceSize));
DetectionBasedTracker::Parameters DetectorParams = \
((DetectionBasedTracker*)thiz)->getParameters();
DetectorParams.minObjectSize = faceSize;
((DetectionBasedTracker*)thiz)->setParameters(DetectorParams);
}
}
catch(cv::Exception e)
{
......@@ -205,23 +147,20 @@ JNIEXPORT void JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeSe
{
LOGD("nativeSetFaceSize catched unknown exception");
jclass je = jenv->FindClass("java/lang/Exception");
jenv->ThrowNew(je, "Unknown exception in JNI code {Java_org_opencv_samples_fd_DetectionBasedTracker_nativeSetFaceSize(...)}");
jenv->ThrowNew(je, "Unknown exception in JNI code {highgui::VideoCapture_n_1VideoCapture__()}");
}
LOGD("Java_org_opencv_samples_fd_DetectionBasedTracker_nativeSetFaceSize -- END");
}
JNIEXPORT void JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeDetect
(JNIEnv * jenv, jclass, jlong thiz, jlong imageGray, jlong faces)
{
LOGD("Java_org_opencv_samples_fd_DetectionBasedTracker_nativeDetect");
try
{
vector<Rect> RectFaces;
((DetectorAgregator*)thiz)->tracker->process(*((Mat*)imageGray));
((DetectorAgregator*)thiz)->tracker->getObjects(RectFaces);
*((Mat*)faces) = Mat(RectFaces, true);
((DetectionBasedTracker*)thiz)->process(*((Mat*)imageGray));
((DetectionBasedTracker*)thiz)->getObjects(RectFaces);
vector_Rect_to_Mat(RectFaces, *((Mat*)faces));
}
catch(cv::Exception e)
{
......@@ -235,7 +174,6 @@ JNIEXPORT void JNICALL Java_org_opencv_samples_fd_DetectionBasedTracker_nativeDe
{
LOGD("nativeDetect catched unknown exception");
jclass je = jenv->FindClass("java/lang/Exception");
jenv->ThrowNew(je, "Unknown exception in JNI code {Java_org_opencv_samples_fd_DetectionBasedTracker_nativeDetect(...)}");
jenv->ThrowNew(je, "Unknown exception in JNI code {highgui::VideoCapture_n_1VideoCapture__()}");
}
LOGD("Java_org_opencv_samples_fd_DetectionBasedTracker_nativeDetect END");
}
\ No newline at end of file
samples/cpp/CMakeLists.txt
View file @ bd901eb5
......@@ -3,7 +3,7 @@
#
# ----------------------------------------------------------------------------
SET(OPENCV_CPP_SAMPLES_REQUIRED_DEPS opencv_core_vision_api opencv_core opencv_flann opencv_imgproc
SET(OPENCV_CPP_SAMPLES_REQUIRED_DEPS opencv_core opencv_flann opencv_imgproc
opencv_highgui opencv_ml opencv_video opencv_objdetect opencv_photo opencv_nonfree
opencv_features2d opencv_calib3d opencv_legacy opencv_contrib opencv_stitching opencv_videostab)
......
samples/cpp/core_vision_tracking_image.cpp deleted 100644 → 0
View file @ 74707ec7
#include <opencv2/core/core.hpp> // Basic OpenCV structures (cv::Mat, Scalar)
#include <opencv2/highgui/highgui.hpp> // OpenCV window I/O
#include <opencv2/core_vision_api/tracker.hpp>
#include <stdio.h>
#include <string>
#include <vector>
using namespace std;
using namespace cv;
const string WindowName = "Face Detection example";
const Scalar RectColor = CV_RGB(0,255,0);
int main()
{
namedWindow(WindowName);
cv::moveWindow(WindowName, 100, 100);
Mat Viewport;
Mat ReferenceFrame = imread("board.jpg");
if (ReferenceFrame.empty())
{
printf("Error: Cannot load input image\n");
return 1;
}
cv::Ptr<nv::Tracker> tracker = nv::Algorithm::create<nv::Tracker>("nv::Tracker::OpticalFlow");
tracker->initialize();
// First frame for initialization
tracker->feed(ReferenceFrame);
nv::Tracker::TrackedObjectHandler obj = tracker->addObject(cv::Rect(100,100, 200, 200));
while(true)
{
tracker->feed(ReferenceFrame);
if (obj->getStatus() == nv::Tracker::LOST_STATUS)
break;
cv::Rect currentLocation = obj->getLocation();
ReferenceFrame.copyTo(Viewport);
rectangle(Viewport, currentLocation, RectColor);
imshow(WindowName, Viewport);
if (cvWaitKey(30) >= 0) break;
}
return 0;
}
samples/cpp/dbt_face_detection.cpp deleted 100644 → 0
View file @ 74707ec7
#if 0 //defined(__linux__) || defined(LINUX) || defined(__APPLE__) || defined(ANDROID)
#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):
IDetector(),
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;
}
#else
#include <stdio.h>
int main()
{
printf("This sample works for UNIX or ANDROID only\n");
return 0;
}
#endif
samples/cpp/detection_based_tracker_sample.cpp
View file @ bd901eb5
......@@ -43,6 +43,8 @@
#define LOGE(...) do{} while(0)
#endif
using namespace cv;
using namespace std;
......@@ -61,31 +63,9 @@ 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;
}
......@@ -100,14 +80,12 @@ 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;
}
......@@ -116,15 +94,10 @@ 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::Parameters params;
DetectionBasedTracker fd(MainDetector, TrackingDetector, params);
DetectionBasedTracker fd(cascadeFrontalfilename, params);
fd.run();
......@@ -135,13 +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);
......@@ -151,8 +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();
......@@ -161,21 +136,23 @@ 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);
}
}
fd.stop();
return 0;
}
int main(int argc, char *argv[])
{
return test_FaceDetector(argc, argv);
......
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