Reverted changes breaking Android build

modules/contrib/include/opencv2/contrib/detection_based_tracker.hpp

@@ -12,66 +12,17 @@ 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
+        DetectionBasedTracker(const std::string& cascadeFilename, const Parameters& params);
-        {
-            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 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);
         virtual ~DetectionBasedTracker();
 
         virtual bool run();
@@ -93,6 +44,7 @@ class DetectionBasedTracker
         cv::Ptr<SeparateDetectionWork> separateDetectionWork;
         friend void* workcycleObjectDetectorFunction(void* p);
 
+
         struct InnerParameters
         {
             int numLastPositionsToTrack;
@@ -138,7 +90,8 @@ 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;

modules/contrib/src/detection_based_tracker.cpp

@@ -52,11 +52,10 @@ static inline cv::Rect scale_rect(const cv::Rect& r, float scale)
 };
 
 void* workcycleObjectDetectorFunction(void* p);
-
 class DetectionBasedTracker::SeparateDetectionWork
 {
     public:
-        SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, cv::Ptr<DetectionBasedTracker::IDetector> _detector);
+        SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, const std::string& cascadeFilename);
         virtual ~SeparateDetectionWork();
         bool communicateWithDetectingThread(const Mat& imageGray, vector<Rect>& rectsWhereRegions);
         bool run();
@@ -78,7 +77,7 @@ class DetectionBasedTracker::SeparateDetectionWork
     protected:
 
         DetectionBasedTracker& detectionBasedTracker;
-        cv::Ptr<DetectionBasedTracker::IDetector> cascadeInThread;
+        cv::CascadeClassifier cascadeInThread;
 
         pthread_t second_workthread;
         pthread_mutex_t mutex;
@@ -106,7 +105,7 @@ class DetectionBasedTracker::SeparateDetectionWork
         long long  timeWhenDetectingThreadStartedWork;
 };
 
-DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, cv::Ptr<DetectionBasedTracker::IDetector> _detector)
+DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork(DetectionBasedTracker& _detectionBasedTracker, const std::string& cascadeFilename)
     :detectionBasedTracker(_detectionBasedTracker),
     cascadeInThread(),
     isObjectDetectingReady(false),
@@ -114,10 +113,9 @@ DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork(DetectionBas
     stateThread(STATE_THREAD_STOPPED),
     timeWhenDetectingThreadStartedWork(-1)
 {
-    CV_Assert(!_detector.empty());
+    if(!cascadeInThread.load(cascadeFilename)) {
-
+        CV_Error(CV_StsBadArg, "DetectionBasedTracker::SeparateDetectionWork::SeparateDetectionWork: Cannot load a cascade from the file '"+cascadeFilename+"'");
-    cascadeInThread = _detector;
+    }
-
     int res=0;
     res=pthread_mutex_init(&mutex, NULL);//TODO: should be attributes?
     if (res) {
@@ -276,17 +274,20 @@ void DetectionBasedTracker::SeparateDetectionWork::workcycleObjectDetector()
 
         int64 t1_detect=getTickCount();
 
-        cascadeInThread->detect(imageSeparateDetecting, objects);
+        int minObjectSize=detectionBasedTracker.parameters.minObjectSize;
+        Size min_objectSize=Size(minObjectSize, minObjectSize);
 
-        /*cascadeInThread.detectMultiScale( imageSeparateDetecting, objects,
+        int maxObjectSize=detectionBasedTracker.parameters.maxObjectSize;
+        Size max_objectSize(maxObjectSize, maxObjectSize);
+
+
+        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()) {
@@ -421,10 +422,16 @@ 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;
@@ -437,32 +444,39 @@ 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.maxTrackLifetime >= 0)
+    CV_Assert( (params.minObjectSize > 0)
-            && (!MainDetector.empty())
+            && (params.maxObjectSize >= 0)
-            && (!TrackingDetector.empty()) );
+            && (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;
 
-    separateDetectionWork = new SeparateDetectionWork(*this, MainDetector);
+    separateDetectionWork=new SeparateDetectionWork(*this, cascadeFilename);
 
     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()) {
@@ -480,9 +494,15 @@ 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 {
@@ -497,6 +517,7 @@ void DetectionBasedTracker::process(const Mat& imageGray)
                 continue;
             }
 
+
             //correction by speed of rectangle
             if (n > 1) {
                 Point2f center=centerRect(r);
@@ -539,7 +560,6 @@ 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();
@@ -554,6 +574,8 @@ void DetectionBasedTracker::getObjects(std::vector<Object>& result) const
     }
 }
 
+
+
 bool DetectionBasedTracker::run()
 {
     return separateDetectionWork->run();
@@ -689,7 +711,6 @@ void DetectionBasedTracker::updateTrackedObjects(const vector<Rect>& detectedObj
         }
     }
 }
-
 Rect DetectionBasedTracker::calcTrackedObjectPositionToShow(int i) const
 {
     if ( (i < 0) || (i >= (int)trackedObjects.size()) ) {
@@ -722,8 +743,8 @@ 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];
+            w+= lastPositions[k].width  * weightsSizesSmoothing[j];
-            h += lastPositions[k].height * weightsSizesSmoothing[j];
+            h+= lastPositions[k].height * weightsSizesSmoothing[j];
             sum+=weightsSizesSmoothing[j];
         }
         w /= sum;
@@ -741,7 +762,7 @@ 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;
@@ -781,7 +802,8 @@ void DetectionBasedTracker::detectInRegion(const Mat& img, const Rect& r, vector
         return;
     }
 
-    int d = cvRound(std::min(r.width, r.height) * innerParameters.coeffObjectSizeToTrack);
+    int d=std::min(r.width, r.height);
+    d=cvRound(d * innerParameters.coeffObjectSizeToTrack);
 
     vector<Rect> tmpobjects;
 
@@ -789,17 +811,17 @@ 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);
 
-    cascadeForTracking->setMinObjectSize(Size(d, d));
+    int maxObjectSize=parameters.maxObjectSize;
-    cascadeForTracking->detect(img1, tmpobjects);
+    Size max_objectSize(maxObjectSize, maxObjectSize);
-            /*
+
-            detectMultiScale( img1, tmpobjects,
+    cascadeForTracking.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());
@@ -809,7 +831,10 @@ void DetectionBasedTracker::detectInRegion(const Mat& img, const Rect& r, vector
 
 bool DetectionBasedTracker::setParameters(const Parameters& params)
 {
-    if ( params.maxTrackLifetime < 0 )
+    if ( (params.minObjectSize <= 0)
+            || (params.maxObjectSize < 0)
+            || (params.scaleFactor <= 1.0)
+            || (params.maxTrackLifetime < 0) )
     {
         LOGE("DetectionBasedTracker::setParameters: ERROR: wrong parameters value");
         return false;

samples/cpp/dbt_face_detection.cpp

@@ -1,104 +0,0 @@
-#if 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

@@ -43,6 +43,8 @@
 #define LOGE(...) do{} while(0)
 #endif
 
+
+
 using namespace cv;
 using namespace std;
 
@@ -61,32 +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):
-            IDetector(),
-            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;
     }
@@ -101,14 +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;
             }
@@ -117,15 +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(cascadeFrontalfilename, params);
-    DetectionBasedTracker fd(MainDetector, TrackingDetector, 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);
+        char outfilename[256];
-        LOGD("outfilename='%s'", outfilename);
+        for(int n=1; n <= num_images; n++) {
-        m=images[n-1];
+            snprintf(outfilename, sizeof(outfilename), outfilepattern, n);
-        imwrite(outfilename, m);
+            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);