int main(int argc, char **argv)
{
std::cout << "Using OpenCV " << CV_MAJOR_VERSION << "." << CV_MINOR_VERSION << "." << CV_SUBMINOR_VERSION << std::endl;
/* Open video file */
CvCapture *capture = 0;
capture = cvCaptureFromAVI("dataset/jakomali.mp4"); //video.avi
if(!capture){
std::cerr << "Cannot open video!" << std::endl;
return 1;
}
/* Background Subtraction Algorithm */
IBGS *bgs;
bgs = new PixelBasedAdaptiveSegmenter;
/* Blob Tracking Algorithm */
cv::Mat img_blob;
BlobTracking* blobTracking;
blobTracking = new BlobTracking;
/* Vehicle Counting Algorithm */
VehicleCouting* vehicleCouting;
vehicleCouting = new VehicleCouting;
std::cout << "Press 'q' to quit..." << std::endl;
int key = 0;
IplImage *frame;
while(key != 'q')
{
frame = cvQueryFrame(capture);
if(!frame) break;
cv::Mat img_input(frame);
//cv::imshow("Input", img_input); // input video
cv::Mat img_mask;
bgs->process(img_input, img_mask);
if(!img_mask.empty())
{
// Perform blob tracking
blobTracking->process(img_input, img_mask, img_blob);
// Perform vehicle counting
vehicleCouting->setInput(img_blob);
vehicleCouting->setTracks(blobTracking->getTracks());
vehicleCouting->process();
}
key = cvWaitKey(1);
}
delete vehicleCouting;
delete blobTracking;
delete bgs;
cvDestroyAllWindows();
cvReleaseCapture(&capture);
return 0;
}
int main(int argc, char **argv)
{
CvCapture *capture = 0;
capture = cvCaptureFromAVI("./dataset/video.avi");
if(!capture)
{
std::cerr << "Cannot open video!" << std::endl;
return 1;
}
cascade = (CvHaarClassifierCascade*) cvLoad("cars3.xml");
storage = cvCreateMemStorage(0);
assert(cascade && storage && capture);
ofstream myfile;
myfile.open ("Statistics.dat");
int resize_factor = 100; // 50% of original image
int sec=0; // Storing time temporarily
char buff[DTTMSZ]; // Buffer of size 10 for storing seconds
sec=atoi(getDtTm(buff)); // Storing corrent time
IplImage *frame_aux = cvQueryFrame(capture);
IplImage *frame = cvCreateImage(cvSize((int)((frame_aux->width*resize_factor)/100) , (int)((frame_aux->height*resize_factor)/100)), frame_aux->depth, frame_aux->nChannels);
// Initializing Background Subtraction Methods
IBGS *bgs;
bgs = new PixelBasedAdaptiveSegmenter;
// Initializing Blob Tracking
cv::Mat img_blob;
BlobTracking* blobTracking;
blobTracking = new BlobTracking;
// Initializing Vehicle Counting Algorithm
VehicleCouting* vehicleCouting;
vehicleCouting = new VehicleCouting;
int key = 0;
while(key != 'q')
{
frame_aux = cvQueryFrame(capture);
if(!frame_aux) break;
cvResize(frame_aux, frame);
cv::Mat img_input(frame);
cv::imshow("input", img_input);
// bgs->process(...) method internally shows the foreground mask image
cv::Mat img_mask;
bgs->process(img_input, img_mask);
if(!img_mask.empty())
{
// Blob tracking each frame
blobTracking->process(img_input, img_mask, img_blob);
// Vehicle counting in each frame
vehicleCouting->setInput(img_blob);
vehicleCouting->setTracks(blobTracking->getTracks());
vehicleCouting->process();
// Haar Classification
detect(frame);
//Writing data to a file
myfile <<(((atoi(getDtTm(buff))-sec)< 0) ?(atoi(getDtTm(buff))+ 60 -sec):(atoi(getDtTm(buff))-sec))<< "\t" <<(vehicleCouting->countAB +vehicleCouting->countBA) << "\n" ;
}
key = cvWaitKey(1);
}
delete vehicleCouting;
delete blobTracking;
delete bgs;
cvDestroyAllWindows();
cvReleaseCapture(&capture);
cvReleaseHaarClassifierCascade(&cascade);
cvReleaseMemStorage(&storage);
cvReleaseImage(&frame);
myfile.close();
return 0;
}
int mainDemo2()
{
std::cout << "Using OpenCV " << CV_MAJOR_VERSION << "." << CV_MINOR_VERSION << "." << CV_SUBMINOR_VERSION << std::endl;
/* Background Subtraction Methods */
IBGS *bgs;
/*** Default Package ***/
bgs = new FrameDifferenceBGS;
// bgs = new StaticFrameDifferenceBGS;
//bgs = new WeightedMovingMeanBGS;
//bgs = new WeightedMovingVarianceBGS;
//bgs = new MixtureOfGaussianV1BGS;
//bgs = new MixtureOfGaussianV2BGS;
//bgs = new AdaptiveBackgroundLearning;
//bgs = new AdaptiveSelectiveBackgroundLearning;
//bgs = new GMG;
/*** DP Package (thanks to Donovan Parks) ***/
//bgs = new DPAdaptiveMedianBGS;
//bgs = new DPGrimsonGMMBGS;
//bgs = new DPZivkovicAGMMBGS;
//bgs = new DPMeanBGS;
//bgs = new DPWrenGABGS;
//bgs = new DPPratiMediodBGS;
//bgs = new DPEigenbackgroundBGS;
//bgs = new DPTextureBGS;
/*** TB Package (thanks to Thierry Bouwmans, Fida EL BAF and Zhenjie Zhao) ***/
//bgs = new T2FGMM_UM;
//bgs = new T2FGMM_UV;
//bgs = new T2FMRF_UM;
//bgs = new T2FMRF_UV;
//bgs = new FuzzySugenoIntegral;
//bgs = new FuzzyChoquetIntegral;
/*** JMO Package (thanks to Jean-Marc Odobez) ***/
//bgs = new MultiLayerBGS;
/*** PT Package (thanks to Martin Hofmann, Philipp Tiefenbacher and Gerhard Rigoll) ***/
//bgs = new PixelBasedAdaptiveSegmenter;
/*** LB Package (thanks to Laurence Bender) ***/
//bgs = new LBSimpleGaussian;
//bgs = new LBFuzzyGaussian;
//bgs = new LBMixtureOfGaussians;
//bgs = new LBAdaptiveSOM;
//bgs = new LBFuzzyAdaptiveSOM;
/*** LBP-MRF Package (thanks to Csaba Kertész) ***/
//bgs = new LbpMrf;
/*** AV Package (thanks to Lionel Robinault and Antoine Vacavant) ***/
//bgs = new VuMeter;
/*** EG Package (thanks to Ahmed Elgammal) ***/
//bgs = new KDE;
/*** DB Package (thanks to Domenico Daniele Bloisi) ***/
//bgs = new IndependentMultimodalBGS;
/*** SJN Package (thanks to SeungJong Noh) ***/
//bgs = new SJN_MultiCueBGS;
/*** BL Package (thanks to Benjamin Laugraud) ***/
//bgs = new SigmaDeltaBGS;
/*** PL Package (thanks to Pierre-Luc) ***/
// bgs = new SuBSENSEBGS();
//bgs = new LOBSTERBGS();
int frameNumber = 1;
int key = 0;
cvNamedWindow("input",0);
while(key != 'q')
{
std::stringstream ss;
ss << frameNumber;
std::string fileName = "../qt_bgslibrary/frames/" + ss.str() + ".png";
std::cout << "reading " << fileName << std::endl;
cv::Mat img_input = cv::imread(fileName, CV_LOAD_IMAGE_COLOR);
if (img_input.empty())
break;
cv::imshow("input", img_input);
cv::Mat img_mask;
cv::Mat img_bkgmodel;
std::cout<<" process start ..............."<<std::endl;
bgs->process(img_input, img_mask, img_bkgmodel); // by default, it shows automatically the foreground mask image
std::cout<<" process end ..............."<<std::endl;
//if(!img_mask.empty())
// cv::imshow("Foreground", img_mask);
// do something
key = cvWaitKey(33);
frameNumber++;
}
cvWaitKey(0);
delete bgs;
cvDestroyAllWindows();
return 0;
}
int main(int argc, char **argv)
{
CvCapture *capture = 0;
int resize_factor = 100;
if(argc > 1)
{
std::cout << "Openning: " << argv[1] << std::endl;
capture = cvCaptureFromAVI(argv[1]);
}
else
{
capture = cvCaptureFromCAM(0);
resize_factor = 50; // set size = 50% of original image
}
if(!capture)
{
std::cerr << "Cannot initialize video!" << std::endl;
return 1;
}
IplImage *frame_aux = cvQueryFrame(capture);
IplImage *frame = cvCreateImage(cvSize((int)((frame_aux->width*resize_factor)/100) , (int)((frame_aux->height*resize_factor)/100)), frame_aux->depth, frame_aux->nChannels);
cvResize(frame_aux, frame);
/* Background Subtraction Methods */
IBGS *bgs;
/*** Default Package ***/
bgs = new FrameDifferenceBGS;
//bgs = new StaticFrameDifferenceBGS;
//bgs = new WeightedMovingMeanBGS;
//bgs = new WeightedMovingVarianceBGS;
//bgs = new MixtureOfGaussianV1BGS;
//bgs = new MixtureOfGaussianV2BGS;
//bgs = new AdaptiveBackgroundLearning;
//bgs = new GMG;
/*** DP Package (adapted from Donovan Parks) ***/
//bgs = new DPAdaptiveMedianBGS;
//bgs = new DPGrimsonGMMBGS;
//bgs = new DPZivkovicAGMMBGS;
//bgs = new DPMeanBGS;
//bgs = new DPWrenGABGS;
//bgs = new DPPratiMediodBGS;
//bgs = new DPEigenbackgroundBGS;
//bgs = new DPTextureBGS;
/*** TB Package (adapted from Thierry Bouwmans) ***/
//bgs = new T2FGMM_UM;
//bgs = new T2FGMM_UV;
//bgs = new T2FMRF_UM;
//bgs = new T2FMRF_UV;
//bgs = new FuzzySugenoIntegral;
//bgs = new FuzzyChoquetIntegral;
/*** JMO Package (adapted from Jean-Marc Odobez) ***/
//bgs = new MultiLayerBGS;
/*** PT Package (adapted from Hofmann) ***/
//bgs = new PixelBasedAdaptiveSegmenter;
/*** LB Package (adapted from Laurence Bender) ***/
//bgs = new LBSimpleGaussian;
//bgs = new LBFuzzyGaussian;
//bgs = new LBMixtureOfGaussians;
//bgs = new LBAdaptiveSOM;
//bgs = new LBFuzzyAdaptiveSOM;
/*** LBP-MRF Package (adapted from Csaba Kertész) ***/
//bgs = new LbpMrf;
/*** AV Package (adapted from Antoine Vacavant) ***/
//bgs = new VuMeter;
/*** EG Package (adapted from Ahmed Elgammal) ***/
//bgs = new KDE;
int key = 0;
while(key != 'q')
{
frame_aux = cvQueryFrame(capture);
if(!frame_aux) break;
cvResize(frame_aux, frame);
cv::Mat img_input(frame);
cv::imshow("input", img_input);
cv::Mat img_mask;
cv::Mat img_bkgmodel;
bgs->process(img_input, img_mask, img_bkgmodel); // automatically shows the foreground mask image
//if(!img_mask.empty())
// do something
key = cvWaitKey(33);
}
delete bgs;
cvDestroyAllWindows();
cvReleaseCapture(&capture);
return 0;
}
void MainWindow::on_pushButton_3_clicked()
{
//run programe
IBGS *bgs;
int i=ui->comboBox->currentIndex();
qDebug()<<"select bgs "<<i;
/*** Default Package ***/
if(i==0) bgs = new FrameDifferenceBGS;
if(i==1) bgs = new StaticFrameDifferenceBGS;
if(i==2) bgs = new WeightedMovingMeanBGS;
if(i==3) bgs = new WeightedMovingVarianceBGS;
if(i==4) bgs = new MixtureOfGaussianV1BGS;
if(i==5) bgs = new MixtureOfGaussianV2BGS;
if(i==6) bgs = new AdaptiveBackgroundLearning;
if(i==7) bgs = new AdaptiveSelectiveBackgroundLearning;
if(i==8) bgs = new GMG;
/*** DP Package (thanks to Donovan Parks) ***/
if(i==9) bgs = new DPAdaptiveMedianBGS;
if(i==10) bgs = new DPGrimsonGMMBGS;
if(i==11) bgs = new DPZivkovicAGMMBGS;
if(i==12) bgs = new DPMeanBGS;
if(i==13) bgs = new DPWrenGABGS;
if(i==14) bgs = new DPPratiMediodBGS;
if(i==15) bgs = new DPEigenbackgroundBGS;
if(i==16) bgs = new DPTextureBGS;
/*** TB Package (thanks to Thierry Bouwmans, Fida EL BAF and Zhenjie Zhao) ***/
if(i==17) bgs = new T2FGMM_UM;
if(i==18) bgs = new T2FGMM_UV;
if(i==19) bgs = new T2FMRF_UM;
if(i==20) bgs = new T2FMRF_UV;
if(i==21) bgs = new FuzzySugenoIntegral;
if(i==22) bgs = new FuzzyChoquetIntegral;
/*** JMO Package (thanks to Jean-Marc Odobez) ***/
if(i==23) bgs = new MultiLayerBGS;
/*** PT Package (thanks to Martin Hofmann, Philipp Tiefenbacher and Gerhard Rigoll) ***/
// if(i==24) bgs = new PixelBasedAdaptiveSegmenter;
/*** LB Package (thanks to Laurence Bender) ***/
if(i==25) bgs = new LBSimpleGaussian;
if(i==26) bgs = new LBFuzzyGaussian;
if(i==27) bgs = new LBMixtureOfGaussians;
if(i==28) bgs = new LBAdaptiveSOM;
if(i==29) bgs = new LBFuzzyAdaptiveSOM;
/*** LBP-MRF Package (thanks to Csaba Kertész) ***/
if(i==30) bgs = new LbpMrf;
/*** AV Package (thanks to Lionel Robinault and Antoine Vacavant) ***/
if(i==31) bgs = new VuMeter;
/*** EG Package (thanks to Ahmed Elgammal) ***/
if(i==32) bgs = new KDE;
/*** DB Package (thanks to Domenico Daniele Bloisi) ***/
if(i==33) bgs = new IndependentMultimodalBGS;
/*** SJN Package (thanks to SeungJong Noh) ***/
if(i==34) bgs = new SJN_MultiCueBGS;
/*** BL Package (thanks to Benjamin Laugraud) ***/
if(i==35) bgs = new SigmaDeltaBGS;
/*** PL Package (thanks to Pierre-Luc) ***/
if(i==36) bgs = new SuBSENSEBGS();
if(i==37) bgs = new LOBSTERBGS();
int temporalRoi[2];
temporalRoi[0]=ui->spinBox->value();
temporalRoi[1]=ui->spinBox_2->value();
qDebug()<<"from to: "<<temporalRoi[0]<<" "<<temporalRoi[1];
QString prefix=ui->lineEdit_3->text();
QString suffix=ui->comboBox_2->currentText();
int format=ui->spinBox_3->value();
qDebug()<<"prefix "<<prefix;
qDebug()<<"suffix "<<suffix;
qDebug()<<"format "<<format;
QString CDNetDir=ui->lineEdit->text();
QString VideoPath=ui->lineEdit_2->text();
qDebug()<<"CDNet Dir "<<CDNetDir;
qDebug()<<"VideoPath "<<VideoPath;
if(CDNetDir.isEmpty()) return;
int frameNumber = temporalRoi[0];
int key = 0;
cvNamedWindow("input",0);
QString fileName;
// QString qformat=QString("%%1d").arg(format);
// qDebug()<<"qformat "<<qformat;
// const char *cformat=qformat.toStdString().data();
QString numstr;
QTextStream out(&numstr);
out.setFieldAlignment(QTextStream::AlignRight);
out.setFieldWidth(format);
out.setPadChar(QLatin1Char('0'));
out<<frameNumber;
// QString numstr=QString::sprintf(cformat,frameNumber);
fileName=CDNetDir+"/"+prefix+numstr+suffix;
qDebug()<<"fileName "<<fileName;
settings->setValue("/Folder/CDNetDir",CDNetDir);
settings->setValue("/Folder/from",temporalRoi[0]);
settings->setValue("/Folder/to",temporalRoi[1]);
settings->setValue("/Folder/prefix",prefix);
settings->setValue("/Folder/suffix",suffix);
settings->sync();
while(key != 'q')
{
if(frameNumber>temporalRoi[1]) break;
out.flush();
numstr.clear();
out<<frameNumber;
fileName=CDNetDir+"/"+prefix+numstr+suffix;
qDebug()<<frameNumber<<" fileName "<<fileName;
std::string filename =fileName.toStdString();
std::cout << "reading " << filename << std::endl;
cv::Mat img_input = cv::imread(filename, CV_LOAD_IMAGE_COLOR);
if (img_input.empty())
break;
cv::imshow("input", img_input);
cv::Mat img_mask;
cv::Mat img_bkgmodel;
std::cout<<" process start ..............."<<std::endl;
bgs->process(img_input, img_mask, img_bkgmodel); // by default, it shows automatically the foreground mask image
std::cout<<" process end ..............."<<std::endl;
//if(!img_mask.empty())
// cv::imshow("Foreground", img_mask);
// do something
key = cvWaitKey(33);
frameNumber++;
}
delete bgs;
cvDestroyAllWindows();
qDebug()<<"exit ..................";
}
int main(int argc, char **argv)
{
std::cout << "Using OpenCV " << CV_MAJOR_VERSION << "." << CV_MINOR_VERSION << "." << CV_SUBMINOR_VERSION << std::endl;
CvCapture *capture = 0;
int resize_factor = 100;
if(argc > 1)
{
std::cout << "Openning: " << argv[1] << std::endl;
capture = cvCaptureFromAVI(argv[1]);
}
else
{
capture = cvCaptureFromCAM(0);
resize_factor = 50; // set size = 50% of original image
}
if(!capture)
{
std::cerr << "Cannot initialize video!" << std::endl;
return -1;
}
IplImage *frame_aux = cvQueryFrame(capture);
IplImage *frame = cvCreateImage(cvSize((int)((frame_aux->width*resize_factor)/100) , (int)((frame_aux->height*resize_factor)/100)), frame_aux->depth, frame_aux->nChannels);
cvResize(frame_aux, frame);
/* Background Subtraction Methods */
IBGS *bgs;
/*** Default Package ***/
bgs = new FrameDifferenceBGS;
//bgs = new StaticFrameDifferenceBGS;
//bgs = new WeightedMovingMeanBGS;
//bgs = new WeightedMovingVarianceBGS;
//bgs = new MixtureOfGaussianV1BGS;
//bgs = new MixtureOfGaussianV2BGS;
//bgs = new AdaptiveBackgroundLearning;
//bgs = new AdaptiveSelectiveBackgroundLearning;
//bgs = new GMG;
/*** DP Package (thanks to Donovan Parks) ***/
//bgs = new DPAdaptiveMedianBGS;
//bgs = new DPGrimsonGMMBGS;
//bgs = new DPZivkovicAGMMBGS;
//bgs = new DPMeanBGS;
//bgs = new DPWrenGABGS;
//bgs = new DPPratiMediodBGS;
//bgs = new DPEigenbackgroundBGS;
//bgs = new DPTextureBGS;
/*** TB Package (thanks to Thierry Bouwmans, Fida EL BAF and Zhenjie Zhao) ***/
//bgs = new T2FGMM_UM;
//bgs = new T2FGMM_UV;
//bgs = new T2FMRF_UM;
//bgs = new T2FMRF_UV;
//bgs = new FuzzySugenoIntegral;
//bgs = new FuzzyChoquetIntegral;
/*** JMO Package (thanks to Jean-Marc Odobez) ***/
//bgs = new MultiLayerBGS;
/*** PT Package (thanks to Martin Hofmann, Philipp Tiefenbacher and Gerhard Rigoll) ***/
//bgs = new PixelBasedAdaptiveSegmenter;
/*** LB Package (thanks to Laurence Bender) ***/
//bgs = new LBSimpleGaussian;
//bgs = new LBFuzzyGaussian;
//bgs = new LBMixtureOfGaussians;
//bgs = new LBAdaptiveSOM;
//bgs = new LBFuzzyAdaptiveSOM;
/*** LBP-MRF Package (thanks to Csaba Kertész) ***/
//bgs = new LbpMrf;
/*** AV Package (thanks to Lionel Robinault and Antoine Vacavant) ***/
//bgs = new VuMeter;
/*** EG Package (thanks to Ahmed Elgammal) ***/
//bgs = new KDE;
/*** DB Package (thanks to Domenico Daniele Bloisi) ***/
//bgs = new IndependentMultimodalBGS;
/*** SJN Package (thanks to SeungJong Noh) ***/
//bgs = new SJN_MultiCueBGS;
/*** BL Package (thanks to Benjamin Laugraud) ***/
//bgs = new SigmaDeltaBGS;
int key = 0;
while(key != 'q')
{
frame_aux = cvQueryFrame(capture);
if(!frame_aux) break;
cvResize(frame_aux, frame);
cv::Mat img_input(frame);
cv::imshow("input", img_input);
cv::Mat img_mask;
cv::Mat img_bkgmodel;
bgs->process(img_input, img_mask, img_bkgmodel); // by default, it shows automatically the foreground mask image
//if(!img_mask.empty())
// cv::imshow("Foreground", img_mask);
// do something
key = cvWaitKey(33);
}
delete bgs;
cvDestroyAllWindows();
cvReleaseCapture(&capture);
return 0;
}
void start(VideoFolder videoFolder, uint bgsMethodId){
cout << "staring bgs..." << endl;
const imgRange range = videoFolder.getRange();
//注意：一定要略微扩大处理范围
const uint fromIdx = range.first - 10;;
const uint toIdx = range.second;
const string runTimePath = videoFolder.runTimeFile();
cout << "imgRange From " << fromIdx << " to " << toIdx << endl;
/* Background Subtraction Methods */
IBGS *bgs;
switch(bgsMethodId){
/*** Default Package ***/
case 1:
bgs = new FrameDifferenceBGS;
break;
case 2:
bgs = new StaticFrameDifferenceBGS;break;
case 3:
bgs = new WeightedMovingMeanBGS;break;
case 4:
bgs = new WeightedMovingVarianceBGS;break;
case 5:
bgs = new MixtureOfGaussianV1BGS;break;
case 6:
bgs = new MixtureOfGaussianV2BGS;break;
case 7:
bgs = new AdaptiveBackgroundLearning;break;
case 8:
bgs = new AdaptiveSelectiveBackgroundLearning;break;
case 9:
bgs = new GMG;break;
/*** DP Package (thanks to Donovan Parks) ***/
case 10:
bgs = new DPAdaptiveMedianBGS;break;
case 11:
bgs = new DPGrimsonGMMBGS;break;
case 12:
bgs = new DPZivkovicAGMMBGS;break;
case 13:
bgs = new DPMeanBGS;break;
case 14:
bgs = new DPWrenGABGS;break;
case 15:
bgs = new DPPratiMediodBGS;break;
case 16:
bgs = new DPEigenbackgroundBGS;break;
case 17:
bgs = new DPTextureBGS;break;
/*** TB Package (thanks to Thierry Bouwmans, Fida EL BAF and Zhenjie Zhao) ***/
case 18:
bgs = new T2FGMM_UM;break;
case 19:
bgs = new T2FGMM_UV;break;
case 20:
bgs = new T2FMRF_UM;break;
case 21:
bgs = new T2FMRF_UV;break;
case 22:
bgs = new FuzzySugenoIntegral;break;
case 23:
bgs = new FuzzyChoquetIntegral;break;
/*** JMO Package (thanks to Jean-Marc Odobez) ***/
case 24:
bgs = new MultiLayerBGS;break;
/*** PT Package (thanks to Martin Hofmann, Philipp Tiefenbacher and Gerhard Rigoll) ***/
//case 25:
// bgs = new PixelBasedAdaptiveSegmenter;break;
/*** LB Package (thanks to Laurence Bender) ***/
case 25:
bgs = new LBSimpleGaussian;break;
case 26:
bgs = new LBFuzzyGaussian;break;
case 27:
bgs = new LBMixtureOfGaussians;break;
case 28:
bgs = new LBAdaptiveSOM;break;
case 29:
bgs = new LBFuzzyAdaptiveSOM;break;
/*** LBP-MRF Package (thanks to Csaba Kertész) ***/
case 30:
bgs = new LbpMrf;break;
/*** AV Package (thanks to Lionel Robinault and Antoine Vacavant) ***/
case 31:
bgs = new VuMeter;break;
/*** EG Package (thanks to Ahmed Elgammal) ***/
case 32:
bgs = new KDE;break;
/*** DB Package (thanks to Domenico Daniele Bloisi) ***/
case 33:
bgs = new IndependentMultimodalBGS;break;
/*** SJN Package (thanks to SeungJong Noh) ***/
case 34:
bgs = new SJN_MultiCueBGS;break;
/*** BL Package (thanks to Benjamin Laugraud) ***/
case 35:
bgs = new SigmaDeltaBGS;break;
/*** PL Package (thanks to Pierre-Luc) ***/
case 36:
bgs = new SuBSENSEBGS();break;
case 37:
bgs = new LOBSTERBGS();break;
default:break;
}
ull allTime = 0;
for (uint t = fromIdx; t <= toIdx; ++t){
cout << "imgIdx " << t << endl;
//bgs(videoFolder.inputFrame(t), videoFolder.binaryFrame(t), videoFolder.bgmodelFrame(t), bgsMethodId);
const string imageFromPath = videoFolder.inputFrame(t);
const string imageToPath = videoFolder.binaryFrame(t);
const string bgmodelPath = videoFolder.bgmodelFrame(t);
if(bgsMethodId < 1 || bgsMethodId > 37){
cerr << "bgsMethodId not found!" << endl;
return;
}
cout << "bgsMethodId is " << bgsMethodId << endl;
cout << "imageFromPath is " << imageFromPath << endl;
cout << "imageToPath is " << imageToPath << endl;
cout << "bgmodelPath is " << bgmodelPath << endl;
cv::Mat img_input;
cv::Mat img_mask;
cv::Mat img_bgmodel;
img_input = cv::imread(imageFromPath);
cout << "starting bgs process..." << endl;
ull begin = getSystemTime();
bgs->process(img_input, img_mask, img_bgmodel); // by default, it shows automatically the foreground mask image
ull end = getSystemTime();
allTime += (end - begin);
cout << "single process done!" << endl;
//if(!img_mask.empty())
// cv::imshow("Foreground", img_mask);
// do something
if(!img_mask.empty()){
cv::imwrite(imageToPath,img_mask);
cout << "save mask..." << endl;
}
if(!img_bgmodel.empty()){
cv::imwrite(bgmodelPath,img_bgmodel);
cout << "save bgmodel" << endl;
}
}
double averageTime = (allTime*1.0) / toIdx;
ofstream ofile(runTimePath, ios::out);
ofile << averageTime;
ofile.close();
}
