int detect(int argc, char* argv[]) {
cout << "Testing L1 started" << endl;
if(argc<3) {
cerr << "Usage: HFTrainDetect config.txt 1 [image] [detection]" << endl;
return -1;
}
// read config file
StructParam param;
if(!param.loadConfigDetect(argv[1])) {
cerr << "Could not parse " << argv[1] << endl;
exit(-1);
}
// timer
timeval start, end;
double runtime;
gettimeofday(&start, NULL);
// load forest
HFForest_L1 forest(¶m);
forest.loadForest(param.treepath_L1);
AnnotationData TestD;
TestD.loadAnnoFile(param.test_file.c_str());
// detect hypotheses on all images
for(unsigned int i=0; i<TestD.AnnoData.size(); ++i) {
// read image
Mat originImg = imread((param.image_path+"/"+TestD.AnnoData[i].image_name).c_str()); // originImg is UINT8_3Channel
string depthFileName = param.depth_image_path+"/"+TestD.AnnoData[i].image_name.substr(0,TestD.AnnoData[i].image_name.size()-4)+"_abs_smooth.png";
Mat depthImg = imread(depthFileName,CV_LOAD_IMAGE_ANYDEPTH); // depthImg is UINT16
if(originImg.empty()) {
cerr << "Could not read image file " << param.image_path << "/" << TestD.AnnoData[i].image_name << endl;
continue;
}
// detect
Hypotheses hyp;
if(param.feature_path.empty()) {
forest.detect(TestD.AnnoData[i].image_name,originImg,depthImg,hyp);
}
#if 0
// evaluate
Annotation train;
hyp.check(TestD.AnnoData[i], param.d_thres, train);
#endif
// save detections
hyp.save_detections( (param.hypotheses_path+"/"+TestD.AnnoData[i].image_name+".txt").c_str());
#if 0
// show detections
hyp.show_detections(originImg, param.d_thres);
#endif
}
gettimeofday(&end, NULL);
runtime = ( (end.tv_sec - start.tv_sec)*1000 + (end.tv_usec - start.tv_usec)/(1000.0) );
cout << "Total runtime (L1 test): " << runtime << " msec" << endl;
return 0;
}
// main routine
int main(int argc, char* argv[]) {
//%%%%%%%%%%%%%%%%%%%%%%%% init %%%%%%%%%%%%%%%%%%%%%%%%
// read arguments
if(argc<3) {
cerr << "Usage: ComputeFeatures config.txt override(no(0)/yes(1))" << endl;
exit(-1);
}
// read config file
StructParam param;
if(!param.loadConfigFeature(argv[1])) {
cerr << "Could not parse " << argv[1] << endl;
exit(-1);
}
// read test/anno data (uses same data structure)
AnnotationData TestD;
TestD.loadAnnoFile(param.test_file.c_str());
//if(atoi(argv[2])==2)
//system(("rm " + param.feature_path + "/*.pgm").c_str());
// detect hypotheses on all images
for(int i=0; i<TestD.AnnoData.size(); ++i) {
// read image
Mat originImg = imread((param.image_path+"/"+TestD.AnnoData[i].image_name).c_str());
if(originImg.empty()) {
cerr << "Could not read image file " << param.image_path << "/" << TestD.AnnoData[i].image_name << endl;
continue;
}
cout << system(("mkdir " + param.feature_path + "/" + TestD.AnnoData[i].image_name).c_str());
// extract features
for(int k=0; k<param.scales.size(); ++k) {
Features Feat;
string fname(param.feature_path+"/"+TestD.AnnoData[i].image_name+"/"+TestD.AnnoData[i].image_name);
if( atoi(argv[2])==1 || !Feat.loadFeatures( fname, param.scales[k]) ) {
Mat scaledImg;
resize(originImg, scaledImg, Size(int(originImg.cols * param.scales[k] + 0.5), int(originImg.rows * param.scales[k] + 0.5)) );
Feat.extractFeatureChannels(scaledImg);
Feat.saveFeatures( fname, param.scales[k]);
#if 0
// debug!!!!
Features Feat2;
namedWindow( "ShowF", CV_WINDOW_AUTOSIZE );
imshow( "ShowF", Feat.Channels[0] );
Feat2.loadFeatures( fname, param.scales[k]);
namedWindow( "ShowF2", CV_WINDOW_AUTOSIZE );
imshow( "ShowF2", Feat2.Channels[0] );
cout << scaledImg.rows << " " << scaledImg.cols << " " << scaledImg.depth() << " " << scaledImg.channels() << " " << scaledImg.isContinuous() << endl;
cout << Feat.Channels[0].rows << " " << Feat.Channels[0].cols << " " << Feat.Channels[0].depth() << " " << Feat.Channels[0].channels() << " " << Feat.Channels[0].isContinuous() << endl;
cout << Feat2.Channels[0].rows << " " << Feat2.Channels[0].cols << " " << Feat2.Channels[0].depth() << " " << Feat2.Channels[0].channels() << " " << Feat.Channels[0].isContinuous() << endl;
Mat diff(Size(scaledImg.cols,scaledImg.rows),CV_8UC1);
cout << diff.rows << " " << diff.cols << " " << diff.depth() << " " << diff.channels() << " " << scaledImg.isContinuous() << endl;
diff = Feat.Channels[0] - Feat2.Channels[0];
namedWindow( "ShowDiff", CV_WINDOW_AUTOSIZE );
imshow( "ShowDiff", diff );
waitKey(0);
#endif
}
}
}
return 0;
}
int detect_L2(int argc, char* argv[]) {
cout << "Testing L2 started" << endl;
if(argc<3) {
cerr << "Usage: HFTrainDetect config.txt 1 [image] [detection]" << endl;
return -1;
}
// timer
timeval start, end;
gettimeofday(&start, NULL);
double runtime=0;
// read config file
StructParam param;
if(!param.loadConfigDetect_L2(argv[1])) {
cerr << "Could not parse " << argv[1] << endl;
exit(-1);
}
// load first layer forest
HFForest_L1 forest_L1(¶m);
forest_L1.loadForest(param.treepath_L1);
// load second layer forest
HFForest_L2 forest_L2(¶m);
forest_L2.loadForest(param.treepath_L2);
AnnotationData TestD;
TestD.loadAnnoFile(param.test_file.c_str());
// detect hypotheses on all images
for(unsigned int i=0; i<TestD.AnnoData.size(); ++i) {
// read image
string fileName = param.image_path+"/"+TestD.AnnoData[i].image_name;
string depthFileName = param.depth_image_path+"/"+TestD.AnnoData[i].image_name.substr(0,TestD.AnnoData[i].image_name.size()-4)+"_abs_smooth.png";
Mat originImg = imread(fileName);
Mat depthImg = imread(depthFileName,CV_LOAD_IMAGE_ANYDEPTH); // depthImg is UINT16
// calculate leaf id maps using first layer forest
cout<<"evaluating leafId maps"<<endl;
vector<vector<vector<Mat> > > leafIdMaps;
forest_L1.evaluateLeafIdMaps(originImg, depthImg, leafIdMaps);
// // get the vote maps from the first layer
// cout<<"evaluating L1 vote maps"<<endl;
// vector<vector<Mat> > voteMaps_L1;
// forest_L1.returnVoteMaps(originImg, depthImg, voteMaps_L1);
// get the vote maps from the second layer
cout<<"evaluating L2 vote maps"<<endl;
vector<vector<Mat> > voteMaps_L2;
forest_L2.returnVoteMaps(leafIdMaps,voteMaps_L2,originImg);
#if 0
namedWindow("show",CV_WINDOW_AUTOSIZE);
for(unsigned int aspIdx=0; aspIdx<param.asp_ratios.size(); ++aspIdx){
for(unsigned int sclIdx=0; sclIdx<param.scales.size(); ++sclIdx){
Mat show;
voteMaps_L2[aspIdx][sclIdx].convertTo(show,CV_8U,255*0.05);
imshow("show",show);
waitKey(0);
}
}
#endif
Hypotheses hyp;
forest_L2.detect(hyp,voteMaps_L2);
// hyp.save_detections((param.hypotheses_path+"/"+TestD.AnnoData[i].image_name+".txt").c_str());
// hyp.show_detections(originImg,param.d_thres);
// // pass leafIdMaps to second layer forest for detection
// cout<<"evaluating combined detection"<<endl;
// vector<Hypotheses> bigHyp;
// forest_L2.detect(bigHyp, voteMaps_L1, voteMaps_L2);
//
// // save detections
// for(unsigned int hypIdx=0; hypIdx<bigHyp.size(); ++hypIdx){
// char buffer[5];
// sprintf(buffer,"%02d",hypIdx);
// string strBuffer = buffer;
// bigHyp[hypIdx].save_detections( (param.hypotheses_path+"/lambda"+strBuffer+"/"+TestD.AnnoData[i].image_name+".txt").c_str());
// }
}
gettimeofday(&end, NULL);
runtime = ( (end.tv_sec - start.tv_sec)*1000 + (end.tv_usec - start.tv_usec)/(1000.0) );
cout << "Total runtime (L2 test): " << runtime << " msec" << endl;
return 0;
}