// Outliers =============================================================== void ProgClassifyCL2DCore::computeStableCores() { if (verbose && node->rank==0) std::cerr << "Computing stable cores ...\n"; MetaData thisClass, anotherClass, commonImages, thisClassCore; MDRow row; size_t first, last; Matrix2D<unsigned char> coocurrence; Matrix1D<unsigned char> maximalCoocurrence; int Nblocks=blocks.size(); taskDistributor->reset(); std::vector<size_t> commonIdx; std::map<String,size_t> thisClassOrder; String fnImg; while (taskDistributor->getTasks(first, last)) for (size_t idx=first; idx<=last; ++idx) { // Read block CL2DBlock &thisBlock=blocks[idx]; if (thisBlock.level<=tolerance) continue; if (!existsBlockInMetaDataFile(thisBlock.fnLevelCore, thisBlock.block)) continue; thisClass.read(thisBlock.block+"@"+thisBlock.fnLevelCore); thisClassCore.clear(); // Add MDL_ORDER if (thisClass.size()>0) { size_t order=0; thisClassOrder.clear(); FOR_ALL_OBJECTS_IN_METADATA(thisClass) { thisClass.getValue(MDL_IMAGE,fnImg,__iter.objId); thisClassOrder[fnImg]=order++; } // Calculate coocurrence within all blocks whose level is inferior to this size_t NthisClass=thisClass.size(); if (NthisClass>0) { try { coocurrence.initZeros(NthisClass,NthisClass); } catch (XmippError e) { std::cerr << e << std::endl; std::cerr << "There is a memory allocation error. Most likely there are too many images in this class (" << NthisClass << " images). Consider increasing the number of initial and final classes\n"; REPORT_ERROR(ERR_MEM_NOTENOUGH,"While computing stable class"); } for (int n=0; n<Nblocks; n++) { CL2DBlock &anotherBlock=blocks[n]; if (anotherBlock.level>=thisBlock.level) break; if (!existsBlockInMetaDataFile(anotherBlock.fnLevelCore, anotherBlock.block)) continue; anotherClass.read(anotherBlock.block+"@"+anotherBlock.fnLevelCore); anotherClass.intersection(thisClass,MDL_IMAGE); commonImages.join1(anotherClass, thisClass, MDL_IMAGE,LEFT); commonIdx.resize(commonImages.size()); size_t idx=0; FOR_ALL_OBJECTS_IN_METADATA(commonImages) { commonImages.getValue(MDL_IMAGE,fnImg,__iter.objId); commonIdx[idx++]=thisClassOrder[fnImg]; } size_t Ncommon=commonIdx.size(); for (size_t i=0; i<Ncommon; i++) { size_t idx_i=commonIdx[i]; for (size_t j=i+1; j<Ncommon; j++) { size_t idx_j=commonIdx[j]; MAT_ELEM(coocurrence,idx_i,idx_j)+=1; } } } } // Take only those elements whose coocurrence is maximal maximalCoocurrence.initZeros(NthisClass); int aimedCoocurrence=thisBlock.level-tolerance; FOR_ALL_ELEMENTS_IN_MATRIX2D(coocurrence) if (MAT_ELEM(coocurrence,i,j)==aimedCoocurrence) VEC_ELEM(maximalCoocurrence,i)=VEC_ELEM(maximalCoocurrence,j)=1; // Now compute core FOR_ALL_OBJECTS_IN_METADATA(thisClass) { thisClass.getValue(MDL_IMAGE,fnImg,__iter.objId); size_t idx=thisClassOrder[fnImg]; if (VEC_ELEM(maximalCoocurrence,idx)) { thisClass.getRow(row,__iter.objId); thisClassCore.addRow(row); } } } thisClassCore.write(thisBlock.fnLevel.insertBeforeExtension((String)"_stable_core_"+thisBlock.block),MD_APPEND); }
int main2() { MultidimArray<double> preImg, avgCurr, mappedImg; MultidimArray<double> outputMovie; Matrix1D<double> meanStdev; ImageGeneric movieStack; Image<double> II; MetaData MD; // To save plot information FileName motionInfFile, flowFileName, flowXFileName, flowYFileName; ArrayDim aDim; // For measuring times (both for whole process and for each level of the pyramid) clock_t tStart, tStart2; #ifdef GPU // Matrix that we required in GPU part GpuMat d_flowx, d_flowy, d_dest; GpuMat d_avgcurr, d_preimg; #endif // Matrix required by Opencv cv::Mat flow, dest, flowx, flowy; cv::Mat flowxPre, flowyPre; cv::Mat avgcurr, avgstep, preimg, preimg8, avgcurr8; cv::Mat planes[]={flowxPre, flowyPre}; int imagenum, cnt=2, div=0, flowCounter; int h, w, levelNum, levelCounter=1; motionInfFile=foname.replaceExtension("xmd"); std::string extension=fname.getExtension(); if (extension=="mrc") fname+=":mrcs"; movieStack.read(fname,HEADER); movieStack.getDimensions(aDim); imagenum = aDim.ndim; h = aDim.ydim; w = aDim.xdim; if (darkImageCorr) { II.read(darkRefFilename); darkImage=II(); } if (gainImageCorr) { II.read(gianRefFilename); gainImage=II(); } meanStdev.initZeros(4); //avgcurr=cv::Mat::zeros(h, w,CV_32FC1); avgCurr.initZeros(h, w); flowxPre=cv::Mat::zeros(h, w,CV_32FC1); flowyPre=cv::Mat::zeros(h, w,CV_32FC1); #ifdef GPU // Object for optical flow FarnebackOpticalFlow d_calc; setDevice(gpuDevice); // Initialize the parameters for optical flow structure d_calc.numLevels=6; d_calc.pyrScale=0.5; d_calc.fastPyramids=true; d_calc.winSize=winSize; d_calc.numIters=1; d_calc.polyN=5; d_calc.polySigma=1.1; d_calc.flags=0; #endif // Initialize the stack for the output movie if (saveCorrMovie) outputMovie.initZeros(imagenum, 1, h, w); // Correct for global motion from a cross-correlation based algorithms if (globalShiftCorr) { Matrix1D<double> shiftMatrix(2); shiftVector.reserve(imagenum); shiftMD.read(globalShiftFilename); FOR_ALL_OBJECTS_IN_METADATA(shiftMD) { shiftMD.getValue(MDL_SHIFT_X, XX(shiftMatrix), __iter.objId); shiftMD.getValue(MDL_SHIFT_Y, YY(shiftMatrix), __iter.objId); shiftVector.push_back(shiftMatrix); } } tStart2=clock(); // Compute the average of the whole stack fstFrame++; // Just to adapt to Li algorithm lstFrame++; // Just to adapt to Li algorithm if (lstFrame>=imagenum || lstFrame==1) lstFrame=imagenum; imagenum=lstFrame-fstFrame+1; levelNum=sqrt(double(imagenum)); computeAvg(fname, fstFrame, lstFrame, avgCurr); // if the user want to save the PSD if (doAverage) { II()=avgCurr; II.write(foname); return 0; } xmipp2Opencv(avgCurr, avgcurr); cout<<"Frames "<<fstFrame<<" to "<<lstFrame<<" under processing ..."<<std::endl; while (div!=groupSize) { div=int(imagenum/cnt); // avgStep to hold the sum of aligned frames of each group at each step avgstep=cv::Mat::zeros(h, w,CV_32FC1); cout<<"Level "<<levelCounter<<"/"<<levelNum<<" of the pyramid is under processing"<<std::endl; // Compute time for each level tStart = clock(); // Check if we are in the final step if (div==1) cnt=imagenum; flowCounter=1; for (int i=0;i<cnt;i++) { //Just compute the average in the last step if (div==1) { if (globalShiftCorr) { Matrix1D<double> shiftMatrix(2); MultidimArray<double> frameImage; movieStack.readMapped(fname,i+1); movieStack().getImage(frameImage); if (darkImageCorr) frameImage-=darkImage; if (gainImageCorr) frameImage/=gainImage; XX(shiftMatrix)=XX(shiftVector[i]); YY(shiftMatrix)=YY(shiftVector[i]); translate(BSPLINE3, preImg, frameImage, shiftMatrix, WRAP); } else { movieStack.readMapped(fname,fstFrame+i); movieStack().getImage(preImg); if (darkImageCorr) preImg-=darkImage; if (gainImageCorr) preImg/=gainImage; } xmipp2Opencv(preImg, preimg); } else { if (i==cnt-1) computeAvg(fname, i*div+fstFrame, lstFrame, preImg); else computeAvg(fname, i*div+fstFrame, (i+1)*div+fstFrame-1, preImg); } xmipp2Opencv(preImg, preimg); // Note: we should use the OpenCV conversion to use it in optical flow convert2Uint8(avgcurr,avgcurr8); convert2Uint8(preimg,preimg8); #ifdef GPU d_avgcurr.upload(avgcurr8); d_preimg.upload(preimg8); if (cnt==2) d_calc(d_avgcurr, d_preimg, d_flowx, d_flowy); else { flowXFileName=foname.removeLastExtension()+formatString("flowx%d%d.txt",div*2,flowCounter); flowYFileName=foname.removeLastExtension()+formatString("flowy%d%d.txt",div*2,flowCounter); readMat(flowXFileName.c_str(), flowx); readMat(flowYFileName.c_str(), flowy); d_flowx.upload(flowx); d_flowy.upload(flowy); d_calc.flags=cv::OPTFLOW_USE_INITIAL_FLOW; d_calc(d_avgcurr, d_preimg, d_flowx, d_flowy); } d_flowx.download(planes[0]); d_flowy.download(planes[1]); d_avgcurr.release(); d_preimg.release(); d_flowx.release(); d_flowy.release(); #else if (cnt==2) calcOpticalFlowFarneback(avgcurr8, preimg8, flow, 0.5, 6, winSize, 1, 5, 1.1, 0); else { flowFileName=foname.removeLastExtension()+formatString("flow%d%d.txt",div*2,flowCounter); readMat(flowFileName.c_str(), flow); calcOpticalFlowFarneback(avgcurr8, preimg8, flow, 0.5, 6, winSize, 1, 5, 1.1, cv::OPTFLOW_USE_INITIAL_FLOW); } split(flow, planes); #endif // Save the flows if we are in the last step if (div==groupSize) { if (i > 0) { std_dev2(planes,flowxPre,flowyPre,meanStdev); size_t id=MD.addObject(); MD.setValue(MDL_OPTICALFLOW_MEANX, double(meanStdev(0)), id); MD.setValue(MDL_OPTICALFLOW_MEANY, double(meanStdev(2)), id); MD.setValue(MDL_OPTICALFLOW_STDX, double(meanStdev(1)), id); MD.setValue(MDL_OPTICALFLOW_STDY, double(meanStdev(3)), id); MD.write(motionInfFile, MD_APPEND); } planes[0].copyTo(flowxPre); planes[1].copyTo(flowyPre); } else { #ifdef GPU flowXFileName=foname.removeLastExtension()+formatString("flowx%d%d.txt",div,i+1); flowYFileName=foname.removeLastExtension()+formatString("flowy%d%d.txt",div,i+1); saveMat(flowXFileName.c_str(), planes[0]); saveMat(flowYFileName.c_str(), planes[1]); #else flowFileName=foname.removeLastExtension()+formatString("flow%d%d.txt",div,i+1); saveMat(flowFileName.c_str(), flow); #endif if ((i+1)%2==0) flowCounter++; } for( int row = 0; row < planes[0].rows; row++ ) for( int col = 0; col < planes[0].cols; col++ ) { planes[0].at<float>(row,col) += (float)col; planes[1].at<float>(row,col) += (float)row; } cv::remap(preimg, dest, planes[0], planes[1], cv::INTER_CUBIC); if (div==1 && saveCorrMovie) { mappedImg.aliasImageInStack(outputMovie, i); opencv2Xmipp(dest, mappedImg); } avgstep+=dest; } avgcurr=avgstep/cnt; cout<<"Processing level "<<levelCounter<<"/"<<levelNum<<" has been finished"<<std::endl; printf("Processing time: %.2fs\n", (double)(clock() - tStart)/CLOCKS_PER_SEC); cnt*=2; levelCounter++; } opencv2Xmipp(avgcurr, avgCurr); II() = avgCurr; II.write(foname); printf("Total Processing time: %.2fs\n", (double)(clock() - tStart2)/CLOCKS_PER_SEC); if (saveCorrMovie) { II()=outputMovie; II.write(foname.replaceExtension("mrcs")); } // Release the memory avgstep.release(); preimg.release(); avgcurr8.release(); preimg8.release(); flow.release(); planes[0].release(); planes[1].release(); flowxPre.release(); flowyPre.release(); movieStack.clear(); preImg.clear(); avgCurr.clear(); II.clear(); return 0; }