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Diffstat (limited to 'sci_gateway1/cpp/opencv_evaluate.cpp')
| -rw-r--r-- | sci_gateway1/cpp/opencv_evaluate.cpp | 417 |
1 files changed, 417 insertions, 0 deletions
diff --git a/sci_gateway1/cpp/opencv_evaluate.cpp b/sci_gateway1/cpp/opencv_evaluate.cpp new file mode 100644 index 0000000..2794b90 --- /dev/null +++ b/sci_gateway1/cpp/opencv_evaluate.cpp @@ -0,0 +1,417 @@ +/*************************************************** +Author : Rohit Suri +***************************************************/ +#include <iostream> +#include <opencv2/opencv.hpp> +#include <opencv2/nonfree/nonfree.hpp> +#include <opencv2/ml/ml.hpp> + +using namespace std; +using namespace cv; + +extern "C" +{ + #include "api_scilab.h" + #include "Scierror.h" + #include "BOOL.h" + #include <localization.h> + #include "sciprint.h" + int opencv_evaluate(char *fname, unsigned long fname_len) + { + // Error management variables + SciErr sciErr; + + //------Local variables------// + int upright = 1; + Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create("FlannBased"); + Ptr<DescriptorExtractor> extractor = new SurfDescriptorExtractor(1, 4, 2, 1, int(upright)); + BOWImgDescriptorExtractor bowDE(extractor, matcher); + SurfFeatureDetector detector(1, 4, 2, 1, int(upright)); + char *classifierLocation = NULL; + Mat dictionary,inp,features; + double response; + vector<KeyPoint> keyPoints; + CvSVM svm; + int dictionarySize; + int *piAddr = NULL; + int *piChild = NULL; + int iRows, iCols; + char **pstData = NULL; + int *piLen = NULL; + int *count = NULL; + char **classifierDescription = NULL; + int classifierDescriptionCount; + char **description = NULL; + char ***location = NULL; + char *bagOfFeaturesLocation = NULL; + int descriptionCount; + double *confMatrix = NULL; + char *fileName = NULL; + double avgAccuracy = 0; + //------Check number of parameters------// + CheckInputArgument(pvApiCtx, 2, 2); + CheckOutputArgument(pvApiCtx, 1, 1); + + //------Get input arguments------// + sciErr = getVarAddressFromPosition(pvApiCtx, 1, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr)) + { + Scierror(999, "Error: The input argument #1 is not of type classifier.\n"); + return 0; + } + + // Extracting object type and checking if type is classifier + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!(strcmp(pstData[0],"classifier")==0)) + { + Scierror(999, "Error: The input argument #1 is not of type classifier.\n"); + return 0; + } + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows!=1 || iCols!=1) + { + Scierror(999, "1x1 Matrix expected for classifier argument."); + return 0; + } + classifierLocation = pstData[0]; + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + pstData[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 3, &iRows, &iCols, piLen, pstData); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(iRows!=1 || iCols!=1) + { + Scierror(999, "1x1 Matrix expected for bagOfFeatures argument."); + return 0; + } + bagOfFeaturesLocation = pstData[0]; + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, NULL, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*) malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, piLen, NULL); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + classifierDescription = (char**) malloc(sizeof(char*) * iRows * iCols); + for(int iterPstData = 0; iterPstData < iRows * iCols; iterPstData++) + { + classifierDescription[iterPstData] = (char*) malloc(sizeof(char) * piLen[iterPstData] + 1); + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 4, &iRows, &iCols, piLen, classifierDescription); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + classifierDescriptionCount = iRows; + // Second Argument + sciErr = getVarAddressFromPosition(pvApiCtx, 2, &piAddr); + if (sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + if(!isListType(pvApiCtx, piAddr)) + { + Scierror(999, "Error: The input argument #2 is not of type imageSet.\n"); + return 0; + } + + // Extracting object type and checking if type is imageSet + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + pstData = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + pstData[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 1, &iRows, &iCols, piLen, pstData); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + if(!(strcmp(pstData[0],"imageSet")==0)) + { + Scierror(999, "Error: The input argument #2 is not of type imageSet.\n"); + return 0; + } + + // Extracting Description attribute of input argument + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + description = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int iter = 0 ; iter < iRows * iCols ; iter++) + { + description[iter] = (char*)malloc(sizeof(char) * (piLen[iter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piAddr, 2, &iRows, &iCols, piLen, description); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + descriptionCount = iRows; + + // Extracting Count attribute of input argument + sciErr = getMatrixOfInteger32InList(pvApiCtx, piAddr, 3, &iRows, &iCols, &count); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + location = (char***) malloc(sizeof(char**) * descriptionCount); + sciErr = getListItemAddress(pvApiCtx, piAddr, 4, &piChild); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + for(int iter = 1; iter<=descriptionCount; iter++) + { + sciErr = getMatrixOfStringInList(pvApiCtx, piChild, iter, &iRows, &iCols, NULL, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + piLen = (int*)malloc(sizeof(int) * iRows * iCols); + + sciErr = getMatrixOfStringInList(pvApiCtx, piChild, iter, &iRows, &iCols, piLen, NULL); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + + location[iter-1] = (char**)malloc(sizeof(char*) * iRows * iCols); + + for(int colIter = 0 ; colIter < iRows * iCols ; colIter++) + { + location[iter-1][colIter] = (char*)malloc(sizeof(char) * (piLen[colIter] + 1));//+ 1 for null termination + } + + sciErr = getMatrixOfStringInList(pvApiCtx, piChild, iter, &iRows, &iCols, piLen, location[iter-1]); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + } + //------Actual processing------// + if(descriptionCount != classifierDescriptionCount) + { + Scierror(999, "Error: The input imageSet does not match the classifier's training set.\n"); + return 0; + } + for(int i=0; i<descriptionCount; i++) + { + if(strcmp(classifierDescription[i],description[i])!=0) + { + Scierror(999, "Error: The input imageSet does not match the classifier's training set.\n"); + return 0; + } + } + sciprint("Evaluating image category classifier for %d categories.\n",descriptionCount); + sciprint("--------------------------------------------------------\n\n"); + for(int i=0;i<descriptionCount;i++) + { + sciprint("# Category %d: %s\n",i+1,description[i]); + } + sciprint("\n"); + confMatrix = (double*) malloc(sizeof(double)*descriptionCount*descriptionCount); + for(int i=0;i<descriptionCount*descriptionCount;i++) + { + confMatrix[i]=0; + } + FileStorage fs(bagOfFeaturesLocation, FileStorage::READ); + fs["dictionary"] >> dictionary; + fs.release(); + dictionarySize = dictionary.rows; + bowDE.setVocabulary(dictionary); + svm.load(classifierLocation); + for(int i=0; i<descriptionCount;i++) + { + sciprint("# Evaluating %d images from category %d ...",count[i],i+1); + for(int j=0; j<count[i]; j++) + { + features.release(); + keyPoints.clear(); + fileName = location[i][j]; + inp = imread(fileName); + detector.detect(inp, keyPoints); + bowDE.compute(inp, keyPoints, features); + response = svm.predict(features); + confMatrix[i+(int)response*descriptionCount]++; + } + sciprint("done.\n"); + } + sciprint("\n"); + sciprint("\t PREDICTED\n"); + sciprint("KNOWN\t|"); + for(int i=0;i<descriptionCount;i++) + { + sciprint(" %d\t",i+1); + } + sciprint("\n"); + for(int i=0; i<descriptionCount;i++) + { + sciprint("%d\t|",i+1); + for(int j=0; j<descriptionCount; j++) + { + confMatrix[i+descriptionCount*j] /= count[i]; + sciprint(" %.2f\t",confMatrix[i+descriptionCount*j]); + } + sciprint("\n"); + } + sciprint("\n"); + for(int i=0;i<descriptionCount*descriptionCount;i=i+descriptionCount+1) + { + avgAccuracy += confMatrix[i]; + } + sciprint("# Average accuracy: %f\n",avgAccuracy/descriptionCount); + //------Create output arguments------// + sciErr = createMatrixOfDouble(pvApiCtx, nbInputArgument(pvApiCtx)+1, descriptionCount, descriptionCount, confMatrix); + if(sciErr.iErr) + { + printError(&sciErr, 0); + return 0; + } + //------Return Arguments------// + AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1; + ReturnArguments(pvApiCtx); + return 0; + } + /* ==================================================================== */ +} |