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/***************************************************
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_trainImageCategoryClassifier(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 *fileName = NULL;
Mat dictionary,inp,features;
vector<KeyPoint> keyPoints;
int *piAddr = NULL;
int *piChild = NULL;
int iRows, iCols;
char **pstData = NULL;
int *piLen = NULL;
int *count = NULL;
char **description = NULL;
char ***location = NULL;
char *bagOfFeaturesLocation = NULL;
int descriptionCount;
char *classifierLocation = "classifier.yml";
char *objectType = "classifier";
//------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 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 #1 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;
}
}
// 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 bagOfFeatures.\n");
return 0;
}
// Extracting object type and checking if type is bagOfFeatures
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],"bagOfFeatures")==0))
{
Scierror(999, "Error: The input argument #2 is not of type bagOfFeatures.\n");
return 0;
}
// Extracting name of next argument takes three calls to getMatrixOfString
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 bagOfFeatures argument.");
return 0;
}
bagOfFeaturesLocation = pstData[0];
//------Actual processing------//
FileStorage fs(bagOfFeaturesLocation, FileStorage::READ);
fs["dictionary"] >> dictionary;
fs.release();
if(dictionary.rows==0 || dictionary.cols==0)
{
sciprint("Error: The provided file for bagOfFeatures may be invalid.\n");
}
sciprint("Training an 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");
int dictionarySize = dictionary.rows;
Mat labels(0, 1, CV_32FC1);
Mat trainingData(0, dictionarySize, CV_32FC1);
bowDE.setVocabulary(dictionary);
for(int i=0; i<descriptionCount;i++)
{
sciprint("# Encoding features for Category %d ...",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);
trainingData.push_back(features);
labels.push_back((float) i);
}
sciprint("done.\n");
}
sciprint("\n# Training the category classifier...");
CvSVMParams params;
params.kernel_type=CvSVM::RBF;
params.svm_type=CvSVM::C_SVC;
params.gamma=0.50625000000000009;
params.C=312.50000000000000;
params.term_crit=cvTermCriteria(CV_TERMCRIT_ITER,100,0.000001);
CvSVM svm;
svm.train(trainingData,labels,cv::Mat(),cv::Mat(),params);
svm.save(classifierLocation);
sciprint("done.\n");
//------Create output arguments------//
sciErr = createList(pvApiCtx, nbInputArgument(pvApiCtx) + 1, 4, &piAddr);
if(sciErr.iErr)
{
printError(&sciErr, 0);
return 0;
}
sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 1, 1, 1, &objectType);
if(sciErr.iErr)
{
printError(&sciErr, 0);
return 0;
}
sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 2, 1, 1, &classifierLocation);
if(sciErr.iErr)
{
printError(&sciErr, 0);
return 0;
}
sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 3, 1, 1, &bagOfFeaturesLocation);
if(sciErr.iErr)
{
printError(&sciErr, 0);
return 0;
}
sciErr = createMatrixOfStringInList(pvApiCtx, nbInputArgument(pvApiCtx)+1, piAddr, 4, descriptionCount, 1, description);
if(sciErr.iErr)
{
printError(&sciErr, 0);
return 0;
}
//------Return Arguments------//
AssignOutputVariable(pvApiCtx, 1) = nbInputArgument(pvApiCtx)+1;
ReturnArguments(pvApiCtx);
return 0;
}
/* ==================================================================== */
}
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