/*!
Detect using the cascade classifier.
\param I: Grayscale image.
\param func: Function pointer to eliminate detections according to specific criterion
\param scaleFactor: Parameter specifying how much the image size is reduced at each image scale.
\param minNeighbors: Parameter specifying how many neighbors each candidate rectangle should have to retain it.
\param minSize: Minimum possible object size. Objects smaller than that are ignored.
\param maxSize: Maximum possible object size. Objects larger than that are ignored.
*/
void vpCascadeClassifier::detect(const vpImage<unsigned char> &I,
bool (*func)(const vpImage<unsigned char> &I, const vpRect &boundingBox),
const double scaleFactor, const int minNeighbors, const cv::Size &minSize, const cv::Size &maxSize) {
if (m_classifierDetector.empty()) {
clear();
throw vpException(vpException::fatalError, "Empty classifier !");
}
if(m_prevI.getWidth() == 0 || m_prevI.getHeight() == 0) {
m_prevI = I;
}
computeDetection(I, scaleFactor, minNeighbors, minSize, maxSize);
//Custom supplied filtering
if(func != NULL) {
for(std::vector<vpRect>::iterator it = m_objectBoundingBoxes.begin(); it != m_objectBoundingBoxes.end();) {
if(!func(I, *it)) {
m_vectorOfDetectedObjects.push_back(vpObjectDetection(*it, vpObjectDetection::FILTERED_STATUS));
it = m_objectBoundingBoxes.erase(it);
} else {
++it;
}
}
}
computeMatching(I);
m_prevI = I;
}
int main(int argc, char *argv[])
{
// Read command line files
// Init cuda
CUcontext cuContext;
initCuda(cuContext);
// Image buffer allocation
unsigned int depth =4;
unsigned int width=960;
unsigned int height=1080;
size_t bufferSize = sizeof(unsigned char)*width*height*depth;
unsigned char *imgRight = (unsigned char*)malloc(bufferSize);
unsigned char *imgLeft= (unsigned char*)malloc(bufferSize);
// Read the list of test files
std::vector<std::string> testsFiles;
readTestsFiles(testsFiles, "./tests.txt");
// Launch tests
for(int i=0; i<testsFiles.size(); i++)
{
std::stringstream testImage1;
testImage1 << "./" << testsFiles[i] << "_1.dat";
std::stringstream testImage2;
testImage2 << "./" << testsFiles[i] << "_2.dat";
readTestImage( testImage1.str(), imgRight, bufferSize);
readTestImage( testImage2.str(), imgLeft, bufferSize);
VertexBufferObject rightPoints;
VertexBufferObject leftPoints;
DescriptorData rightDescriptors;
DescriptorData leftDescriptors;
computeDescriptorsLane(imgRight, depth, width, height, rightPoints, rightDescriptors);
computeDescriptorsLane(imgLeft, depth, width, height, leftPoints, leftDescriptors);
UInt2 imgSize(1920,1080);
vector<CvPoint2D32f> leftMatchedPts;
vector<CvPoint2D32f> rightMatchedPts;
leftMatchedPts.reserve(10000);
rightMatchedPts.reserve(10000);
computeMatching( leftDescriptors, rightDescriptors, leftMatchedPts, rightMatchedPts, imgSize);
}
// finalize cuda
CUresult cerr = cuCtxDestroy(cuContext);
checkError(cerr);
return 0;
}
