/*!
This is a basic version for returning the score of a feature on a certain position. This basic version will be called a lot, only if a specialised version of a channel (for example size, ...) will be used this function will be overloaded
\param F The feature to evaluate
\param Image The feature image (possible multi-channel). The structure of this image is dependend on the channel, so this allows to use specialised versions of images (such as 1 pixel large containing the layer-number)
\param offsetX the X-position in the image
\param offsetY the Y-position in the image
\param shrinking The shrinking used (not useable yet)
\param offset The channel inside the multi-channel image
\param method The method is default CHNFTRS, this is the only option currently available, but could later be extended with convolution
\author F. De Smedt
\date 2014
*/
float ChannelOld::giveScore(const Feature& F, const cv::Mat& Image, int offsetX, int offsetY, int shrinking, int offset, int method)
{
/*
Simple check if the offset is inside the available channels
*/
if (offset >= this->getChannelAmount()) {
std::cout << "Offset lies outside of number in internal channels" << std::endl;
exit(1);
}
/*
Check if the featureis inside the feature image. A fail is most probably due to a mismatch in model size and evaluation positions
*/
int FeaturePositionX = F.getX() + F.getWidth() + offsetX;
int FeaturePositionY = F.getY() + F.getHeight() + offsetY;
if (FeaturePositionX >= Image.cols || FeaturePositionY >= Image.rows) {
std::cout << "The features lies outside the image!!" << std::endl;
std::cout << "ImageSize: " << Image.cols << " x " << Image.rows << " Feature: X" << F.getX() << " width:" << F.getWidth() << " offsetX:" << offsetX << " Y:" << F.getY() << " height" << F.getHeight() << " offsetY" << offsetY << std::endl;
exit(4);
}
//Get the score of the feature out ofthe integral image
if (method == CHNFTRS) {
float a = Image.at<float>(F.getY() + offsetY, F.getX() + offsetX);
float b = Image.at<float>(F.getY() + offsetY, F.getX() + F.getWidth() + offsetX);
float d = Image.at<float>(F.getY() + F.getHeight() + offsetY, F.getX() + offsetX);
float c = Image.at<float>(F.getY() + F.getHeight() + offsetY, F.getX() + F.getWidth() + offsetX);
return (float)(a - b + c - d);
}
else {
std::cout << "Evaluation method not supported yet" << std::endl;
exit(3);
}
return 0;
}
bool StudentLocalization::stepFindChinContours(const IntensityImage &image, FeatureMap &features) const {
//Get the position of the mouth
Feature Mouth = features.getFeature(Feature::FEATURE_MOUTH_TOP);
Point2D<double> MouthPosition;
//Initialise the chin feature
std::vector<Point2D<double>> ChinPositions;
Feature Chin = Feature(Feature::FEATURE_CHIN);
Feature ChinContour = Feature(Feature::FEATURE_CHIN_CONTOUR);
int y = 0;
int m = 0;
//Draw a half circle starting from the center of the mouth
for (int j = HALF_CIRCLE; j > 0; j -= DEGREE_STEP){
//reset the position of the mouth
MouthPosition.set(Mouth.getX(), Mouth.getY());
MouthPosition.set(drawLine(j, START_POSITION, MouthPosition));
m = m + 1;
for (int i = 0; i < MEASURE_RANGE; i++){
MouthPosition.set(drawLine(j, MEASURE_STEP, MouthPosition));
Intensity pixel = image.getPixel(MouthPosition.getX(), MouthPosition.getY());
// If the intensity of the current pixel is lower than 2 (which means it is black)
if (pixel < 2){
// If the current angle is within the bounds of the half circle
if (j < RIGHT_HALF && j > LEFT_HALF){
ChinContour.addPoint(drawLine(j, 2, MouthPosition));
}
else{
//Draw a point on the mouth position, to indicate the detection failed.
ChinContour.addPoint(MouthPosition);
}
break;
}
}
}
features.putFeature(ChinContour);
return true;
}
