I am having a little bit of trouble creating a haar classifier. I need to build up a classifier to detect cars. At the moment I made a program in python that reads in an image, I draw a rectangle around the area the object is in, Once the rectangle is drawn, it outputs the image name, the top left and bottom right coordinates of the rectangle. I am unsure of where to go from here and how to actually build up the classifier. Can anyone offer me any help?
EDIT*
I am looking for help on how to use the opencv_traincascade. I have looked at the documentation but I can't quite figure out how to use it to create the xml file to be used in the detection program.
This looks like you need to determine what features you would like to train your classifier on first, as using the haar classifier it benefits from those extra features. From there you will need to train the classifier, this requires you to get a lot of images that have cars and those that do not have cars in them and then run it over this and having it tweak the average it is shooting for in order to classify to the best it can with your selected features.
To get a better classifier you will have to figure out the order of your features and the optimal order you put them together to further dive into the object and determine if it is in fact what you are looking for. Again this will require a lot of examples for your particular features and your problem as a whole.