I have my FLANN matcher here:
flann_params = dict(algorithm = 1, trees = 4)
matcher = cv2.FlannBasedMatcher(flann_params, {})
I add descriptors of training images to it in a loop and then I train it:
matcher.add([descriptors])
matcher.train()
Few more related methods:
matcher.clear()
matcher.empty()
Both clear the train descriptor collection (right?)
But what I really want is:
Store the descriptors to disk and simply load them into the matcher and then train it
OR
Save the matcher data to disk so that I don't have to train images everytime I run the program.Make the matcher editable: if I delete an image off the disk, it shouldn't be found by the matcher. Maybe something like
matcher.clear(index_of_image_deleted)