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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:

  1. 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.

  2. 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)

sundar nataraj
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