doodle.py 文件源码

def do_match_patches(self, layer):
        # Use node in the model to compute the result of the normalized cross-correlation, using results from the
        # nearest-neighbor layers called 'nn3_1' and 'nn4_1'.
        dist = self.matcher_outputs[layer]
        dist = dist.reshape((dist.shape[1], -1))
        # Compute the score of each patch, taking into account statistics from previous iteration. This equalizes
        # the chances of the patches being selected when the user requests more variety.
        offset = self.matcher_history[layer].reshape((-1, 1))
        scores = (dist - offset * args.variety)
        # Pick the best style patches for each patch in the current image, the result is an array of indices.
        # Also return the maximum value along both axis, used to compare slices and add patch variety.
        return [scores.argmax(axis=0), scores.max(axis=0), dist.max(axis=1)]


    #------------------------------------------------------------------------------------------------------------------
    # Error/Loss Functions
    #------------------------------------------------------------------------------------------------------------------