2019-10-24 19:37:21 +00:00
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import numpy as np
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2017-08-16 12:24:29 +00:00
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2018-06-08 17:27:32 +00:00
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# credits to https://stackoverflow.com/users/6076729/manuel-lagunas
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2017-09-26 19:00:51 +00:00
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def rle_encode(mask_image):
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pixels = mask_image.flatten()
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# We avoid issues with '1' at the start or end (at the corners of
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# the original image) by setting those pixels to '0' explicitly.
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# We do not expect these to be non-zero for an accurate mask,
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# so this should not harm the score.
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pixels[0] = 0
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pixels[-1] = 0
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runs = np.where(pixels[1:] != pixels[:-1])[0] + 2
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runs[1::2] = runs[1::2] - runs[:-1:2]
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return runs
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