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markloyman/crop_random_with_mask.py

Created September 28, 2017 19:58
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Random crop of an image and it's mask (crop is aware of mask region)
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crop_random_with_mask.py
def crop(image, mask, min_size= 128):
# Determine New Size on Y axis
max_size_y = image.shape[0]
mask_y = np.where(np.sum(mask, axis=1))
min_size_y = np.max(mask_y) - np.min(mask_y)
new_size_y = np.random.rand() * (max_size_y - min_size_y)
new_size_y = np.maximum(new_size_y, min_size).astype('uint16')
# Determine New Size on X axis
max_size_x = image.shape[1]
mask_x = np.where(np.sum(mask, axis=0))
min_size_x = np.max(mask_x) - np.min(mask_x)
new_size_x = np.random.rand() * (max_size_x - min_size_x)
new_size_x = np.maximum(new_size_x, min_size).astype('uint16')
# Determine crop translation on Y axis
min_crop_start_y = np.maximum(0, np.max(mask_y) - new_size_y)
max_crop_start_y = np.minimum(np.min(mask_y), max_size_y - new_size_y)
crop_start_y = min_crop_start_y + np.random.rand() * (max_crop_start_y - min_crop_start_y)
crop_start_y = crop_start_y.astype('uint16')
# Determine crop translation on X axis
min_crop_start_x = np.maximum(0, np.max(mask_x) - new_size_x)
max_crop_start_x = np.minimum(np.min(mask_x), max_size_x - new_size_x)
crop_start_x = min_crop_start_x + np.random.rand() * (max_crop_start_x - min_crop_start_x)
crop_start_x = crop_start_x.astype('uint16')
new_image = image[crop_start_y:crop_start_y + new_size_y, crop_start_x:crop_start_x + new_size_x]
new_mask = mask[crop_start_y:crop_start_y + new_size_y, crop_start_x:crop_start_x + new_size_x]
return new_image, new_mask
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