26 lines
1.1 KiB
Python
26 lines
1.1 KiB
Python
import cv2
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import numpy as np
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from modules.shared import opts
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DEBUG_MODE = opts.data.get("deforum_debug_mode_enabled", False)
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def unsharp_mask(img, kernel_size=(5, 5), sigma=1.0, amount=1.0, threshold=0, mask=None):
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if amount == 0:
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return img
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# Return a sharpened version of the image, using an unsharp mask.
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# If mask is not None, only areas under mask are handled
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blurred = cv2.GaussianBlur(img, kernel_size, sigma)
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sharpened = float(amount + 1) * img - float(amount) * blurred
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sharpened = np.maximum(sharpened, np.zeros(sharpened.shape))
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sharpened = np.minimum(sharpened, 255 * np.ones(sharpened.shape))
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sharpened = sharpened.round().astype(np.uint8)
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if threshold > 0:
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low_contrast_mask = np.absolute(img - blurred) < threshold
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np.copyto(sharpened, img, where=low_contrast_mask)
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if mask is not None:
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mask = np.array(mask)
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masked_sharpened = cv2.bitwise_and(sharpened, sharpened, mask=mask)
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masked_img = cv2.bitwise_and(img, img, mask=255-mask)
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sharpened = cv2.add(masked_img, masked_sharpened)
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return sharpened
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