| # Copyright (C) 2023 Deforum LLC | |
| # | |
| # This program is free software: you can redistribute it and/or modify | |
| # it under the terms of the GNU Affero General Public License as published by | |
| # the Free Software Foundation, version 3 of the License. | |
| # | |
| # This program is distributed in the hope that it will be useful, | |
| # but WITHOUT ANY WARRANTY; without even the implied warranty of | |
| # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | |
| # GNU General Public License for more details. | |
| # | |
| # You should have received a copy of the GNU Affero General Public License | |
| # along with this program. If not, see <https://www.gnu.org/licenses/>. | |
| # Contact the authors: https://deforum.github.io/ | |
| import cv2 | |
| import numpy as np | |
| def unsharp_mask(img, kernel_size=(5, 5), sigma=1.0, amount=1.0, threshold=0, mask=None): | |
| if amount == 0: | |
| return img | |
| # Return a sharpened version of the image, using an unsharp mask. | |
| # If mask is not None, only areas under mask are handled | |
| blurred = cv2.GaussianBlur(img, kernel_size, sigma) | |
| sharpened = float(amount + 1) * img - float(amount) * blurred | |
| sharpened = np.maximum(sharpened, np.zeros(sharpened.shape)) | |
| sharpened = np.minimum(sharpened, 255 * np.ones(sharpened.shape)) | |
| sharpened = sharpened.round().astype(np.uint8) | |
| if threshold > 0: | |
| low_contrast_mask = np.absolute(img - blurred) < threshold | |
| np.copyto(sharpened, img, where=low_contrast_mask) | |
| if mask is not None: | |
| mask = np.array(mask) | |
| masked_sharpened = cv2.bitwise_and(sharpened, sharpened, mask=mask) | |
| masked_img = cv2.bitwise_and(img, img, mask=255-mask) | |
| sharpened = cv2.add(masked_img, masked_sharpened) | |
| return sharpened |