| import cv2 |
| import numpy as np |
| from modules.shared import opts |
|
|
| DEBUG_MODE = opts.data.get("deforum_debug_mode_enabled", False) |
|
|
| def unsharp_mask(img, kernel_size=(5, 5), sigma=1.0, amount=1.0, threshold=0, mask=None): |
| if amount == 0: |
| return img |
| |
| |
| 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 |
|
|
