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Sleeping
| import cv2 | |
| import numpy as np | |
| import os | |
| # create_watermark =============================================================== | |
| # return: | |
| # (<Boolean> True/False), depending on the transformation process | |
| def create_watermark(nude): | |
| # Add alpha channel if missing | |
| # if nude.shape[2] < 4: | |
| # nude = np.dstack([nude, np.ones((512, 512), dtype="uint8") * 255]) | |
| # watermark = cv2.imread("fake.png", cv2.IMREAD_UNCHANGED) | |
| # f1 = np.asarray([0, 0, 0, 250]) # red color filter | |
| # f2 = np.asarray([255, 255, 255, 255]) | |
| # mask = cv2.bitwise_not(cv2.inRange(watermark, f1, f2)) | |
| # mask_inv = cv2.bitwise_not(mask) | |
| # res1 = cv2.bitwise_and(nude, nude, mask = mask) | |
| # # res2 = cv2.bitwise_and(nude, nude, mask = mask) | |
| # # res2 = cv2.bitwise_and(watermark, watermark, mask = mask_inv) | |
| # res = res1 | |
| # alpha = 0.6 | |
| # return cv2.addWeighted(res, alpha, nude, 1 - alpha, 0) | |
| return nude |