| import numpy as np |
| import cv2 as cv |
| from PIL import Image |
|
|
| def norm_mat(mat): |
| return cv.normalize(mat, None, 0, 255, cv.NORM_MINMAX).astype(np.uint8) |
|
|
| def equalize_img(img): |
| ycrcb = cv.cvtColor(img, cv.COLOR_BGR2YCrCb) |
| ycrcb[:, :, 0] = cv.equalizeHist(ycrcb[:, :, 0]) |
| return cv.cvtColor(ycrcb, cv.COLOR_YCrCb2BGR) |
|
|
| def create_lut(intensity, gamma): |
| lut = np.zeros((256, 1, 3), dtype=np.uint8) |
| for i in range(256): |
| lut[i, 0, 0] = min(255, max(0, i + intensity)) |
| lut[i, 0, 1] = min(255, max(0, i + intensity)) |
| lut[i, 0, 2] = min(255, max(0, i + intensity)) |
| return lut |
|
|
| def gradient_processing(image, intensity=90, blue_mode="Abs", invert=False, equalize=False): |
| """Apply gradient processing to an image. |
| |
| Args: |
| image (Image.Image, string: filepath): The input image to analyze. |
| intensity (int, optional): The intensity of the gradient. Defaults to 90. |
| blue_mode (str, optional): The mode to use for the blue channel. Defaults to "Abs". |
| invert (bool, optional): Whether to invert the gradient. Defaults to False. |
| equalize (bool, optional): Whether to equalize the gradient. Defaults to False. |
| |
| Returns: |
| Image.Image: A PIL image of the gradient. |
| """ |
| image = np.array(image) |
| dx, dy = cv.spatialGradient(cv.cvtColor(image, cv.COLOR_BGR2GRAY)) |
| intensity = int(intensity / 100 * 127) |
| if invert: |
| dx = (-dx).astype(np.float32) |
| dy = (-dy).astype(np.float32) |
| else: |
| dx = (+dx).astype(np.float32) |
| dy = (+dy).astype(np.float32) |
| dx_abs = np.abs(dx) |
| dy_abs = np.abs(dy) |
| red = ((dx / np.max(dx_abs) * 127) + 127).astype(np.uint8) |
| green = ((dy / np.max(dy_abs) * 127) + 127).astype(np.uint8) |
| if blue_mode == "None": |
| blue = np.zeros_like(red) |
| elif blue_mode == "Flat": |
| blue = np.full_like(red, 255) |
| elif blue_mode == "Abs": |
| blue = norm_mat(dx_abs + dy_abs) |
| elif blue_mode == "Norm": |
| blue = norm_mat(np.linalg.norm(cv.merge((red, green)), axis=2)) |
| else: |
| blue = None |
| gradient = cv.merge([blue, green, red]) |
| if equalize: |
| gradient = equalize_img(gradient) |
| elif intensity > 0: |
| gradient = cv.LUT(gradient, create_lut(intensity, intensity)) |
| return Image.fromarray(gradient) |
