python如何将图片转换素描画

 # -*- coding:utf-8 -*- import cv2 import numpy as np from tkinter import filedialog, Tk from os import getcwd from re import findall def open_path(): # 图片路径 root = Tk() root.withdraw() file_path = (filedialog.askopenfilename(title='选择图片文件', filetypes=[('All Files', '*')])) return file_path def dodgeNaive(image, mask): # determine the shape of the input image width, height = image.shape[:2] # prepare output argument with same size as image blend = np.zeros((width, height), np.uint8) for col in range(width): for row in range(height): # do for every pixel if mask[col, row] == 255: # avoid division by zero blend[col, row] = 255 else: # shift image pixel value by 8 bits # divide by the inverse of the mask tmp = (image[col, row] << 8) / (255 - mask) # print('tmp={}'.format(tmp.shape)) # make sure resulting value stays within bounds if tmp.any() > 255: tmp = 255 blend[col, row] = tmp return blend def dodgeV2(image, mask): return cv2.divide(image, 255 - mask, scale=256) def burnV2(image, mask): return 255 - cv2.divide(255 - image, 255 - mask, scale=256) def rgb_to_sketch(src_image_name): print('转换中......') img_rgb = cv2.imread(src_image_name) img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY) # 读取图片时直接转换操作 # img_gray = cv2.imread('example.jpg-600', cv2.IMREAD_GRAYSCALE) img_gray_inv = 255 - img_gray img_blur = cv2.GaussianBlur(img_gray_inv, ksize=(21, 21), sigmaX=0, sigmaY=0) img_blend = dodgeV2(img_gray, img_blur) # cv2.imshow('original', img_rgb) # cv2.imshow('gray', img_gray) # cv2.imshow('gray_inv', img_gray_inv) # cv2.imshow('gray_blur', img_blur) cv2.imwrite(dst_image_name, img_blend) save_path = getcwd() + "\\" + dst_image_name # 保存路径 print('转换完成!!!\n') print('保存路径:' + save_path) cv2.imshow(save_path, img_blend) cv2.waitKey(0) cv2.destroyAllWindows() if __name__ == '__main__': print('请选择图片(路径不要含中文)：') src_image_name = open_path() # 文件路径 print(src_image_name + '\n') image_name = ''.join(findall(r'[^\\/:*?"<>|\r\n]+$', src_image_name)) # 获取文件名 dst_image_name = 'Sketch_' + image_name rgb_to_sketch(src_image_name)