python如何將圖片轉換素描畫
阿新 • • 發佈:2020-09-10
程式碼如下
# -*- 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(): # 圖片路徑 root = Tk() root.withdraw() file_path = (filedialog.askopenfilename(title='選擇圖片檔案',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,scale=256) def rgb_to_sketch(src_image_name): print('轉換中......') img_rgb = cv2.imread(src_image_name) img_gray = cv2.cvtColor(img_rgb,cv2.COLOR_BGR2GRAY) # 讀取圖片時直接轉換操作 # img_gray = cv2.imread('example.jpg',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 # 儲存路徑 print('轉換完成!!!\n') print('儲存路徑:' + save_path) cv2.imshow(save_path,img_blend) cv2.waitKey(0) cv2.destroyAllWindows() if __name__ == '__main__': print('請選擇圖片(路徑不要含中文):') src_image_name = open_path() # 檔案路徑 print(src_image_name + '\n') image_name = ''.join(findall(r'[^\\/:*?"<>|\r\n]+$',src_image_name)) # 獲取檔名 dst_image_name = 'Sketch_' + image_name rgb_to_sketch(src_image_name)
效果如下
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