from PIL import Image from PIL import ImageEnhance import numpy as np # image = Image.open('file:///C:/Users/25764/Desktop/新建位图图像.bmp') #image.show() def BrightnessEnhancement(brightness): # ''' # #亮度增强 :brightness在(0-1)之间,新图像较原图暗,在(1-~)新图像较原图亮 , # ##brightness=1,保持原图像不变;可自定义参数范围 # ''' image = Image.open(filepath) enh_bri = ImageEnhance.Brightness(image) # brightness =1.5 image_brightened = enh_bri.enhance(brightness) image_brightened.show() def ContrastEnhancement(contrast): # ''' # #对比度增强: 可自定义参数contrast范围,contrast=1,保持原图像不变 # ''' image = Image.open(filepath) enh_con = ImageEnhance.Contrast(image) # contrast =1.5 image_contrasted = enh_con.enhance(contrast) image_contrasted.show() def ColorEnhancement(color): # ''' # #色度增强 : 饱和度 color=1,保持原图像不变 # ''' image = Image.open(filepath) enh_col = ImageEnhance.Color(image) # color =0.8 image_colored = enh_col.enhance(color) image_colored.show() def SharpnessEnhancement(sharpness): # ''' # #锐度增强: 清晰度 sharpness=1,保持原图像不变 # ''' image = Image.open(filepath) enh_sha = ImageEnhance.Sharpness(image) # sharpness = 2 image_sharped = enh_sha.enhance(sharpness) image_sharped.show() def Filter(image): # """ # 色彩窗的半径 # 图像将呈现类似于磨皮的效果 # """ #image:输入图像,可以是Mat类型, # 图像必须是8位或浮点型单通道、三通道的图像 #0:表示在过滤过程中每个像素邻域的直径范围,一般为0 #后面两个数字:空间高斯函数标准差,灰度值相似性标准差 import cv2 image =cv2.imread(filepath) Remove=cv2.bilateralFilter(image,0,0,10) cv2.imshow('filter',Remove) cv2.waitKey(0) cv2.destroyAllWindows() # res = np.uint8(np.clip((1.2 * image + 10), 0, 255)) # tmp = np.hstack((dst, res)) # cv2.imshow('bai',res) def WhiteBeauty(image,whi): # ''' # 美白 # ''' import cv2 image =cv2.imread(filepath) white = np.uint8(np.clip((whi * image + 10), 0, 255)) cv2.imshow('bai',white) cv2.waitKey(0) cv2.destroyAllWindows() if __name__ =="__main__": filepath = 'C:/Users/25764/Pictures/Saved Pictures/timg.jpg' brightness = 1.5 contrast = 0.2 color=1.9 sharpness=0.1 BrightnessEnhancement(brightness) ContrastEnhancement(contrast) ColorEnhancement(color) SharpnessEnhancement(sharpness) whi = 1.2 image =cv2.imread('C:/Users/25764/Pictures/Saved Pictures/timg.jpg') Filter(image) WhiteBeauty(image,whi)