• 任务20


    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)

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  • 原文地址:https://www.cnblogs.com/670ling/p/12838587.html
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