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import sys
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print('python 版本：',sys.version.split('|')[0])
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#python 版本： 3.11.4

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%matplotlib qt
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from scipy import ndimage
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from PIL import Image
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import matplotlib.pyplot as plt
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import numpy as np
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#中文乱码的处理
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plt.rcParams['font.sans-serif']=['Microsoft YaHei']
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def blur_image(image_path):
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    image=np.array(Image.open(image_path))
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    image = np.rot90(image,-1)  #对图片顺时针旋转90度
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    plt.figure(figsize=(5, 15),dpi=100)
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    plt.subplot(221)
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    plt.imshow(image)
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    plt.title("原始图片")
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    plt.axis( 'off')
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    sigma = 5
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    blurred_image = np.zeros(image.shape, dtype=np.uint8)
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    for i in range(3):  #对图像的每一个通道都应用高斯滤波
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        blurred_image[:,:,i] = ndimage.gaussian_filter(image[:,:,i], sigma)
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    plt.subplot(222)
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    plt.imshow(blurred_image)
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    plt.title(f'模糊化的图像 (sigma={sigma})')
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    plt.axis('off')
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    sigma = 10
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    blurred_image = np.zeros(image.shape, dtype=np.uint8)
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    for i in range(3):  #对图像的每一个通道都应用高斯滤波
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        blurred_image[:,:,i] = ndimage.gaussian_filter(image[:,:,i], sigma)
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    plt.subplot(223)
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    plt.imshow(blurred_image)
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    plt.title(f'模糊化的图像 (sigma={sigma})')
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    plt.axis('off')
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    sigma = 20
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    blurred_image = np.zeros(image.shape, dtype=np.uint8)
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    for i in range(3):  #对图像的每一个通道都应用高斯滤波
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        blurred_image[:,:,i] = ndimage.gaussian_filter(image[:,:,i], sigma)
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    plt.subplot(224)
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    plt.imshow(blurred_image)
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    plt.title(f'模糊化的图像 (sigma={sigma})')
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    plt.axis('off')
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    plt.subplots_adjust(top=0.9,
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                        bottom=0.1,
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                        left=0.125,
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                        right=0.9,
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                        hspace=0.05,
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                        wspace=0.07)
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    plt.show()
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image_path ='秋天的银杏树.jpg'
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blur_image(image_path)