In [34]:

    

from PIL import Image
jpgfile = Image.open(".\\input\\train\\000bec180eb18c7604dcecc8fe0dba07.jpg")
print(jpgfile.bits, jpgfile.size, jpgfile.format)
jpgfile = Image.open(".\\input\\train\\00a338a92e4e7bf543340dc849230e75.jpg")
print(jpgfile.bits, jpgfile.size, jpgfile.format)
jpgfile = Image.open(".\\input\\train\\00a366d4b4a9bbb6c8a63126697b7656.jpg")
print(jpgfile.bits, jpgfile.size, jpgfile.format)

jpgfile = Image.open(".\\input\\test\\00a3edd22dc7859c487a64777fc8d093.jpg")
print(jpgfile.bits, jpgfile.size, jpgfile.format)
jpgfile = Image.open(".\\input\\test\\00a6892e5c7f92c1f465e213fd904582.jpg")
print(jpgfile.bits, jpgfile.size, jpgfile.format)
jpgfile = Image.open(".\\input\\test\\00a558277e1f03b71d8c813e03344ddf.jpg")
print(jpgfile.bits, jpgfile.size, jpgfile.format)


    

    




8 (500, 375) JPEG
8 (200, 280) JPEG
8 (500, 375) JPEG
8 (500, 375) JPEG
8 (500, 347) JPEG
8 (375, 500) JPEG

In [28]:

    

import matplotlib.pyplot as plt # plt 用于显示图片
import matplotlib.image as mpimg # mpimg 用于读取图片
import numpy as np
 
lena = mpimg.imread(".\\input\\train\\000bec180eb18c7604dcecc8fe0dba07.jpg") # 读取和代码处于同一目录下的 lena.png
# 此时 lena 就已经是一个 np.array 了，可以对它进行任意处理
print(lena.shape) #(512, 512, 3)
print(type(lena[0,0,0]))
plt.imshow(lena) # 显示图片
plt.axis('off') # 不显示坐标轴
plt.show()


    

    




(375, 500, 3)
<class 'numpy.uint8'>






    

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