深度学习图片EXIF问题与图片大小判断

用于解决下载图像读取错误，exif问题，与判断图像重新定义大小是否会出错问题，并找出出错图像。

import piexif
import os
from PIL import Image

# 图像存放绝对地址
original_dataset_dir='/home/lyuncxw/AI/bird/bird1'

# 重定义图像大小,元组
target_size = [300,300]
width_height_tuple = (target_size[1], target_size[0])

# 重采样滤波器参数
'''
        fill_mode: One of {"constant", "nearest", "reflect" or "wrap"}.
            Default is 'nearest'.
            Points outside the boundaries of the input are filled
            according to the given mode:
            - 'constant': kkkkkkkk|abcd|kkkkkkkk (cval=k)
            - 'nearest':  aaaaaaaa|abcd|dddddddd
            - 'reflect':  abcddcba|abcd|dcbaabcd
            - 'wrap':  abcdabcd|abcd|abcdabcd
'''

# interpolation='nearest'  #即 -> pil_image.NEAREST
# resample = _PIL_INTERPOLATION_METHODS[interpolation]

# 利用format()函数把字符串当成一个模板，通过传入的参数进行格式化，并且使用大括号‘{}’作为特殊字
# 符代替'%'

fnames = ['bird1.{}.jpg'.format(i) for i in range(1000)]

# 循环抛出异常
for fname in fnames:
    try:
        src = os.path.join(original_dataset_dir, fname)
        piexif.remove(src)     # 去除图片exif
        img = Image.open(src)    # 打开图片
        img = img.resize(width_height_tuple, Image.NEAREST)
        # img = img.resize(width_height_tuple, pil_image.NEAREST)
    except IOError:
        print(src)