Tensorflow删除JFIF [英] Tensorflow Removing JFIF

问题描述

我对tensorflow非常陌生，我想清楚地知道，以下命令是做什么的？

  import tensorflow从tensorflow导入keras的tf 
到tensorflow.keras导入层的
到
导入os 
 
 num_skipped = 0 
 for folder_name in（ Cat，狗）：
 print（ folder_name：，folder_name）＃文件夹名称：猫
 folder_path = os.path.join（ Dataset / PetImages，folder_name）
 print（ folder_path： ，folder_path）#folder_path：os.listdir中的fname的数据集/ PetImages / Cat 
（folder_path）：
 print（ fname：，fname）#fname：5961.jpg 
 fpath = os.path.join（folder_path，fname）
 print（ fpath：，fpath）#fpath：Dataset / PetImages / Cat / 10591.jpg 
 try：
 fobj = open（ fpath， rb）
 is_jfif = tf.compat.as_bytes（ JFIF）in fobj.peek（10）
最后：
 fobj.close（）
 
如果不是is_jfif：
 num_skipped + = 1 
 ＃删除损坏的图像
 os.remove（fpath）
 
打印（已删除％d个图像％num_skipped）
  

Keras网站对上述代码的评论：

在处理大量在真实世界的图像数据中，损坏的图像是常见的情况。让我们过滤掉标题中不包含字符串 JFIF的错误编码的图像。

我想具体了解以下命令的作用，它是怎么做的？

  is_jfif = tf.compat.as_bytes（ JFIF）in fobj.peek（10）
  

我检查了API，但显然无法理解。

更好的解释将有很大帮助。

谢谢

解决方案

因此：

• tf.compat.as_bytes（ JFIF）将字符串 JFIF转换为字节。您也可以只使用 b JFIF ，尽管也许TensorFlow实现具有一些我不知道的优化。


• fobj.peek（10）理论上返回文件的前10个字节，但实际上，它通常返回整个文件。


• is_jfif 然后只检查转换后的 JFIF字符串是否是 fobj.peek 的结果。

I am quite new to tensorflow, I would like to clearly know, what does the below command do?

import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
import os

num_skipped = 0
for folder_name in ("Cat", "Dog"):
    print("folder_name:",folder_name) #folder_name: Cat
    folder_path = os.path.join("Dataset/PetImages", folder_name)
    print("folder_path:",folder_path) #folder_path: Dataset/PetImages/Cat
    for fname in os.listdir(folder_path):
        print("fname:",fname) #fname: 5961.jpg
        fpath = os.path.join(folder_path, fname)
        print("fpath:", fpath) #fpath: Dataset/PetImages/Cat/10591.jpg
        try:
            fobj = open(fpath, "rb")
            is_jfif = tf.compat.as_bytes("JFIF") in fobj.peek(10)
        finally:
            fobj.close()

        if not is_jfif:
            num_skipped += 1
            # Delete corrupted image
            os.remove(fpath)

print("Deleted %d images" % num_skipped)

Keras Website comment on the above code :

When working with lots of real-world image data, corrupted images are a common occurence. Let's filter out badly-encoded images that do not feature the string "JFIF" in their header.

I want to specifically know what does the below command do, how does it do ?

 is_jfif = tf.compat.as_bytes("JFIF") in fobj.peek(10)

I checked the API but wasn't clearly able to understand it.

A better explanation will be of much help.

Thanks

解决方案

Wikipedia explains that JPG files contain the string "JFIF" at the beginning of the file, encoded as bytes:

So:

• tf.compat.as_bytes("JFIF") converts the string "JFIF" to bytes. You could also just use b"JFIF", though maybe the TensorFlow implementation has some optimization I don't know about.
• fobj.peek(10) theoretically returns the first 10 bytes of the file, but in practice it often returns the entire file.
• is_jfif then just checks if the converted "JFIF" string is in the result of fobj.peek.

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