使用文件名数据集，创建图像到元组的数据集 [英] Using a dataset of filenames, create a dataset of images to tuples

问题描述

我在一个文件夹中创建了一个包含许多图像文件名的 tensorflow 数据集.这些图像被命名为 [index].jpg，其中 index 是一些用于标识图像的整数.我有一个字符串 'index' 的字典来标记为元组.如何使用 tf.data.Dataset.map 将索引映射到标签元组?

这是我试图传递给 map 函数的 map_func:

defgrabImages(filepath):index = getIndexFromFilePath(filepath)img = tf.io.read_file(文件路径)img = translateImage(img)字典 = getLabelDictionary()返回索引，img

其中字典是标签字典的索引，索引是文件路径的索引，如 tf.Tensor 和 img 是位于文件路径的预处理图像.

这会返回一个带有索引的数据集，作为张量，映射到相应的图像.有没有办法使用 dictionary 使用 dictionary[index] 之类的东西来获取 index 的标签?基本上，我想找到索引的字符串内容.

我曾尝试在 grabImages 函数中使用 .numpy() 和 .eval() 和当前会话，但都不起作用.

解决方案

这里有一个示例，说明如何在 tf.data.Dataset.map 函数中获取张量的字符串部分.

以下是我在代码中实现的步骤.

1. 你必须用tf.py_function(get_path, [x], [tf.string])来修饰map函数.您可以在此处找到有关 tf.py_function 的更多信息.
2. 您可以通过在 map 函数中使用 bytes.decode(file_path.numpy()) 来获取字符串部分.

代码 -

%tensorflow_version 2.x将张量流导入为 tf将 numpy 导入为 npdef get_path(file_path):打印(文件路径:"，bytes.decode(file_path.numpy())，类型(bytes.decode(file_path.numpy())))返回文件路径train_dataset = tf.data.Dataset.list_files('/content/bird.jpg')train_dataset = train_dataset.map(lambda x: tf.py_function(get_path, [x], [tf.string]))对于 train_dataset 中的 one_element:打印(一个元素)

输出 -

file_path:/content/bird.jpg (<tf.Tensor: shape=(), dtype=string, numpy=b'/content/bird.jpg'>,)

希望这能回答您的问题.

I create a tensorflow dataset of filenames of many images in a folder. The images are named [index].jpg, where index is some integer used to identify the images. I have a dictionary of string 'index' to labels as tuples. How, using tf.data.Dataset.map, can I map the index to a label tuple?

Here's the map_func I am trying to pass to the map function:

def grabImages(filepath):
   index = getIndexFromFilePath(filepath)
   img = tf.io.read_file(filepath)
   img = translateImage(img)
   dictionary = getLabelDictionary()
   return index, img

Where dictionary is the index to labels dict, index is the index of the filepath as tf.Tensor and img is a preprocessed image that was at the filepath.

This returns a dataset with the index, as a tensor, mapped to the corresponding image. Is there a way to get the labels of the index using dictionary using something like dictionary[index]? Basically, I want to find the string content of index.

I have tried using .numpy() and .eval() with the current session within the grabImages function, but neither work.

解决方案

Here is an example of how to get string part of a tensor in the tf.data.Dataset.map function.

Below are the steps I have implemented in the code to achieve this.

1. You have to decorate the map function with tf.py_function(get_path, [x], [tf.string]). You can find more about tf.py_function here.
2. You can get your string part by using bytes.decode(file_path.numpy()) in map function.

Code -

%tensorflow_version 2.x
import tensorflow as tf
import numpy as np

def get_path(file_path):
    print("file_path: ",bytes.decode(file_path.numpy()),type(bytes.decode(file_path.numpy())))
    return file_path

train_dataset = tf.data.Dataset.list_files('/content/bird.jpg')
train_dataset = train_dataset.map(lambda x: tf.py_function(get_path, [x], [tf.string]))

for one_element in train_dataset:
    print(one_element)

Output -

file_path:  /content/bird.jpg <class 'str'>
(<tf.Tensor: shape=(), dtype=string, numpy=b'/content/bird.jpg'>,)

Hope this answers your question.

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