tensorflow Reading the data How to load images and labels from a TXT file

Example

It has not been explained in the Tensorflow documentation how to load images and labels directly from a TXT file. The code below illustrates how I achieved it. However, it does not mean that is the best way to do it and that this way will help in further steps.

For instance, I'm loading the labels in one single integer value {0,1} while the documentation uses a one-hot vector [0,1].

# Learning how to import images and labels from a TXT file
#
# TXT file format
#
# path/to/imagefile_1 label_1
# path/to/imagefile_2 label_2
# ...                 ...
#
# where label_X is either {0,1}

#Importing Libraries
import os
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.python.framework import ops
from tensorflow.python.framework import dtypes

#File containing the path to images and the labels [path/to/images label]
filename = '/path/to/List.txt'

#Lists where to store the paths and labels
filenames = []
labels = []

#Reading file and extracting paths and labels
with open(filename, 'r') as File:
    infoFile = File.readlines() #Reading all the lines from File
    for line in infoFile: #Reading line-by-line
        words = line.split() #Splitting lines in words using space character as separator
        filenames.append(words[0])
        labels.append(int(words[1]))

NumFiles = len(filenames)

#Converting filenames and labels into tensors
tfilenames = ops.convert_to_tensor(filenames, dtype=dtypes.string)
tlabels = ops.convert_to_tensor(labels, dtype=dtypes.int32)

#Creating a queue which contains the list of files to read and the value of the labels
filename_queue = tf.train.slice_input_producer([tfilenames, tlabels], num_epochs=10, shuffle=True, capacity=NumFiles)

#Reading the image files and decoding them
rawIm= tf.read_file(filename_queue[0])
decodedIm = tf.image.decode_png(rawIm) # png or jpg decoder

#Extracting the labels queue
label_queue = filename_queue[1]

#Initializing Global and Local Variables so we avoid warnings and errors
init_op = tf.group(tf.local_variables_initializer() ,tf.global_variables_initializer())

#Creating an InteractiveSession so we can run in iPython
sess = tf.InteractiveSession()

with sess.as_default():
    sess.run(init_op)
    
    # Start populating the filename queue.
    coord = tf.train.Coordinator()
    threads = tf.train.start_queue_runners(coord=coord)

    for i in range(NumFiles): #length of your filenames list
        nm, image, lb = sess.run([filename_queue[0], decodedIm, label_queue])
        
        print image.shape
        print nm
        print lb
        
        #Showing the current image
        plt.imshow(image)
        plt.show()

    coord.request_stop()
    coord.join(threads)