Loading Custom Dataset into TensorFlow CNN

Question

We are using TensorFlow and python to create a custom CNN that will classify images into one of several categories. We have created our CNN based on this tutorial: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/tutorials/layers/cnn_mnist.py

Instead of reading in a pre-existing dataset like the MNIST dataset used in the tutorial, we would like to read in all images from multiple folders. The name of each folder is the label associated with all the images in that folder. Unfortunately we're very new to python and TensorFlow, could someone point us in the right direction, either with a tutorial or some basic code?

Thank you so much!

Answer 1

consider using the glob package. it allows you to import multiple files in subdirectories easily using patterns. https://docs.python.org/2/library/glob.html

import glob
import matplotlib.pyplot as plt
import numpy as np
images = glob.glob(<file pattern>)
img_list = [plt.imread(image) for image in images]
img_array = np.stack(tuple(img_list))

I haven't tested this so there might be errors but it should make a 3-d numpy array of images (each image a 2-d array). Is this the format you were looking for?