How do I verify images in a TensorFlow Dataset?

Question

I am creating a tensor flow dataset of labels and images using the following code taken from TensorFlow documentation here.

# Reads an image from a file, decodes it into a dense tensor, and resizes it
# to a fixed shape.
def _parse_function(filename, label):
  image_string = tf.read_file(filename)
  image_decoded = tf.image.decode_jpeg(image_string)
  image_resized = tf.image.resize_images(image_decoded, [28, 28])
  return image_resized, label

# A vector of filenames.
filenames = tf.constant(["/var/data/image1.jpg", "/var/data/image2.jpg", ...])

# `labels[i]` is the label for the image in `filenames[i].
labels = tf.constant([0, 37, ...])

dataset = tf.data.Dataset.from_tensor_slices((filenames, labels))
dataset = dataset.map(_parse_function)

I now want to verify that the images have been added to the dataset and check the dimensions. How do I go about doing that?

Answer 1

A standard way to access elements in dataset is to make an iterator

iterator = dataset.make_one_shot_iterator()
image, label = iterator.get_next()

with tf.Session() as sess:
  print(sess.run(label))
  print(sess.run(image.get_shape()))