mxl:

I used TensorFlow function tf.image.resize_images to resize my image, but I got this Error in Code: ValueError: 'images' contains no shape. The full code is below:

# -*- coding: utf-8 -*-
import tensorflow as tf
file = ["./1.jpg"]
f = tf.train.string_input_producer(file)
reader = tf.WholeFileReader()
key, img = reader.read(f)

img = tf.image.decode_image(img)
# img.set_shape([218,178,3])
img = tf.image.resize_images(img, [64,64])

coord = tf.train.Coordinator()    
with tf.Session() as sess:
    tf.train.start_queue_runners(coord=coord)
    image = sess.run(img)

The full Error information is

Traceback (most recent call last):
  File "image_read_test.py", line 10, in 
    img = tf.image.resize_images(img, [64,64])
  File "C:\Python35\lib\site-packages\tensorflow\python\ops\image_ops_impl.py", line 724, in resize_images
    raise ValueError('\'images\' contains no shape.')
ValueError: 'images' contains no shape.

Then I try to fix this, but only find a way like that

# -*- coding: utf-8 -*-
    import tensorflow as tf
    file = ["./1.jpg"]
    f = tf.train.string_input_producer(file)
    reader = tf.WholeFileReader()
    key, img = reader.read(f)

    img = tf.image.decode_image(img)
    # img.set_shape([218,178])
    # img = tf.image.resize_images(img, [64,64])

    coord = tf.train.Coordinator()    
    with tf.Session() as sess:
        tf.train.start_queue_runners(coord=coord)
        image = sess.run(img)
        image = tf.image.resize_images(image, [64,64])

Only in this way the function can work well, But I don't know why? Is the function tf.image.resize_images only take the numpy array as parameter? Or I can find another way to solve this problem? NB: img.set_shape([218,78,3]) does not work for me