sobel_x = tf.constant([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]], tf.float32)
sobel_x_filter = tf.reshape(sobel_x, [1, 3, 3, 3, 3]) # here it crashes

import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt

im0 = plt.imread('../../data/im0.png') # already divided by 255
sobel_x = tf.constant([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]], tf.float32)
sobel_x_filter = tf.reshape(sobel_x, [1, 3, 3, 3, 3])
image = tf.placeholder(tf.float32, shape=[496, 718, 3])
image_resized = tf.expand_dims(tf.expand_dims(image, 0), 0)

filters_x  = tf.nn.conv3d(image_resized, filter=sobel_x_filter, strides=[1,1,1,1,1],
                          padding='SAME', data_format='NDHWC')

with tf.Session('') as sess:
    sess.run([tf.global_variables_initializer(), tf.local_variables_initializer()])
    coord = tf.train.Coordinator()
    threads = tf.train.start_queue_runners(sess=sess, coord=coord)
    feed_dict = {image: im0}
    img  =  filters_x.eval(feed_dict=feed_dict)

plt.figure(0), plt.title('red'), plt.imshow(np.squeeze(img[...,0])),
plt.figure(1), plt.title('green'), plt.imshow(np.squeeze(img[...,1])),
plt.figure(2), plt.title('blue'), plt.imshow(np.squeeze(img[...,2]))