Deep Learning with TensorFlow

Softmax loader source code

To load the network and to test on a single image, you need to execute the following lines of code. Here is the full source code:

import matplotlib.pyplot as plt import tensorflow as tf imort numpy as np import mnist_data  mnist = mnist_data.read_data_sets('data', one_hot=True) sess = tf.InteractiveSession() new_saver = tf.train.import_meta_graph('saved_mnist_cnn.ckpt.meta') new_saver.restore(sess, 'saved_mnist_cnn.ckpt') tf.get_default_graph().as_graph_def() x = sess.graph.get_tensor_by_name("input:0") y_conv = sess.graph.get_tensor_by_name("output:0") image_b = mnist.test.images[100] result = sess.run(y_conv, feed_dict={x:image_b}) print(result) print(sess.run(tf.argmax(result, 1)))  plt.imshow(image_b.reshape([28, ...