def predict_imagenet(filename):
test_x = ImageDataGenerator.get_image(filename)
X = tf.placeholder(tf.float32, [None, 227, 227, 3])
keep_prob = tf.placeholder(tf.float32)
model = AlexNet(X,keep_prob)
y_ = model.create_model()
prob = tf.nn.softmax(y_)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
model.initial_weights(sess)
y_,output = sess.run([y_,prob],feed_dict={X: [test_x], keep_prob: 1})
ImageDataGenerator.predict(output)
