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@DanWahlin
Last active May 3, 2018 20:19
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Machine Learning Image Classifier Python Script
# Originally created by Lin JungHsuan: https://medium.com/@linjunghsuan/create-a-simple-image-classifier-using-tensorflow-a7061635984a
import tensorflow as tf, sys
image_path = sys.argv[1]
# Read in the image_data
image_data = tf.gfile.FastGFile(image_path, 'rb').read()
# Loads label file, strips off carriage return
label_lines = [line.rstrip() for line
in tf.gfile.GFile('./tf_files/retrained_labels.txt')]
# Unpersists graph from file
with tf.gfile.FastGFile('./tf_files/retrained_graph.pb', 'rb') as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
_ = tf.import_graph_def(graph_def, name='')
# Feed the image_data as input to the graph and get first prediction
with tf.Session() as sess:
softmax_tensor = sess.graph.get_tensor_by_name('final_result:0')
predictions = sess.run(softmax_tensor, {'DecodeJpeg/contents:0': image_data})
# Sort to show labels of first prediction in order of confidence
top_k = predictions[0].argsort()[-len(predictions[0]):][::-1]
for node_id in top_k:
human_string = label_lines[node_id]
score = predictions[0][node_id]
print('%s (score = %.5f)' % (human_string, score))
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