无baz的张量流初始

Question

我尝试了tensorflow网站上的图像识别教程： https://www.tensorflow.org/tutorials/image_retraining 它成功地与bazelbu命令行一起工作 是否可以使用bazel或python脚本以编程方式调用此inception模型，以便我可以轻松地向它提供图像

Answer 1

您可以使用tmp目录下生成的文件并编写python脚本来加载模型并生成预测。在

另外，建议将文件保存在tmp文件夹以外的目录中，因为文件夹的内容可能会被清除。在

import tensorflow as tf
import sys


image_path = sys.argv[1]
image_data = tf.gfile.FastGFile(image_path, 'rb').read()

#loads label file, strips off carriage return
label_lines = [line.strip() for line in tf.gfile.GFile("/tmp/output_labels.txt")]

# Unpersists graph from file
with tf.gfile.FastGFile("/tmp/output_graph.pb", 'rb') as f:
    graph_def = tf.GraphDef()
    graph_def.ParseFromString(f.read())
    _ = tf.import_graph_def(graph_def, name='')

with tf.Session() as sess:
    # Feed the image data as input to the graph an get first prediction
    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 = %.2f)' % (human_string, score))