Question

以下是Tensorflow For Poets教程提供的代码，该教程有助于使用重新训练的Inception模型对图像进行分类

import tensorflow as tf, sys

# change this as you see fit
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='')

with tf.Session() as sess:
    # Feed the image_data as input to the graph and 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 = %.5f)' % (human_string, score))

我不是一次只对一个图像进行分类，而是要对多个图像进行分类。我知道这可以通过将每个图像的数据放在代码的sess.run(softmax_tensor,{'DecodeJpeg/contents:0': image_data})部分中来为每个图像运行此过程来完成，但我希望同时执行此操作并且并行。

是否有一些由tensorflow提供的东西，或者可能是Python的多处理库，它可以让我使用我的多核并同时对我的图像进行分类（比如一次可能只有4-8个）？

如何与Inception并行分类多个图像？

0 个答案: