Labeling Images using Inception Getting ValueError: GraphDef cannot be larger than 2GB

Question

我正在使用 TensorFlow for Poets 代码实验室来指导我重新训练 Inceptionv3 CNN 以对图像列表进行分类。我已经成功地训练了这个模型，当我使用给定的代码对单个图像进行分类时它就起作用了。但是当我尝试在大量图像上使用它时，我发现 GraphDef 不能大于 2GB。请指教

import pandas as pd
import os, sys
import tensorflow as tf
test_images = pd.read_csv('test_images.csv')
testid = test_images['Id']
listx= list(range(4320))
predlist=[]
output = pd.DataFrame({'Id': listx})
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
for x in listx:
    path = 'test/'+str(x+1)+'.jpg'

# change this as you see fit
    image_path = path

# 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("retrained_labels.txt")]

# Unpersists graph from file
with tf.gfile.FastGFile("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
    with tf.Graph().as_default():
        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]
    # print('the top result is' + label_lines[node_id])
    flag = 0
    for node_id in top_k:

        while flag == 0:
            human_string = label_lines[node_id]
            score = predictions[0][node_id]
            predlist.append(int(human_string[:3]))
            print('%s' % (human_string))

            flag = 1  # we only want the top prediction

输出['Prediction']=预测表 output.to_csv('outputtest.csv')

Answer 1

解决此错误的一种方法是放置

    with tf.Graph().as_default():

for 循环之后。这是在尝试读取批量图像时对我有用的一段代码：

    for filename in os.listdir(image_path):

       with tf.Graph().as_default():
       # Read in the image_data
       image_data = tf.gfile.FastGFile(image_path + filename, 'rb').read()

Labeling Images using Inception Getting ValueError: GraphDef cannot be larger than 2GB

Labeling Images using Inception Getting ValueError: GraphDef cannot be larger than 2GB

image-processing

labeling

tensorflow