python - 创建自定义初始时的 tensorflow.python.framework.errors_impl.NotFoundError

Question

我使用以下代码使用 tensorflow 创建自定义初始。

import tensorflow as tf
import sys

interesting_class = sys.argv[1:]
print("Interesting class: ", interesting_class)

# Read in the image_data

from os import listdir
from shutil import copyfile
from os.path import isfile, join
varPath = 'toScan/'
destDir = "scanned/"
imgFiles = [f for f in listdir(varPath) if isfile(join(varPath, f))]


# 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') 
    file_count = len(imgFiles)
    i = 0

    for imageFile in imgFiles:
        print("File ", i, " of ",  file_count)
        i = i+1
        image_data =  tf.gfile.FastGFile(varPath+"/"+imageFile, 'rb').read()       

        print (varPath+"/"+imageFile)
        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]
        firstElt = top_k[0];

        newFileName = label_lines[firstElt] +"--"+ str(predictions[0][firstElt])[2:7]+".jpg"
        print(interesting_class, label_lines[firstElt])
        if interesting_class == label_lines[firstElt]:
            print(newFileName)
            copyfile(varPath+"/"+imageFile, destDir+"/"+newFileName)

        for node_id in top_k:
            human_string = label_lines[node_id]
            score = predictions[0][node_id]
            print (node_id)
            print('%s (score = %.5f)' % (human_string, score))

执行时出现以下错误

('Interesting class: ', []) Traceback (most recent call last): File "/Users/Downloads/imagenet_train-master/label_dir.py", line 22, in in tf.gfile.GFile("/tf_files/retrained_labels.txt")] File "/Users/tensorflow/lib/python2.7/site-packages/tensorflow/python/lib/io/file_io.py", line 156, in next retval = self.readline() File "/Users/tensorflow/lib/python2.7/site-packages/tensorflow/python/lib/io/file_io.py", line 123, in readline self._preread_check() File "/Users/tensorflow/lib/python2.7/site-packages/tensorflow/python/lib/io/file_io.py", line 73, in _preread_check compat.as_bytes(self.name), 1024 * 512, status) File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/contextlib.py", line 24, in __exit self.gen.next() File "/Users/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status pywrap_tensorflow.TF_GetCode(status)) tensorflow.python.framework.errors_impl.NotFoundError: /tf_files/retrained_labels.txt

为什么会出现此错误？

以下是我的文件夹结构:

tensorflow_try
|- new_pics
|  |- class1
|  |- class2
|  |- ...
|- toScan
|- scanned

Answer 1

问题出在这一行:

label_lines = [line.rstrip() for line 
                   in tf.gfile.GFile("/tf_files/retrained_labels.txt")]

请检查:

1. 文件系统根目录中存在文件夹 tf_files -- 您可以运行 ls/tf_files 来检查它；
2. (如果第 1 项没问题)如果您对 /tf_files/retrained_labels.txt 有读/写权限。