Question

使用以下代码在cmd中使用代码时出现错误：

python generate_tfrecord.py --csv_input=images\train_labels.csv --image_dir=images\train --output_path=train.record""
Usage:
  # From tensorflow/models/
  # Create train data:
  python generate_tfrecord.py --csv_input=data/train_labels.csv  --output_path=train.record

  # Create test data:
  python generate_tfrecord.py --csv_input=data/test_labels.csv  --output_path=test.record
"""
from __future__ import division
from __future__ import print_function
from __future__ import absolute_import

import os
import io
import pandas as pd
import tensorflow as tf
from PIL import Image
from object_detection.utils import dataset_util
from collections import namedtuple, OrderedDict
flags = tf.compat.v1.flags
flags.DEFINE_string('csv_input', '', 'Path to the CSV input')
flags.DEFINE_string('output_path', '', 'Path to output TFRecord')
flags.DEFINE_string('image_dir', '', 'Path to images')
FLAGS = flags.FLAGS
# TO-DO replace this with label map
def class_text_to_int(row_label):
    if row_label == 'put your selected items':
        return 1
    else:
        None
def split(df, group):
    data = namedtuple('data', ['filename', 'object'])
    gb = df.groupby(group)
    return [data(filename, gb.get_group(x)) for filename, x in zip(gb.groups.keys(), gb.groups)]
def create_tf_example(group, path):
   with tf.gfile.GFile(os.path.join(path, '{}'.format(group.filename)), 'rb') as fid:
        encoded_jpg = fid.read()
    encoded_jpg_io = io.BytesIO(encoded_jpg)
    image = Image.open(encoded_jpg_io)
    width, height = image.size
filename = group.filename.encode('utf8')
    image_format = b'jpg'
    xmins = []
    xmaxs = []
    ymins = []
    ymaxs = []
    classes_text = []
    classes = []
for index, row in group.object.iterrows():
        xmins.append(row['xmin'] / width)
        xmaxs.append(row['xmax'] / width)
        ymins.append(row['ymin'] / height)
        ymaxs.append(row['ymax'] / height)
        classes_text.append(row['class'].encode('utf8'))
        classes.append(class_text_to_int(row['class']))
tf_example = tf.train.Example(features=tf.train.Features(feature={
 'image/height': dataset_util.int64_feature(height),
 'image/width': dataset_util.int64_feature(width),
'image/filename': dataset_util.bytes_feature(filename),'image/source_id': dataset_util.bytes_feature(filename),
  'image/encoded': dataset_util.bytes_feature(encoded_jpg),
'image/format': dataset_util.bytes_feature(image_format),
'image/object/bbox/xmin': dataset_util.float_list_feature(xmins)'image/object/bbox/xmax': dataset_util.float_list_feature(xmaxs),
'image/object/bbox/ymin': dataset_util.float_list_feature(ymins),'image/object/bbox/ymax': dataset_util.float_list_feature(ymaxs),
 'image/object/class/text': dataset_util.bytes_list_feature(classes_text),
 'image/object/class/label': dataset_util.int64_list_feature(classes),
}))
return tf_example
def main(_):
writer = tf.python_io.TFRecordWriter(FLAGS.output_path)
path = os.path.join(FLAGS.image_dir)
examples = pd.read_csv(FLAGS.csv_input)
grouped = split(examples, 'filename')
for group in grouped:
tf_example = create_tf_example(group, path)
writer.write(tf_example.SerializeToString())
writer.close()
output_path = os.path.join(os.getcwd(), FLAGS.output_path)
print('Successfully created the TFRecords: {}'.format(output_path))
if __name__ == '__main__':
   tf.app.run()

tf.app.run（）

得到的错误消息是：

回溯（最近一次通话最后一次）：文件“ generate_tfrecord.py”，行   102英寸       tf.app.run（）

AttributeError：模块'tensorflow'没有属性'app'

有人可以帮助我吗？

Answer 1

如果您正在使用TensorFlow v2，则#if !UNITY_EDITOR var filepath = string.Format("{0}/{1}", Application.persistentDataPath, DatabaseName); if (!File.Exists(filepath)) { Utils.Log(LogType.Debug, "Database does not exist"); string DatabaseName = Constants.Settings.dbName; #if UNITY_ANDROID // open StreamingAssets directory and load the db -> var filepath = string.Format("{0}/{1}", Application.persistentDataPath, DatabaseName); var loadDb = new WWW("jar:file://" + Application.dataPath + "!/assets/" + DatabaseName); while (!loadDb.isDone) { } File.WriteAllBytes(filepath, loadDb.bytes); #endif }已移至app.run，如图here所示。

Answer 2

如果您将张量流降级到其他版本，即1.x。

那应该可以正常工作。

通过使用命令pip install tensorflow == 1.7.0来做到这一点

Answer 3

只需尝试将 import tensorflow as tf 替换为 import tensorflow.compat.v1 as tf 就可以了，我遇到了同样的问题。这对我有用。

Answer 4

如果您不想降级，请使用绳索

from absl import app

if __name__ == '__main__':

    app.run(main)

解决：AttributeError：模块“ tensorflow”没有属性“ app”

使用以下代码在cmd中使用代码时出现错误：

tf.app.run（）

4 个答案: