我试图得到tfrecord文件使用以下代码,我打印多个部分的代码试图得到的问题,但;然而,我总是得到相同的消息“absl.flags._exceptions.UnrecognizedFlagError:未知的命令行标志“mode”。
为什么没有印国旗
谢谢你的帮助
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
from numpy import split
csv_input = "C:\\Users\\Documents\\Research\\ShortCut\\Model_B\\PTrain_labels.csv"
output_path = "C:\\Users\\Documents\\OutPutPath\\Output.tfrecord"
image_dir = "C:\\Users\\Documents\\Research\\ShortCut\\Model_B\\Base"
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
print("csv_input flag:", FLAGS.csv_input)
print("output_path flag:", FLAGS.output_path)
print("image_dir flag:", FLAGS.image_dir)
def class_text_to_int(row_label):
if row_label == "M":
return 1
elif row_label == "J":
return 2
else:
return 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.io.gfile.GFile(os.path.join(path, 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 _, 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(_):
# Print the values of csv_input, output_path, and image_dir
print("csv_input:", csv_input)
print("output_path:", output_path)
print("image_dir:", image_dir)
print("csv_input:", FLAGS.csv_input)
print("output_path:", FLAGS.output_path)
print("image_dir:", FLAGS.image_dir)
writer = tf.io.TFRecordWriter(FLAGS.output_path)
path = 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())
print("Writing TFRecord to:", FLAGS.output_path)
writer.close()
print('Successfully created the TFRecords: {}'.format(FLAGS.output_path))
print('Successfully created the TFRecords: {}'.format(FLAGS.output_path))
if __name__ == '__main__':
try:
tf.compat.v1.app.run()
except Exception as e:
# Print any error messages that occur during script execution
print("An error occurred:", str(e))
1条答案
按热度按时间jdgnovmf1#
给予这个试试。我把你不需要的东西都删掉了。
您有
from numpy import split
,但随后提供了自己的split
副本。有一堆__future__
的东西你不需要。您不需要命令行参数,因为您正在对文件和目录进行硬编码。我实际上已经检查了这里的处理过程,当然我没有你的数据,但是看看这是否能让你通过第一个障碍。