生成tfrecords时出现UnicodeDecodeError错误。

我正在尝试使用TensorFlow API生成用于训练目标检测模型的tfrecords和CSV标签，用于检测对象的PNG图像。我正在使用一个教程中的脚本，但是我遇到了以下错误：UnicodeDecodeError: 'utf-8' codec can't decode byte 0xe9 in position 65: invalid continuation byte，我不知道该如何解决。你们有什么想法吗？

以下是生成tfrecords的程序：

"""
用法：
  # 从tensorflow/models/目录下运行：
  # 创建训练数据：
  python preprocessing/csv_to_tfrecords.py --csv_input=data/train_labels.csv  --output_path=data/train.record
  # 创建测试数据：
  python preprocessing/csv_to_tfrecords.py --csv_input=data/test_labels.csv  --output_path=data/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.app.flags
flags.DEFINE_string('csv_input', '', 'CSV输入路径')
flags.DEFINE_string('output_path', '', '输出TFRecord路径')
flags.DEFINE_string('image_dir', '', '图像路径')
FLAGS = flags.FLAGS
# TO-DO：用标签映射替换此部分
def class_text_to_int(row_label):
    if row_label == 'capsule':
        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.io.gfile.GFile(os.path.join(path, '{}'.format(group.filename)), 'rb') as fid:
        encoded_png = fid.read()
    encoded_png_io = io.BytesIO(encoded_png)
    image = Image.open(encoded_png_io)
    width, height = image.size
    filename = group.filename.encode('utf8')
    image_format = b'png'
    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_png),
        '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.compat.v1.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('成功创建TFRecords：{}'.format(output_path))
if __name__ == '__main__':
    tf.compat.v1.app.run()

尝试生成tfrecords后，我得到了以下回溯信息：

python preprocessing/csv_to_tfrecords.py --csv_input=data/train_labels.csv  --output_path=data/train.record
2021-05-31 21:34:20.376813: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2021-05-31 21:34:20.377348: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
Traceback (most recent call last):
  File "preprocessing/csv_to_tfrecords.py", line 100, in 
    tf.compat.v1.app.run()
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\platform\app.py", line 40, in run
    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\absl\app.py", line 303, in run
    _run_main(main, args)
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\absl\app.py", line 251, in _run_main
    sys.exit(main(argv))
  File "preprocessing/csv_to_tfrecords.py", line 91, in main
    tf_example = create_tf_example(group, path)
  File "preprocessing/csv_to_tfrecords.py", line 46, in create_tf_example
    encoded_png = fid.read()
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\lib\io\file_io.py", line 117, in read     
    self._preread_check()
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\tensorflow\python\lib\io\file_io.py", line 80, in _preread_check
    compat.path_to_str(self.__name), 1024 * 512)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xe9 in position 65: invalid continuation byte