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我正在尝试使用.recordcoco 格式 ( .json) 创建 tfrecord () 文件。因此，我正在使用对象检测 api github 存储库中脚本的这个稍微修改过的版本。 我在 colab 上运行我的笔记本。这些是几行代码：create_coco_tf_record.py

#Mount Google Drive.
from google.colab import drive
drive.mount('/content/gdrive') <br>

!pip install -U --pre tensorflow=="2.2.0"

#Download TensorFlow Model Garden.
import os
import pathlib
#cd into the TensorFlow directory in your Google Drive
%cd '/content/gdrive/My Drive/TensorFlow'
# Clone the tensorflow models repository if it doesn't already exist
if "models" in pathlib.Path.cwd().parts:
  while "models" in pathlib.Path.cwd().parts:
    os.chdir('..')
elif not pathlib.Path('models').exists():
  !git clone --depth 1 https://github.com/tensorflow/models

# Install the Object Detection API
%%bash
cd '/content/gdrive/My Drive/TensorFlow/models/research/'
protoc object_detection/protos/*.proto --python_out=.
cp object_detection/packages/tf2/setup.py .
python -m pip install .

#run model builder test
!python '/content/gdrive/My Drive/TensorFlow/models/research/object_detection/builders/model_builder_tf2_test.py'

!wget https://raw.githubusercontent.com/TannerGilbert/Tensorflow-Object-Detection-API-train-custom-Mask-R-CNN-model/master/create_coco_tf_record.py

# create tf record
!python create_coco_tf_record.py \
  --logtostderr \
  --train_image_dir='/content/gdrive/My Drive/TensorFlow/workspace/training_demo/images/combined/' \
  --test_image_dir='/content/gdrive/My Drive/TensorFlow/workspace/training_demo/images/combined/' \
  --train_annotations_file='/content/gdrive/My Drive/TensorFlow/workspace/training_demo/images/train_coco.json' \
  --test_annotations_file='/content/gdrive/My Drive/TensorFlow/workspace/training_demo/images/test_coco.json' \
  --output='/content/gdrive/My Drive/TensorFlow/workspace/training_demo/annotations/'

create_coco_tf_record.py脚本运行没有任何错误。这就是它所显示的：

2020-10-28 08:58:44.931401: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
INFO:tensorflow:Found groundtruth annotations. Building annotations index.
I1028 08:58:46.678869 139783613331328 create_coco_tf_record.py:214] Found groundtruth annotations. Building annotations index.
INFO:tensorflow:0 images are missing annotations.
I1028 08:58:46.679595 139783613331328 create_coco_tf_record.py:227] 0 images are missing annotations.
INFO:tensorflow:On image 0 of 451
I1028 08:58:46.680609 139783613331328 create_coco_tf_record.py:232] On image 0 of 451
INFO:tensorflow:On image 100 of 451
I1028 08:58:51.800869 139783613331328 create_coco_tf_record.py:232] On image 100 of 451
INFO:tensorflow:On image 200 of 451
I1028 08:59:01.762672 139783613331328 create_coco_tf_record.py:232] On image 200 of 451
INFO:tensorflow:On image 300 of 451
I1028 08:59:22.197772 139783613331328 create_coco_tf_record.py:232] On image 300 of 451
INFO:tensorflow:On image 400 of 451
I1028 09:00:17.036898 139783613331328 create_coco_tf_record.py:232] On image 400 of 451
INFO:tensorflow:Finished writing, skipped 0 annotations.
I1028 09:00:32.919734 139783613331328 create_coco_tf_record.py:239] Finished writing, skipped 0 annotations.
INFO:tensorflow:Found groundtruth annotations. Building annotations index.
I1028 09:00:32.932144 139783613331328 create_coco_tf_record.py:214] Found groundtruth annotations. Building annotations index.
INFO:tensorflow:0 images are missing annotations.
I1028 09:00:32.932511 139783613331328 create_coco_tf_record.py:227] 0 images are missing annotations.
INFO:tensorflow:On image 0 of 152
I1028 09:00:32.932658 139783613331328 create_coco_tf_record.py:232] On image 0 of 152
INFO:tensorflow:On image 100 of 152
I1028 09:00:46.510094 139783613331328 create_coco_tf_record.py:232] On image 100 of 152
INFO:tensorflow:Finished writing, skipped 0 annotations.
I1028 09:01:08.650619 139783613331328 create_coco_tf_record.py:239] Finished writing, skipped 0 annotations.

不知何故，它不会创建任何.record文件。

有谁知道这里可能出现什么问题？

提前致谢！

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1 回答 1

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您可以运行此命令在 Windows 机器上的 VS 代码终端中生成您的 .record 文件。“Imp。-不要使用'逗号'来包含您的路径，因为我已经提到只是复制/粘贴路径，就像我在评论中建议的那样”-

python create_coco_tf_record.py 
  --train_image_dir 'Path where you have your training dataset' 
  --test_image_dir 'Path where you have your validation dataset' 
  --train_annotations_file 'Path to your training dataset .json file' 
  --test__annotations_file 'Path to your validation dataset .json file' 
  --logtostderr --output_dir 'Path where do you want to generate your .record file'

还要记住并运行具有运行此代码所需的特定环境要求的代码。

于 2021-10-27T03:05:43.447 回答