tensorflow / tensorflow/models

Object detection API, training part: NewRandomAccessFile failed to Create/Open: training/faster_rcnn_inception_v2_pets.config

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@pkulzc is already working on this.

Since Jun 29, 2020.

models:research:odapi type:bug
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Python
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Description

Prerequisites

Please answer the following questions for yourself before submitting an issue.

  • I am using the latest TensorFlow Model Garden release and TensorFlow 2.
  • I am reporting the issue to the correct repository. (Model Garden official or research directory)
  • I checked to make sure that this issue has not already been filed.

1. The entire URL of the file you are using

https://github.com/tensorflow/models/blob/master/research/object_detection/legacy/train.py

2. Describe the bug

Following the Object Detection API Tutorial @ https://github.com/EdjeElectronics/TensorFlow-Object-Detection-API-Tutorial-Train-Multiple-Objects-Windows-10
When I run the train.py file in C:\tensorflow1\models\research\object_detection\legacy
like this :
python train.py --logtostderr --train_dir=training/ --pipeline_config_path=training/faster_rcnn_inception_v2_pets.config
I get this error:
tensorflow.python.framework.errors_impl.NotFoundError: NewRandomAccessFile failed to Create/Open: training/faster_rcnn_inception_v2_pets.config : The system cannot find the file specified.
; No such file or directory

3. Steps to reproduce

Described in previous section already

4. Expected behavior

Expect the training to initialise and begin.

5. Additional context

Include any logs that would be helpful to diagnose the problem.

6. System information

  • OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows 10
  • Mobile device name if the issue happens on a mobile device:
  • TensorFlow installed from (source or binary): pip install, GPU version of Tensorflow
  • TensorFlow version (use command below):2.1
  • Python version:3.8
  • Bazel version (if compiling from source):
  • GCC/Compiler version (if compiling from source):
  • CUDA/cuDNN version:11.0/8.0.1 RC2
  • GPU model and memory:NVIDIA Geforce RTX 2080/8GB

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  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Assessment

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