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PaddleOCR aims to create multilingual, awesome, leading, and practical OCR tools that help users train better models and apply them into practice implemented in PaddlePaddle. PaddleOCR support a variety of cutting-edge algorithms related to OCR, and developed industrial solution. PaddleOCR now comes with a W&B integration for logging training and evaluation metrics along with model checkpoints with corresponding metadata.

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Example Blog & Colab

Read here to see how to train a model with PaddleOCR on the ICDAR2015 dataset. This also comes with a Google Colab and the corresponding live W&B dashboard is available here. There is also a Chinese version of this blog here: W&B对您的OCR模型进行训练和调试

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Sign up and create an API key

An API key authenticates your machine to W&B. You can generate an API key from your user profile.
For a more streamlined approach, create an API key by going directly to User Settings. Copy the newly created API key immediately and save it in a secure location such as a password manager.
  1. Click your user profile icon in the upper right corner.
  2. Select User Settings, then scroll to the API Keys section.

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Install the wandb library and log in

To install the wandb library locally and log in:
  1. Set the WANDB_API_KEY environment variable to your API key. 
    export WANDB_API_KEY=<your_api_key>
  2. Install the wandb library and log in. 
    pip install wandb

wandb login

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Add wandb to your config.yml file

PaddleOCR requires configuration variables to be provided using a yaml file. Adding the following snippet at the end of the configuration yaml file will automatically log all training and validation metrics to a W&B dashboard along with model checkpoints: 
Global:
    use_wandb: True
Any additional, optional arguments that you might like to pass to wandb.init() can also be added under the wandb header in the yaml file: 
wandb:  
    project: CoolOCR  # (optional) this is the wandb project name 
    entity: my_team   # (optional) if you're using a wandb team, you can pass the team name here
    name: MyOCRModel  # (optional) this is the name of the wandb run

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Pass the config.yml file to train.py

The yaml file is then provided as an argument to the training script available in the PaddleOCR repository. 
python tools/train.py -c config.yml
Once you run your train.py file with W&B turned on, a link will be generated to bring you to your W&B dashboard:
PaddleOCR training dashboard
PaddleOCR validation dashboard
Text Detection Model dashboard

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Feedback or issues

If you have any feedback or issues about the W&B integration, open an issue on the PaddleOCR GitHub or email [email protected].