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Logging metrics and models

PaddleOCR comes with two metric logging tools integrated directly into the training API: VisualDL and Weights & Biases.

VisualDL

VisualDL is a visualization analysis tool of PaddlePaddle. The integration allows all training metrics to be logged to a VisualDL dashboard. To use it, add the following line to the Global section of the config yaml file -

Global:
    use_visualdl: True

To see the visualizations run the following command in your terminal

visualdl --logdir <save_model_dir>

Now open localhost:8040 in your browser of choice!

Weights & Biases

W&B is a MLOps tool that can be used for experiment tracking, dataset/model versioning, visualizing results and collaborating with colleagues. A W&B logger is integrated directly into PaddleOCR and to use it, first you need to install the wandb sdk and login to your wandb account.

pip install wandb
wandb login

If you do not have a wandb account, you can make one here.

To visualize and track your model training add the following flag to your config yaml file under the Global section -

Global:
    use_wandb: True

To add more arguments to the WandbLogger listed here add the header wandb to the yaml file and add the arguments under it -

wandb:
    project: my_project
    entity: my_team

These config variables from the yaml file are used to instantiate the WandbLogger object with the project name, entity name (the logged in user by default), directory to store metadata (./wandb by default) and more. During the training process, the log_metrics function is called to log training and evaluation metrics at the training and evaluation steps respectively from the rank 0 process only.

At every model saving step, the WandbLogger, logs the model using the log_model function along with relavant metadata and tags showing the epoch in which the model is saved, the model is best or not and so on.

All the logging mentioned above is integrated into the program.train function and will generate dashboards like this -

W&B Dashboard

W&B Models

For more advanced usage to log images, audios, videos or any other form of data, you can use WandbLogger().run.log. More examples on how to log different kinds of data are available here.

To view the dashboard, the link to the dashboard is printed to the console at the beginning and end of every training job and you can also access it by logging into your W&B account on your browser.

Using Multiple Loggers

Both VisualDL and W&B can also be used simultaneously by just setting both the aforementioned flags to True.