YOLOX

YOLOX is an anchor-free version of YOLO with strong performance for object detection. You can use the YOLOX W&B integration to turn on logging of metrics related to training, validation, and the system, and you can interactively validate predictions with a single command-line argument.

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.

1. Click your user profile icon in the upper right corner.
2. Select User Settings, then scroll to the API Keys section.
3. Click Reveal. Copy the displayed API key. To hide the API key, reload the page.

Install the wandb library and log in

To install the wandb library locally and log in:

• Command Line
• Python
• Python notebook

pip install wandb

import wandb
wandb.login()

!pip install wandb

import wandb
wandb.login()

Log metrics

Use the --logger wandb command line argument to turn on logging with wandb. Optionally you can also pass all of the arguments that wandb.init expects; prepend each argument with wandb-.

num_eval_imges controls the number of validation set images and predictions that are logged to W&B tables for model evaluation.

# login to wandb
wandb login

# call your yolox training script with the `wandb` logger argument
python tools/train.py .... --logger wandb \
                wandb-project <project-name> \
                wandb-entity <entity>
                wandb-name <run-name> \
                wandb-id <run-id> \
                wandb-save_dir <save-dir> \
                wandb-num_eval_imges <num-images> \
                wandb-log_checkpoints <bool>

Example

Example dashboard with YOLOX training and validation metrics ->

Any questions or issues about this W&B integration? Open an issue in the YOLOX repository.