Skip to main content


YOLOX is an anchor-free version of YOLO with strong performance for object detection. YOLOX contains a Weights & Biases integration that enables you to turn on logging of training, validation and system metrics, as well as interactive validation predictions with just 1 command line argument.

Getting Startedโ€‹

To use YOLOX with Weights & Biases you will first need to sign up for a Weights & Biases account here.

Then just 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 would expect, just prepend wandb- to the start of each argument

Note: num_eval_imges controls the number of validation set images and predictions that will be logged to Weights & Biases Tables for model evaluation.

# login to wandb
wandb login

# call your yolox training script with the `wandb` logger argument
python tools/ .... --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 dashboard with YOLOX training and validation metrics ->

Any questions or issues about this Weights & Biases integration? Open an issue in the YOLOX github repository and we'll catch it and get you an answer :)

Was this page helpful?๐Ÿ‘๐Ÿ‘Ž