YOLOX

YOLOX is an anchor-free version of YOLO with strong performance for object detection. You can use the YOLOX Weights & Biases 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.

Get started

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

num_eval_imges controls the number of validation set images and predictions that are 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/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 Weights & Biases integration? Open an issue in the YOLOX repository.