Documentation
Search…
YOLOX
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 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
Note: num_eval_imges controls the number of validation set images and predictions that will be logged to Weights & Biases Tables for model evaluation.
1
# login to wandb
2
wandb login
3
4
# call your yolox training script with the `wandb` logger argument
5
python tools/train.py .... --logger wandb \
6
wandb-project <project-name> \
7
wandb-entity <entity>
8
wandb-name <run-name> \
9
wandb-id <run-id> \
10
wandb-save_dir <save-dir> \
11
wandb-num_eval_imges <num-images> \
12
wandb-log_checkpoints <bool>
Copied!

Example

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 :)
Copy link