Before Start
This document provides a concise workflow to run AuralSAM2 experiments.
βοΈ Prepare environment and data
Please complete all setup steps in installation first.
π Training
Use the unified launcher script:
cd scripts
./run_avs_train.sh <v1s|v1m|v2> [gpus]
./run_ref_train.sh [gpus]
The experiments are implemented by 4 GPUs by default.
π Inference (example)
cd avs.code/v2.code
python inference.py --gpus 1 --batch_size 1 --inference_ckpt /absolute/path/to/checkpoint.pth
π Training Logs (Reproducibility)
Some examples of training details, please see this wandb link.
In details, after clicking the run (e.g., v1m-hiera-l), you can checkout:
overall information (e.g., command line, hardware information and training time).
training curves and validation visualisation.
output logs.
πΎ Checkpoints
We release both checkpoints and training logs in this Google Drive link.