Skip to content

erobl/hpst

Repository files navigation

Heterogeneous Point Set Transformers for Segmentation of Multiple View Particle Detectors

This repository contains code to train an HPST, and baselines like GAT and RCNN on NoVa Data for Multiple-view particle detector Segmentation, as seen on Heterogeneous Point Set Transformers for Segmentation of Multiple View Particle Detectors.

Setup

We recommend using conda for environment setup.

git clone https://github.com/erobl/hpst.git
cd hpst
conda create -n hpst python=3.10
conda activate hpst
pip install -r requirements.txt

Logging

We use WandB for logging. Please create a WandB project named "HPST" and use CLI login to use the code as is, or disable logging in the scripts.

Train HPST

python scripts/train.py --options_file "config/hpst/hpst_tune_nova.json" --name "{run_name}" --log_dir "runs" --gpus 4 

Train GAT

python scripts/train_gat.py --options_file "config/gnn/gat_tune_nova.json" --name "{run_name}" --log_dir "runs" --gpus 4

Train RCNN

python scripts/train_rcnn.py --options_file "config/rcnn/rcnn_tune_nova.json" --name "{run_name}" --log_dir "runs" --gpus 8

About

Heterogeneous Point Set Transformers

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published