WireCell/dnn-roi

DNN ROI Models

A collection of deep neural network models for region of interest (ROI) detection in LArTPC experiments, including ICARUS, ProtoDUNE-HD, ProtoDUNE-SP, and SBND.

├── icarus
│   └── moon-2025-08-25
│       ├── plane0_rand.ts
│       └── plane1_rand.ts
├── pdhd
│   ├── dikshant
│   │   ├── mobileunet_largedataset_fullimage.ts
│   │   ├── mobileunet_largedataset_rebin4.ts
│   │   ├── unet_largedataset_fullimage.ts
│   │   └── unet_largedataset_rebin4.ts
│   └── hokyeong
│       └── CP49_mobilenetv3.ts
├── pdsp
│   ├── pth-model # models in pytorch pickle format
│   │   ├── nestedunet-l23-cosmic500-e50.pth # input: loose, MP2, MP3
│   │   ├── unet-l23-cosmic500-e50.pth # input: loose, MP2, MP3
│   │   └── unet-lt-cosmic500-e50.pth # input: loose, tight
│   ├── ts-model-1.3 # TorchScript model saved using PyTorch 1.3
│   │   ├── nestedunet-l23-cosmic500-e50.ts
│   │   ├── unet-l23-cosmic500-e50.ts
│   │   └── unet-lt-cosmic500-e50.ts
│   └── ts-model-2.3 # TorchScript model saved using PyTorch 2.3
│       ├── nestedunet-l23-cosmic500-e50.ts
│       ├── unet-l23-cosmic500-e50.ts
│       └── unet-lt-cosmic500-e50.ts
├── README.md
└── sbnd
    └── sbnd_data-v01_34_00
        ├── plane0.ts
        └── plane1.ts