CaliTree weights

These are the trained weights for CaliTree, a solution to the ATM'26 (MICCAI 2026) airway tree modelling challenge.

Code: adinathdukre/CaliTree

folder	model	use
track1/nnUNet_ckpts	nnU-Net ResEnc-M, nnUNetTrainerAirwayCB_clprec025, 5 folds	Track 1 binary airway segmentation
track2/nnUNet_ckpts	nnU-Net ResEnc-M, nnUNetTrainerAirwayCB, 5 folds	Track 2 stage 1 airway mask
track2/nnUNet_t2warm	nnU-Net 3d_fullres_SAS, nnUNetTrainerT2Warm, 5 folds	Track 2 stage 2 21-class voxel labelling

Each track folder is used directly as ATM_RESOURCES:

huggingface-cli download adidukre/CaliTree --local-dir /path/to/weights
ATM_RESOURCES=/path/to/weights/track1 ATM_INPUT=/path/to/ct_folder ATM_OUTPUT=/path/to/output \
    python docker/T1/inference.py