Lightweight public repository for GiLDM, organized into two parts:
- Method code:
gildm/,scripts/,configs/,preprocessing/ - Result processing:
evaluation/(scripts only, no large experiment snapshots)
gildm/: core model, training, and sampling codescripts/train_gildm.py: unified training entry (stage1,stage2, orall)configs/: selected v6 and ablation configspreprocessing/: dataset preprocessing utilitiesevaluation/: evaluation and plotting scriptsdata/sample_TIs/: small sample training images
- Install dependencies
pip install -r requirements.txt- Prepare data
- Sample files are provided in
data/sample_TIs/. - Full datasets (
.npy) should be placed indataset/.
- Train
python scripts/train_gildm.py --config configs/ldm_v6_channel.yaml --stage allResume stage 2 only:
python scripts/train_gildm.py --config configs/ldm_v6_channel.yaml --stage stage2 --resume- Evaluate
python evaluation/evaluate_full.py --config configs/ldm_v6_channel.yaml --ckpt stage2-10.ckpt --out-dir evaluation/full_eval_channel_v6
python evaluation/evaluate_full_delta.py --config configs/ldm_v6_delta.yaml --ckpt stage2-10.ckpt --out-dir evaluation/full_eval_delta_v6Large datasets and checkpoints are distributed externally via Zenodo.
- Code DOI (GitHub release archive): https://doi.org/10.5281/zenodo.19141791
- Assets record (datasets + checkpoints): https://zenodo.org/records/19142031
- Assets DOI: https://doi.org/10.5281/zenodo.19142031
Released files in the assets record:
gildm_checkpoints_v1.0.0.tar.gzgildm_datasets_v1.0.0.tar.gzSHA256SUMS.txt
gildm_checkpoints_v1.0.0.tar.gz:dfc90983963e0fa842dcc27ba9f50bcf2fe1549c2a4640e8d52468803fbc84aegildm_datasets_v1.0.0.tar.gz:b3fcb29e6f5e6bc9143358f6bbb42949835a1a1c05a3a3f990afab4849518390
Verify and extract:
shasum -a 256 -c SHA256SUMS.txt
tar -xzf gildm_checkpoints_v1.0.0.tar.gz -C .
tar -xzf gildm_datasets_v1.0.0.tar.gz -C .- The codebase uses the
gildmnamespace. .gitignoreexcludes large artifacts such as*.ckpt,*.npy,wandb/, and*.raylink.downloading.