T2exture Checkpoints

This repository hosts the trained T2exture-S, T2exture-L, and T2exture-G checkpoints for source-conditioned thermal texture propagation.

Files

File Variant Backbone
t2exture-s.pt T2exture-S AMT-S
t2exture-l.pt T2exture-L AMT-L
t2exture-g.pt T2exture-G AMT-G
configs/train.yaml training config five-frame centered passive context

Each checkpoint stores the full T2exture model state for inference. A separate AMT initialization checkpoint is only needed when training from scratch.

Code And Data

Code release:

https://github.com/dccc2025/T2exture

Set the model and dataset repo ids locally:

export T2EXTURE_MODEL_REPO=<hf-model-repo-id>
export T2EXTURE_DATASET_REPO=<hf-dataset-repo-id>

Download the dataset:

python -c "import os; from huggingface_hub import snapshot_download; snapshot_download(repo_id=os.environ['T2EXTURE_DATASET_REPO'], repo_type='dataset', local_dir='datasets')"

Synthetic Inference

python -B infer.py   --mode synthetic   --variant l   --data-root datasets   --split test   --output-dir outputs/infer/synthetic-l

infer.py downloads t2exture-<variant>.pt from T2EXTURE_MODEL_REPO when --checkpoint is not provided.

Real Inference

For real sequences, provide either residual texture anchors or source-on/source-off frames:

real/<sequence>/texture/001.png
real/<sequence>/passive/001.png

real/<sequence>/source_on/001.png
real/<sequence>/source_off/001.png

If source-off frames at active keyframes are missing, generate Stage 1 caches first:

python -B scripts/stage1.py   --mode real   --data-root datasets/real   --real-config configs/real.yaml   --backbone amt-l   --pretrained pretrained/amt-l.pth   --output-dir datasets/real/source_off/amt-l

Then run inference:

python -B infer.py   --mode real   --variant l   --data-root datasets/real   --source-off-root datasets/real/source_off/amt-l   --output-dir outputs/infer/real-l

Notes

The released config uses a five-frame centered passive structural context and active stride 10. Evaluation numbers are intentionally kept with the paper and local experiment artifacts, not duplicated in this model card.

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