Datasets:
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license: cc-by-nc-sa-4.0
task_categories:
- image-to-image
tags:
- face-restoration
- reference-based-restoration
- training-data
- snapcv
pretty_name: RefineFIR TrainingData
---
# RefineFIR TrainingData
This repository contains training artifacts for the RefineFIR reimplementation:
- `celebref_list_256_jw_0403.pkl`: same-identity `(source_id, target_id)` training pairs.
- `celebaref_warped_snapCV_jw_0403.zip`: precomputed Snap/XCV warped reference images for the above pairs.
The clean image root used by `train.py` is expected to be arranged as `CelebHQRefForRelease/<identity>/<image>.png`, where pair ids such as `00001_2` resolve to `CelebHQRefForRelease/00001/2.png`.
The historical training pipeline generated these warped references with Snap/XCV. The public inference code uses MediaPipe, but training can consume the precomputed warped images directly without releasing Snap/XCV code.
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