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LibreSwinIRs-restore
LibreYOLO/LibreSwinIRs-restore
LibreSwinIRs-restore is a image-to-image model from LibreYOLO. Use it when you need one image transformed into another. It is set up for libreyolo. The card lists the license as apache-2.0.
SwinIR-S x4 lightweight super-resolution (DIV2K), repackaged for LibreYOLO.
Access
Public
Updated Jul 11, 2026
Repo size
17.2 MB
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Repo makeup
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.pt17.2 MB · 100%
At a glance
- Task
- Image-to-Image
- Library
- libreyolo
- License
- apache-2.0
- Access
- Public
- Created
- Jul 11, 2026
- Updated
- Jul 11, 2026
- SHA
- 12c109e5
Model card
From the Hugging Face model README
LibreSwinIRs-restore
SwinIR-S x4 lightweight super-resolution (DIV2K), repackaged for LibreYOLO.
Source
Weights derived from JingyunLiang/SwinIR
release 002_lightweightSR_DIV2K_s64w8_SwinIR-S_x4.pth
(SHA-256 09fad24e32ae62722e1a055efde9921328f4137981bab0a42a4a3a806306c58e).
Copyright (c) 2021 Jingyun Liang. Licensed under the Apache License, Version 2.0.
Architecture reference commit: 6545850fbf8df298df73d81f3e8cba638787c8bd.
Modifications
State-dict metadata-wrap only: keys and learned parameters are unchanged; the
checkpoint is wrapped in the LibreYOLO v1.0 schema (task=restore, scale=4).
Tensor-level parity vs the official model is exact (max_abs_diff == 0, fp32).
Converted with weights/convert_swinir_weights.py from the
LibreYOLO source repository
(converted-file SHA-256 762b804abc7b2d49739fc05c8c10ce434fccbb4a0dff26a958b17e8ac5bf2601).
Usage
from libreyolo import LibreYOLO
model = LibreYOLO("LibreSwinIRs-restore.pt")
res = model.predict("small.jpg") # res.restored is 4x the input
res.save("upscaled.png")
# large images: model.predict("big.jpg", tile=256) # halo-padded tiling
License
Apache-2.0 (code and weights). See the LICENSE and
NOTICE files in this repository.
- Task
- Image-to-Image
- Library
- libreyolo
- License
- apache-2.0
- Created
- Jul 11, 2026
- Updated
- Jul 11, 2026