license: apache-2.0
library_name: libreyolo
tags:
- super-resolution
- image-to-image
- swinir
pipeline_tag: image-to-image
LibreSwinIRl-restore
SwinIR-L x4 real-world super-resolution (large GAN generator), repackaged for LibreYOLO.
Source
Weights derived from JingyunLiang/SwinIR
release 003_realSR_BSRGAN_DFOWMFC_s64w8_SwinIR-L_x4_GAN.pth
(SHA-256 99adfa91350a84c99e946c1eb3d8fce34bc28f57d807b09dc8fe40a316328c0a).
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 373e2397ab8c8fc71308808683da025e98c5f845ea7588e3f65009a516ed985e).
Usage
from libreyolo import LibreYOLO
model = LibreYOLO("LibreSwinIRl-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.