license: mit
library_name: libreyolo
tags:
- denoising
- image-to-image
- nafnet
pipeline_tag: image-to-image
LibreNAFNetl-restore-sidd
NAFNet SIDD real-image denoising weights (width-64), repackaged for LibreYOLO.
This gives the LibreYOLO denoise restore alias a real model.
Source
Weights derived from megvii-research/NAFNet
(NAFNet-SIDD-width64). Copyright (c) 2022 megvii-model. MIT (code) +
Apache-2.0 (BasicSR utilities). Trained on the Smartphone Image Denoising
Dataset (SIDD), which is MIT-licensed.
Modifications
State-dict metadata-wrap only: keys and learned parameters are unchanged; the
checkpoint is wrapped in the LibreYOLO v1.0 schema (task=restore,
degradation=denoise, dataset=SIDD). Conversion is bit-exact vs the upstream
model (max_abs_diff == 0, fp32), so the upstream reported SIDD sRGB validation
figure (PSNR 40.3045 dB, SSIM 0.9614) applies. See
weights/convert_nafnet_weights.py in the
LibreYOLO source repository.
Usage
from libreyolo import LibreYOLO
model = LibreYOLO("LibreNAFNetl-restore-sidd.pt")
res = model.predict("noisy.jpg")
res[0].save("denoised.png")
License
MIT (with Apache-2.0 BasicSR utilities). See the LICENSE and
NOTICE files in this repository.