LibreRealESRGANx4 Restore
RRDBNet Real-ESRGAN super-resolution (4x upscaling), repackaged for LibreYOLO.
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 63,9 MB
- Versión
- vLibre Real ESRGANx4 restore
- Actualizado
- 9 oct 2026
- Fuente
- Hugging Face
Descripción de la fuente
LibreRealESRGANx4-restore
RRDBNet Real-ESRGAN super-resolution (4x upscaling), repackaged for LibreYOLO.
Source
Weights derived from xinntao/Real-ESRGAN
release RealESRGAN_x4plus.pth.
Copyright (c) 2021 Xintao Wang. Licensed under the BSD 3-Clause License.
The RRDBNet architecture lineage is XPixelGroup/BasicSR (Apache-2.0, Copyright 2018-2022 BasicSR Authors).
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).
See weights/convert_realesrgan_weights.py in the
LibreYOLO source repository.
Usage
from libreyolo import LibreYOLO
model = LibreYOLO("LibreRealESRGANx4-restore.pt")
res = model.predict("small.jpg") # res[0].restored is 4x the input
res[0].save("upscaled.png")
# large images: model.predict("big.jpg", tile=512) # seam-free tiling
License
BSD 3-Clause (weights) with Apache-2.0 architecture lineage. See the
LICENSE and NOTICE files in this repository.
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 9 oct
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
2 extractos
Extractos de fuentes
2 extractos--- license: bsd-3-clause library_name: libreyolo tags: - super-resolution - image-to-image - real-esrgan pipeline_tag: image-to-image --- # LibreRealESRGANx4-restore RRDBNet Real-ESRGAN super-resolution (4x upscaling), repackaged for LibreYOLO. ## Source Weights derived from [xinntao/Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN) release `RealESRGAN_x4plus.pth`. Copyright (c) 2021 Xintao Wang. Licensed under the BSD 3-Clause License. The RRDBNet architecture lineage is [XPixelGroup/BasicSR](https://github.com/XPixelGroup/BasicSR) (Apache-2.0, Copyright 2018-2022 BasicSR Authors). ## 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). See `weights/convert_realesrgan_weights.py` in the [LibreYOLO source repository](https://github.com/LibreYOLO/libreyolo). ## Usage ```python from libreyolo import LibreYOLO model = LibreYOLO("LibreRealESRGANx4-restore.pt") res = model.predict("small.jpg") # res[0].restored is 4x the input res[0].save("upscaled.png") # large images: model.predict("big.jpg", tile=512) # seam-free tiling ``` ## License BSD 3-Clause (weights) with Apache-2.0 architecture lineage. See the [`LICENSE`](./LICENSE) and [`NOTICE`](./NOTICE) files in this repository.
Source context: 0 downloads · 0 likes · Pipeline image-to-image · Library libreyolo · Repo LibreYOLO/LibreRealESRGANx4-restore
