Initial upload: Real-ESRGAN x2plus (RRDBNet) super-resolution

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LICENSE

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+BSD 3-Clause License
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LibreRealESRGANx2-restore.pt

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+oid sha256:17a33ef8ee0464515984c716b42c210b4eee1954c5bc27e2e8afeb3cdf780028
+size 67060043

NOTICE

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+LibreRealESRGANx2-restore weights
+---------------------------------
+
+This product contains weights derived from Real-ESRGAN
+(https://github.com/xinntao/Real-ESRGAN).
+Copyright (c) 2021 Xintao Wang. Licensed under the BSD 3-Clause License.
+
+The RRDBNet architecture lineage is BasicSR
+(https://github.com/XPixelGroup/BasicSR).
+Copyright 2018-2022 BasicSR Authors. Licensed under the Apache License, Version 2.0.
+
+Released Real-ESRGAN generator weights are distributed under the BSD 3-Clause
+License; this repository mirrors a converted checkpoint with unchanged learned
+parameters (state-dict metadata-wrap only).

README.md

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+---
+license: bsd-3-clause
+library_name: libreyolo
+tags:
+  - super-resolution
+  - image-to-image
+  - real-esrgan
+pipeline_tag: image-to-image
+---
+
+# LibreRealESRGANx2-restore
+
+RRDBNet Real-ESRGAN super-resolution (2x upscaling), repackaged for LibreYOLO.
+
+## Source
+
+Weights derived from [xinntao/Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN)
+release `RealESRGAN_x2plus.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=2`).
+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("LibreRealESRGANx2-restore.pt")
+res = model.predict("small.jpg")     # res[0].restored is 2x 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.