Machine-learning models used by Numa
====================================

These files are mirrored here so Numa's downloads keep working. They are not
Numa's work and are not covered by Numa's licence. Each is redistributed under
its own licence, reproduced below.

efficientvit_seg_b2_ade20k_1024.onnx
  EfficientViT-Seg-B2 trained on ADE20K. Han Cai et al., MIT Han Lab.
  https://github.com/mit-han-lab/efficientvit
  Exported to ONNX by Numa's dev/export-efficientvit.sh.
  Licence: Apache License 2.0

sam_encoder.onnx, sam_decoder.onnx
  SlimSAM-77 (uniform), Zigeng Chen et al., a pruned Segment Anything (Meta AI).
  https://github.com/czg1225/SlimSAM
  ONNX export by Xenova: https://huggingface.co/Xenova/slimsam-77-uniform
  (published there as vision_encoder.onnx and prompt_encoder_mask_decoder.onnx)
  Licence: Apache License 2.0 (SlimSAM and Segment Anything)

isnet.onnx  (Linux only; never used by the paid Apple app)
  IS-Net (DIS, "Highly Accurate Dichotomous Image Segmentation"), Xuebin Qin et al.
  https://github.com/xuebinqin/DIS
  ONNX export from rembg by Daniel Gatis: https://github.com/danielgatis/rembg
  (published there as isnet-general-use.onnx)
  Licence: Apache License 2.0 (the model); rembg's export under the MIT Licence below
  Its training set, DIS5K, is licensed for non-commercial use only.

face_detection_yunet_2023mar.onnx
  YuNet, Wei Wu, Yuantao Feng, Shiqi Yu. OpenCV Zoo.
  https://github.com/opencv/opencv_zoo/tree/main/models/face_detection_yunet
  Licence: MIT Licence, below

face_recognition_sface_2021dec.onnx
  SFace, Yaoyao Zhong, Weihong Deng et al. OpenCV Zoo.
  https://github.com/opencv/opencv_zoo/tree/main/models/face_recognition_sface
  Licence: Apache License 2.0
  Its training data, face datasets, is licensed for research use only, so
  Numa offers SFace for non-commercial use only (Linux only; not in the paid
  Apple app).

image_classification_ppresnet50_2022jan.onnx
  PP-ResNet50 on ImageNet-1k, PaddlePaddle / PaddleClas. OpenCV Zoo.
  https://github.com/opencv/opencv_zoo/tree/main/models/image_classification_ppresnet
  Licence: Apache License 2.0

scunet_color_real_psnr_fp16.onnx
  SCUNet (real-world, PSNR), Kai Zhang et al., "Practical Blind Image Denoising
  via Swin-Conv-UNet and Data Synthesis". https://github.com/cszn/SCUNet
  From the ONNX export at https://huggingface.co/Heliosoph/scunet-onnx (Apache-2.0),
  modified: its weights and arithmetic converted to float16, input and output
  kept float32, by Numa's dev/export-scunet-fp16.sh.
  Licence: Apache License 2.0


restormer_motion_deblurring.onnx
  Restormer, motion-deblurring checkpoint. Syed Waqas Zamir et al.,
  "Restormer: Efficient Transformer for High-Resolution Image Restoration".
  https://github.com/swz30/Restormer
  Exported to ONNX from the published PyTorch weights by Numa's
  dev/export-restormer.sh.
  Licence: MIT Licence, below

birefnet_lite_512.onnx
  BiRefNet lite (swin_v1_tiny backbone), Peng Zheng et al.
  https://github.com/ZhengPeng7/BiRefNet  weights: https://huggingface.co/ZhengPeng7/BiRefNet_lite
  Exported to ONNX at a 512 x 512 input by Numa (for the iPhone and iPad), from
  the official code and weights; Numa rewrites it for its runtime after download.
  Licence: MIT Licence, below

birefnet_lite_matting.onnx, birefnet_lite_matting_512.onnx
  BiRefNet lite for general matting (swin_v1_tiny backbone), Peng Zheng et al.
  https://github.com/ZhengPeng7/BiRefNet  weights: https://huggingface.co/ZhengPeng7/BiRefNet_lite-matting
  Exported to ONNX by Numa from the official code and weights, at a 1024 x 1024
  input (Linux) and at 512 x 512 (the iPhone and iPad); Numa rewrites them for
  its runtime after download. Used for Refine edge (hair and fur).
  Licence: MIT Licence, below (the BiRefNet licence)

Not mirrored here: downloaded by Numa from where their authors or exporters
publish them, listed so every model Numa can fetch has its licence here.

vitmatte_small.onnx  (Linux only; not offered by the paid Apple app)
  ViTMatte-S (Composition-1k), Jingfeng Yao et al., Hust Vision Lab.
  https://github.com/hustvl/ViTMatte  ONNX by Xenova on Hugging Face.
  Code: MIT Licence, below. The weights were trained on Adobe's Deep Image
  Matting dataset, whose licence says models trained on it "can only be used
  and distributed for noncommercial purposes and may not be sold". Credit:
  N. Xu, B. Price, S. Cohen, T. Huang, "Deep Image Matting", CVPR 2017.
  Numa offers it for non-commercial use only.

lama_fp32.onnx
  LaMa (big-lama), Roman Suvorov et al. https://github.com/advimman/lama
  ONNX by Carve: https://huggingface.co/Carve/LaMa-ONNX
  Licence: Apache License 2.0

yolox_s.onnx
  YOLOX-s, Megvii. https://github.com/Megvii-BaseDetection/YOLOX
  Licence: Apache License 2.0

realplksr_x2.onnx
  RealPLKSR x2, Dongheon Lee. https://github.com/dslisleedh/PLKSR
  ONNX by darktable: https://huggingface.co/darktable-org/upscale-realplksr-onnx
  Licence: MIT Licence, below

open_closed_eye.onnx
  Open-closed eye 0001, Intel. Open Model Zoo.
  https://github.com/openvinotoolkit/open_model_zoo
  Licence: Apache License 2.0

camera profiles (rawtherapee-dcpprofiles-*.tar.gz)
  The RawTherapee project. Their own licence and credits are inside each
  archive: GPL-3.0 for the full set (Linux), public domain and CC0 for the
  free set the Apple app fetches.

------------------------------------------------------------------------------
MIT Licence — YuNet
------------------------------------------------------------------------------
MIT License

Copyright (c) 2020 Shiqi Yu <shiqi.yu@gmail.com>

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

------------------------------------------------------------------------------
MIT Licence — rembg (the IS-Net ONNX export)
------------------------------------------------------------------------------
MIT License

Copyright (c) 2020 Daniel Gatis

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.


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Apache License 2.0
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------------------------------------------------------------------------------
MIT Licence — Restormer
------------------------------------------------------------------------------
MIT License

Copyright (c) 2022 Syed Waqas Zamir and contributors

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
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------------------------------------------------------------------------------
MIT Licence — BiRefNet
------------------------------------------------------------------------------
MIT License

Copyright (c) 2024 ZhengPeng

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
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------------------------------------------------------------------------------
MIT Licence — RealPLKSR
------------------------------------------------------------------------------
MIT License

Copyright (c) 2024 Dongheon Lee

Permission is hereby granted, free of charge, to any person obtaining a copy
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------------------------------------------------------------------------------
MIT Licence — ViTMatte (code)
------------------------------------------------------------------------------
MIT License

Copyright (c) 2023 Hust Vision Lab

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
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