| # Licenses |
|
|
| This repository mirrors third-party models. Each file remains under its |
| upstream license, reproduced/linked below. Arca claims no ownership of any |
| model here. |
|
|
| ## arcface.onnx — Apache-2.0 |
|
|
| Source: <https://github.com/onnx/models/tree/main/validated/vision/body_analysis/arcface> |
| (`arcfaceresnet100-8.onnx`), from the ONNX Model Zoo. ArcFace is by Deng et al. |
| Licensed Apache-2.0 per the model's directory in the ONNX Model Zoo. |
|
|
| ## auraface.mlpackage.zip — Apache-2.0 |
|
|
| Source: <https://huggingface.co/fal/AuraFace-v1> (`glintr100.onnx`), converted |
| to Core ML. `fal/AuraFace-v1`'s `LICENSE.md` was fetched and read in full: it |
| is stock Apache-2.0 with no field-of-use limit, no custom attribution |
| requirement, and no acceptable-use rider — permissive, matching the ONNX Model |
| Zoo files above. The model card states it was "trained on commercially and |
| publicly available data sources to enable its usage in commercial setting." |
|
|
| **Deliberately only `glintr100.onnx` from that repo.** `fal/AuraFace-v1` also |
| ships `scrfd_10g_bnkps.onnx`, `2d106det.onnx`, `1k3d68.onnx`, and |
| `genderage.onnx` — stock InsightFace detection/landmark/attribute models whose |
| upstream terms restrict the pretrained weights to non-commercial research |
| (InsightFace's own repo: "the training data containing the annotation (and the |
| models trained with these data) are available for non-commercial research |
| purposes only"). None of those are needed or mirrored: Arca gets face |
| detection and landmarks from the platform's own Vision/FaceAnalysis API on |
| every platform, never from an ONNX/CoreML detector. `glintr100.onnx` — the |
| recognition/embedding model — is the one file whose license this repo actually |
| verified end to end. |
|
|
| ## clip-vit-b32-image.onnx / clip-vit-b32-text.onnx — MIT |
|
|
| Sources: <https://huggingface.co/Qdrant/clip-ViT-B-32-vision> and |
| <https://huggingface.co/Qdrant/clip-ViT-B-32-text>. ONNX exports of OpenAI's |
| CLIP ViT-B/32. Both upstream repos declare `license: mit`. Original CLIP is by |
| OpenAI, released under MIT. |
|
|
| ## bpe_simple_vocab_16e6.txt.gz — MIT |
| |
| Source: <https://github.com/openai/CLIP> (`clip/bpe_simple_vocab_16e6.txt.gz`). |
| OpenAI's CLIP repository is MIT-licensed. |
|
|
| --- |
|
|
| ## Deliberately NOT hosted here |
|
|
| **Ultralytics YOLO** — v5, v8, v11 and the wider family — is **AGPL-3.0**. AGPL |
| requires that a larger work embedding these weights be released in full under |
| AGPL-3.0, or that the user hold an Ultralytics Enterprise License. Arca is |
| closed-source, so these weights are neither shipped nor mirrored. See |
| <https://www.ultralytics.com/license>. |
|
|
| Two things worth stating plainly, because both are easy to get wrong: |
|
|
| - **Putting the feature behind a paywall does not help.** AGPL triggers on |
| *distribution*, regardless of whether the recipient paid. |
| - **Wrapping it in a service does not launder it.** CodeProject.AI's |
| object-detection module is itself AGPL-3.0 and built on Ultralytics; reaching |
| the same weights over HTTP carries the same obligation. If anything AGPL is |
| stricter about network use — that is what the extra "A" is for. |
|
|
| If Arca ever needs object detection, the model must be Apache-2.0 (YOLOX from |
| Megvii, RT-DETR, or RTMDet — note YOLOX shares the "YOLO" name with Ultralytics |
| but is an unrelated lineage and a different license). |
|
|
| ## Previously hosted, removed |
|
|
| - **`yunet.onnx`** — MIT, from |
| [opencv/opencv_zoo](https://github.com/opencv/opencv_zoo/tree/main/models/face_detection_yunet) |
| (`face_detection_yunet_2023mar.onnx`), by Shiqi Yu and Wei Wu. Removed: Arca |
| detects faces with the OS `FaceDetector`, so it was never loaded. |
| - **`yolox_tiny.onnx`** — Apache-2.0, the official `0.1.1rc0` export from |
| [Megvii-BaseDetection/YOLOX](https://github.com/Megvii-BaseDetection/YOLOX). |
| Removed: mirrored ahead of a feature that doesn't exist yet. |
| |
