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mudler/face-detect-gguf
face-detect-gguf is a machine learning model from mudler. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for gguf. The card lists the license as other.
GGUF model packs for the face-detect backend of LocalAI.
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From the Hugging Face model README
GGUF model packs for the face-detect backend of LocalAI.
Each .gguf here is a self-contained, metadata-driven pack (detector + recognizer,
plus genderage / anti-spoof heads when the source provides them) produced by
face-detect.cpp, a standalone
C++/ggml port of the insightface and OpenCV-Zoo face pipelines. No Python or ONNX
runtime is needed at inference time: the GGUF carries the weights verbatim plus the
forward-graph topology in its KV metadata, and the C++ engine replays it.
e22260d5d5490b37b021b7f795079f386d553afd (face-detect.cpp)general.architecture = "facedetect"face-detect backendThe packs in this repo carry two different licenses depending on their source weights. Pick the pack that matches your use case.
| Pack | Source | License | Commercial use |
|---|---|---|---|
buffalo_l.gguf | insightface buffalo_l | Non-commercial, research-only | No |
buffalo_m.gguf | insightface buffalo_m | Non-commercial, research-only | No |
buffalo_s.gguf | insightface buffalo_s | Non-commercial, research-only | No |
buffalo_sc.gguf | insightface buffalo_sc | Non-commercial, research-only | No |
antelopev2.gguf | insightface antelopev2 | Non-commercial, research-only | No |
yunet-sface.gguf | OpenCV-Zoo YuNet + SFace | Apache-2.0 | Yes |
The insightface buffalo packs (SCRFD + ArcFace) are released by insightface for NON-COMMERCIAL research purposes only. They are redistributed here as derived GGUF artifacts under those same upstream terms. If you need a commercial-friendly option, use
yunet-sface.gguf(Apache-2.0).
buffalo_l.gguf - SCRFD det_10g + ArcFace ResNet50 (512-d)The primary, highest-accuracy insightface pack. SCRFD det_10g detector + ArcFace
w600k_r50 (IResNet50) recognizer producing a 512-d embedding, plus the genderage
head and the MiniFASNet anti-spoof ensemble ([email protected] + [email protected], 80x80) bundled in.
License: non-commercial / research-only.
buffalo_m.gguf - SCRFD det_2.5g + ArcFace ResNet50 (512-d)Mid-size insightface pack. SCRFD det_2.5g detector + ArcFace w600k_r50 512-d
recognizer (+ genderage + anti-spoof when present). The det_2.5g topology is replayed
through the metadata-driven graph interpreter. License: non-commercial / research-only.
buffalo_s.gguf - SCRFD det_500m + ArcFace MobileFaceNet (512-d)Smallest insightface pack. SCRFD det_500m detector + ArcFace MobileFaceNet
(w600k_mbf) 512-d recognizer (+ genderage + anti-spoof when present). Both the
det_500m detector and the MobileFaceNet recognizer are replayed metadata-driven.
License: non-commercial / research-only.
buffalo_sc.gguf - SCRFD det_500m + a small ArcFace (512-d)The compact detect-plus-recognize insightface pack. SCRFD det_500m detector + a
small ArcFace embedder producing a 512-d embedding, detection and recognition only
(no genderage / anti-spoof heads). License: non-commercial / research-only.
antelopev2.gguf - SCRFD det_10g + ArcFace ResNet100 glint360k (512-d)The highest-accuracy insightface pack. SCRFD det_10g detector + ArcFace ResNet100
trained on glint360k, producing a 512-d embedding. License: non-commercial / research-only.
yunet-sface.gguf - YuNet detector + SFace recognizer (128-d), Apache-2.0The commercial-friendly alternative. OpenCV-Zoo YuNet (face_detection_yunet_2023mar)
anchor-free detector + SFace (face_recognition_sface_2021dec) recognizer producing
a 128-d embedding. SFace carries its (x-127.5)/128 normalization in-graph. License:
Apache-2.0 (commercial use OK).
Each pack was validated against its reference pipeline (insightface for buffalo,
cv2 FaceDetectorYN/FaceRecognizerSF for yunet+sface) before upload. The
decode-isolated embedding gate is cosine >= 0.9999 and max|d| <= 1e-3.
| Pack | Dtype | Embedding cosine (gate) | Result |
|---|---|---|---|
buffalo_l.gguf | f16 | 1.000000 | PASS |
buffalo_m.gguf | f16 | 1.000000 | PASS |
buffalo_s.gguf | f16 | 1.000000 | PASS |
buffalo_sc.gguf | f16 | 1.000000 | PASS |
antelopev2.gguf | f16 | 1.000000 | PASS |
yunet-sface.gguf | f16 | 1.000000 | PASS |
f16 quantization is applied only to the large 2-D Gemm weights (the ArcFace / SFace embedding head); every conv kernel, BN stat, bias and projection head stays F32, so f16 is near-lossless. All six packs meet the strict near-lossless bound at f16.
These packs are intended to be installed through the LocalAI model gallery
(face-detect-buffalo-l / -m / -s / -sc / -antelopev2, and face-detect-yunet-sface) and run by the
face-detect backend. See the LocalAI and
face-detect.cpp documentation.