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insightface-buffalo-l
Face recognition using insightface's `buffalo_l` pack
(SCRFD-10GF detector + ResNet50 ArcFace 512-d embedder + genderage head, ~326MB).
Default choice, highest accuracy.
Weights delivered via LocalAI's gallery mechanism (SHA-256 verified,
cached in the models directory like any other managed model).
NON-COMMERCIAL RESEARCH USE ONLY. For commercial use see `insightface-opencv`.
Repository: localaiLicense: insightface-non-commercial
insightface-buffalo-m
Mid-tier insightface pack (SCRFD-2.5GF detector + ResNet50 ArcFace +
genderage, ~313MB). Same recognition accuracy as `buffalo_l` with a
cheaper detector — good balance on mid-range hardware.
NON-COMMERCIAL RESEARCH USE ONLY.
Repository: localaiLicense: insightface-non-commercial
insightface-buffalo-s
Small insightface pack (SCRFD-500MF detector + MBF 512-d embedder +
genderage, ~159MB). Good fit for mid-range CPU deployments.
NON-COMMERCIAL RESEARCH USE ONLY.
Repository: localaiLicense: insightface-non-commercial
insightface-buffalo-sc
Ultra-small insightface pack (SCRFD-500MF + MBF recognition only, ~16MB).
NO landmarks, NO age/gender head — `/v1/face/analyze` returns empty
attributes for this pack. Ideal for edge/embedded deployments where
only verification and embedding are needed.
NON-COMMERCIAL RESEARCH USE ONLY.
Repository: localaiLicense: insightface-non-commercial
insightface-antelopev2
Largest insightface pack (SCRFD-10GF + ResNet100@Glint360K recognizer +
genderage, ~407MB). Higher recognition accuracy than `buffalo_l` on
harder benchmarks; pays for it in GPU memory.
NON-COMMERCIAL RESEARCH USE ONLY.
Repository: localaiLicense: insightface-non-commercial
insightface-opencv
Face recognition using OpenCV Zoo weights: YuNet detector + SFace
128-d recognizer (fp32). APACHE 2.0 — safe for commercial use.
Lower accuracy than insightface packs, no demographic head
(`/v1/face/analyze` returns detection regions only).
Weights are downloaded on install via LocalAI's gallery mechanism
(~40MB).
Repository: localaiLicense: apache-2.0
insightface-opencv-int8
Int8-quantized OpenCV Zoo face pair (YuNet int8 + SFace int8, ~12MB).
Roughly 3x smaller and noticeably faster on CPU than the fp32 variant
at comparable accuracy for face tasks. APACHE 2.0 — commercial-safe.
Weights are downloaded on install via LocalAI's gallery mechanism.
Repository: localaiLicense: apache-2.0
face-detect-buffalo-l
Face recognition with insightface's `buffalo_l` pack (SCRFD-10GF
detector + ResNet50 ArcFace 512-d embedder), ported to C++/ggml and
shipped as a single GGUF for the `face-detect` backend. Highest
accuracy of the buffalo line.
No Python / onnxruntime / torch runtime: face-detect.cpp reads the
detector and embedder architecture (`facedetect.arch`) directly from
the GGUF metadata, so installing this entry is all that is needed to
select buffalo_l. Drives the Embedding / Detect / FaceVerify /
FaceAnalyze gRPC rpcs and the /v1/face/{verify,analyze,embed,detect}
REST endpoints. This GGUF also embeds the MiniFASNet anti-spoof
ensemble, available via the FaceVerify `anti_spoof` request flag.
NON-COMMERCIAL RESEARCH USE ONLY: for commercial use see
`face-detect-yunet-sface`.
Repository: localaiLicense: insightface-non-commercial
face-detect-buffalo-m
Face recognition with insightface's `buffalo_m` pack (SCRFD-2.5GF
detector + ResNet50 ArcFace embedder), converted to a C++/ggml GGUF
for the `face-detect` backend. Same recognition accuracy as
`buffalo_l` with a cheaper detector: a good balance on mid-range
hardware.
The architecture (`facedetect.arch`) is read from the GGUF metadata,
so this entry alone selects the buffalo_m engine. This GGUF also
embeds the MiniFASNet anti-spoof ensemble, available via the
FaceVerify `anti_spoof` request flag. NON-COMMERCIAL RESEARCH USE
ONLY.
Repository: localaiLicense: insightface-non-commercial
face-detect-buffalo-s
Face recognition with insightface's `buffalo_s` pack (SCRFD-500MF
detector + MBF 512-d embedder), converted to a C++/ggml GGUF for the
`face-detect` backend. Small and CPU-friendly: a good fit for
mid-range and edge deployments.
The architecture (`facedetect.arch`) is read from the GGUF metadata,
so this entry alone selects the buffalo_s engine. This GGUF also
embeds the MiniFASNet anti-spoof ensemble, available via the
FaceVerify `anti_spoof` request flag. NON-COMMERCIAL RESEARCH USE
ONLY.
Repository: localaiLicense: insightface-non-commercial
face-detect-buffalo-sc
Face recognition with insightface's `buffalo_sc` pack (SCRFD-500M
detector + a small ArcFace embedder), converted to a C++/ggml GGUF
for the `face-detect` backend. This is the smallest insightface
pack: the lightest option for low-resource and edge deployments.
The architecture (`facedetect.arch`) is read from the GGUF metadata,
so this entry alone selects the buffalo_sc engine. If this GGUF
embeds the MiniFASNet anti-spoof ensemble, it is available via the
FaceVerify `anti_spoof` request flag. NON-COMMERCIAL RESEARCH USE
ONLY.
Repository: localaiLicense: insightface-non-commercial
face-detect-antelopev2
Face recognition with insightface's `antelopev2` pack (SCRFD-10G
detector + ArcFace glint360k R100, 512-d embedder), converted to a
C++/ggml GGUF for the `face-detect` backend. The higher-accuracy
insightface pack: heavier, but the best fit when recognition
quality matters more than speed.
The architecture (`facedetect.arch`) is read from the GGUF metadata,
so this entry alone selects the antelopev2 engine. If this GGUF
embeds the MiniFASNet anti-spoof ensemble, it is available via the
FaceVerify `anti_spoof` request flag. NON-COMMERCIAL RESEARCH USE
ONLY.
Repository: localaiLicense: insightface-non-commercial
face-detect-yunet-sface
Face recognition with OpenCV Zoo weights: YuNet detector + SFace
128-d recognizer, converted to a C++/ggml GGUF for the `face-detect`
backend. APACHE 2.0: safe for commercial use. Lower accuracy than the
buffalo packs and no demographic head, but the commercial-friendly
alternative to the insightface buffalo line.
The architecture (`facedetect.arch`) is read from the GGUF metadata,
so this entry alone selects the YuNet + SFace engine.
Repository: localaiLicense: apache-2.0