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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