/api/v1/face/verifyCompare any two face images with enterprise-grade precision. Our verification engine fuses ArcFace, Facenet512, buffalo_l, and buffalo_sc for majority-vote decisions.
REQUEST
curl -X POST https://api.faceguard.io/api/v1/face/verify \ -H "X-API-Key: fg_live_your_key_here" \ -F "file1=@person_a.jpg" \ -F "file2=@person_b.jpg"
{
"verified": true,
"confidence": 0.91,
"models": {
"ArcFace": { "verified": true, "distance": 0.28 },
"Facenet512": { "verified": true, "distance": 0.35 },
"buffalo_l": { "verified": true, "distance": 0.31 },
"buffalo_sc": { "verified": false, "distance": 0.42 }
}
}Everything you need from a production-ready Face Verification API.
ArcFace, Facenet512, InsightFace buffalo_l, and buffalo_sc all vote independently.
Returns cosine distance per model alongside the final verified/not-verified verdict.
Each model has a calibrated threshold. Override per-request for your use case.
All four models run in parallel. Average response under 1.5 seconds.
Integrate in minutes with our developer-friendly REST API.
POST file1 and file2 — the two face images you want to compare.
All four models compute embeddings and cosine distances simultaneously.
If 3 or more models agree the faces match, the result is verified.
Data Output
All data returned as structured JSON — map directly to your database schema.
verifiedconfidencemodels.ArcFacemodels.Facenet512models.buffalo_lmodels.buffalo_sc{
"verified": true,
"confidence": 0.91,
"models": {
"ArcFace": { "verified": true, "distance": 0.28 },
"Facenet512": { "verified": true, "distance": 0.35 },
"buffalo_l": { "verified": true, "distance": 0.31 },
"buffalo_sc": { "verified": false, "distance": 0.42 }
}
}Create a free account. Get 50 test API requests instantly — no credit card required.