/api/v1/face/enrollExtract compact, portable face embedding vectors. Store them in your own database, use them for identification, or build your own face recognition pipeline on top of our models.
REQUEST
curl -X POST https://api.faceguard.io/api/v1/face/enroll \ -H "X-API-Key: fg_live_your_key_here" \ -F "file=@user_photo.jpg" \ -F "user_id=emp_001"
{
"user_id": "emp_001",
"embeddings": {
"ArcFace": "base64_vector_string_here...",
"buffalo_l": "base64_vector_string_here..."
},
"face_detected": true
}Everything you need from a production-ready Face Embeddings API.
Returns embeddings from both ArcFace and buffalo_l for maximum downstream compatibility.
All embedding vectors are base64-encoded for easy storage in any database column.
Combined embeddings per user average ~5KB — trivially small for large user bases.
Store embeddings in your own DB. Use them later for identification with no vendor lock-in.
Integrate in minutes with our developer-friendly REST API.
POST a clear front-facing face image with a user_id to the enroll endpoint.
ArcFace and buffalo_l extract high-dimensional face vectors independently.
Receive base64-encoded embeddings. Store them in your own database under the user_id.
Data Output
All data returned as structured JSON — map directly to your database schema.
user_idembeddings.ArcFaceembeddings.buffalo_lface_detected{
"user_id": "emp_001",
"embeddings": {
"ArcFace": "base64_vector_string_here...",
"buffalo_l": "base64_vector_string_here..."
},
"face_detected": true
}Create a free account. Get 50 test API requests instantly — no credit card required.