1:1 Verification answers the question: "Are these two faces the same person?" It compares two face images (or one image against an enrolled face ID) and returns a similarity score between 0 and 1.

Use verification when you need to confirm that the person presenting themselves matches a known identity, for example re-authentication, document-to-selfie matching, or access control.

Compare two images

The simplest form: submit two face images and get back a similarity score. No collection or enrollment required.

curl -X POST https://your-domain.com/api/v1/compare \
  -H "X-API-Key: YOUR_API_KEY" \
  -F "image_a=@reference.jpg" \
  -F "image_b=@probe.jpg"

{
  "success": true,
  "data": {
    "similarity": 0.91,
    "verified": true,
    "threshold": 0.55,
    "query_time_ms": 38
  }
}

Verify against an enrolled face

Compare a probe image against a specific enrolled face ID in a collection. More efficient than comparing two raw images since the enrolled face reference is already stored.

curl -X POST https://your-domain.com/api/v1/collections/COLLECTION_ID/verify \
  -H "X-API-Key: YOUR_API_KEY" \
  -F "image=@probe.jpg" \
  -F "face_id=face_01j9abc..."

{
  "success": true,
  "data": {
    "face_id": "face_01j9abc...",
    "external_id": "user_alice_001",
    "similarity": 0.93,
    "verified": true,
    "threshold": 0.55,
    "metadata": {"name": "Alice Smith"},
    "query_time_ms": 22
  }
}

Verify by external ID

If you prefer to reference faces by your own IDs rather than internal face IDs, use the external_id parameter. When multiple embeddings exist for the same external_id (auto-enrolled secondary embeddings), the highest similarity across all of them is returned.

POST /api/v1/collections/{collection_id}/verify
X-API-Key: fr_live_xxxxxxxxxxxxxxxxxxxxxxxxxxxx
Content-Type: multipart/form-data

image=@probe.jpg
external_id=user_alice_001

Response fields

Choosing a threshold

The default threshold of 0.55 works well for most verification use-cases. You can override it per-request with the threshold parameter:

• High security (0.65–0.75): Fewer false positives. Use for access control, financial verification.
• Balanced (0.55, default): Good for most identity verification use-cases.
• Permissive (0.40–0.50): More false positives. Suitable for photo deduplication or fuzzy matching.

# Override threshold per request
image=@probe.jpg
face_id=face_01j9abc...
threshold=0.70

Try it live: verify by external ID

Enter your API key, collection ID, and the external ID of an enrolled face, then upload a probe image.