Face Enrollment

Creates a new facial biometric template that can be used later for identity verification. This operation supports optional liveness and deepfake checks during enrollment.

Endpoint

POST https://cloud.ooto-ai.com/api/v1.0/add

Request Format

• Method: POST

• Content-Type: multipart/form-data

• Query parameters: check_liveness, check_deepfake

Query Parameters

Name	Type	Required	Description
check_liveness	Boolean	No	Enable liveness check (default: false)
check_deepfake	Boolean	No	Enable deepfake check (default: false)

Form Data

Field	Type	Required	Description
photo	File	Yes	JPEG or PNG image containing exactly one face
templateId	String	No	Optional custom ID for the face template

Authentication Headers

• APP-ID: Your application's unique identifier.

• APP-KEY: Your application's authentication key.

Example Request (cURL)

curl -X POST --location 'https://cloud.ooto-ai.com/api/v1.0/add?check_liveness=true&check_deepfake=true' \
--header 'APP-ID: <put_app_id_here>' \
--header 'APP-KEY: <put_app_key_here>' \
--form 'photo=@"/path/to/photo"' \
--form 'templateId=<UUID>'

Replace «put_app_id_here», «put_app_key_here» with your actual credentials and the path to your selfie image.

Successful Response (HTTP 200)

{
  "transactionId": "379875cf-9e21-47cf-95bb-4a3d7c373638",
  "result": {
    "enroll": {
      "templateId": "16de28ea-dd15-4005-9a42-539e911db2d3"
    },
    "quality": {
      "pitch": 5.798101723194122,
      "yaw": -2.267319895327091,
      "roll": -0.3308084886521101,
      "uniformity": {
        "value": 0.7976967765996249,
        "fine": true
      },
      "exposure": {
        "value": 0.6352452907096943,
        "fine": true
      },
      "contrast": {
        "value": 0.780912373462111,
        "fine": true
      },
      "flare": {
        "score": 0.026086460798978806,
        "fine": true
      },
      "blur": {
        "score": 0.000007942797310533933,
        "fine": true
      },
      "macroblocks": {
        "score": 8.378465921055067e-9,
        "fine": true
      },
      "distortion": {
        "score": 0.907139241695404,
        "fine": false
      },
      "occlusion": {
        "score": 0.0005318471812643111,
        "fine": true
      },
      "emotion": {
        "score": 0.020526384934782982,
        "fine": true
      },
      "leftEyeClosed": {
        "score": 0.004296362400054932,
        "fine": true
      },
      "rightEyeClosed": {
        "score": 0.000009238719940185547,
        "fine": true
      },
      "crfiqa": {
        "score": 0.5999192595481873,
        "fine": true
      }
    },
    "demography": {
      "age": 59,
      "gender": "male",
      "race": "latino hispanic"
    },
    "box": {
      "x": 655,
      "y": 1083,
      "w": 937,
      "h": 1210
    },
    "landmarks": [
      [
        912,
        1580
      ],
      [
        1344,
        1583
      ],
      [
        1125,
        1835
      ],
      [
        946,
        1996
      ],
      [
        1297,
        1999
      ]
    ]
  }
}

Error response (HTTP 400)

{
    "transactionId": "9191079a-4f80-4c8a-9a4b-528af2cfd3c4",
    "result": {
        "status": "error",
        "code": 5,
        "info": "can not detect face"
    }
}

Engine Errors

Code	Info
1	photo should not be empty
2	wrong mime-type in input data
3	photo size is 0 bytes
4	can not decode image, check it is valid jpeg or png file
5	can not detect face
6	more than one face detected on photo
9	can not extract features from sample, probably it is too small

Best Practices

• Use sharp, high-quality, frontal-face photos

• Face size ≥ 200×200 pixels in image

• Avoid masks, sunglasses, filters

• Only one face must be present in the image