# Verify #### Endpoint ```bash POST https://cloud.ooto-ai.com/api/v1.0/verify ``` #### Request Format * Method: POST * Content-Type: multipart/form-data * Query Parameters: check\_liveness, check\_deepfake #### Query Parameters
NameTypeRequiredDescription
check_livenessBooleanNoEnable liveness detection
check_deepfakeBooleanNoEnable deepfake detection
#### Authentication Headers To access the API, you need to include the following headers in your request: * APP-ID: Your application's unique identifier. * APP-KEY: Your application's authentication key. #### Form Data | Field | Type | Required | Description | | ------------- | ---- | -------- | ------------------------- | | first\_photo | File | Yes | User selfie (JPEG or PNG) | | second\_photo | File | Yes | User selfie (JPEG or PNG) | #### Example Request (cURL) ```bash curl -X POST --location 'https://cloud.ooto-ai.com/api/v1.0/doc/verify?check_liveness=true&check_deepfake=true' \ --header 'APP-ID: put_app_id_here' \ --header 'APP-KEY: put_app_key_here' \ --form 'first_photo=@"/path/to/first_photo"' \ --form 'second_photo=@"/path/to/second_photo"' ``` Replace «app\_id», «app\_key» with your actual credentials and the path to your doc image. #### Successful Response (HTTP 200) ```json { "transactionId": "2e286eb2-7c7b-4893-9298-ce9fa4c0d7d5", "result": { "firstFace": { "box": { "x": 655, "y": 1083, "w": 937, "h": 1210 }, "landmarks": [ [ 912, 1580 ], [ 1344, 1583 ], [ 1125, 1835 ], [ 946, 1996 ], [ 1297, 1999 ] ], "liveness": { "score": 0.9657026651967726, "fine": true }, "deepfake": { "score": 0.9491408169269562, "fine": true }, "quality": { "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 }, "occlusion": { "score": 0.0005318471812643111, "fine": true }, "macroblocks": { "score": 8.378465921055067e-9, "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 }, "distortion": { "score": 0.907139241695404, "fine": false }, "gender": "male", "age": 59, "race": "latino hispanic", "pitch": 5.798101723194122, "yaw": -2.267319895327091, "roll": -0.3308084886521101 }, "demography": { "gender": "male", "age": 59, "race": "latino hispanic" } }, "secondFace": { "box": { "x": 721, "y": 1090, "w": 887, "h": 1180 }, "landmarks": [ [ 970, 1475 ], [ 1359, 1545 ], [ 1101, 1734 ], [ 922, 1909 ], [ 1233, 1969 ] ], "liveness": { "score": 0.9435631834637448, "fine": true }, "deepfake": { "score": 0.9503215253353119, "fine": true }, "quality": { "uniformity": { "value": 0.7449888391064861, "fine": true }, "exposure": { "value": 0.5834772152336258, "fine": true }, "contrast": { "value": 0.6654583274963126, "fine": true }, "flare": { "score": 0.04973117262125015, "fine": true }, "blur": { "score": 0.0000016207906128329341, "fine": true }, "occlusion": { "score": 0.004378660582005978, "fine": true }, "macroblocks": { "score": 0.0000166263180290116, "fine": true }, "emotion": { "score": 0.35481420159339905, "fine": true }, "leftEyeClosed": { "score": 0, "fine": true }, "rightEyeClosed": { "score": 0, "fine": true }, "crfiqa": { "score": 0.5890940427780151, "fine": true }, "distortion": { "score": 0.3601391315460205, "fine": true }, "gender": "male", "age": 42, "race": "middle eastern", "pitch": -0.25353245437145233, "yaw": -8.07693064212799, "roll": -9.988648295402527 }, "demography": { "gender": "male", "age": 42, "race": "middle eastern" } }, "threshold": 0.75, "similarity": 0.878173828125, "same": true } } ``` #### Field Explanation | templateId | ID of the most similar template found in the database | | ------------------------------------------ | ----------------------------------------------------- | | similarity | Cosine similarity between input and matched template | | firstFace.liveness and secondFace.liveness | Returned if check\_liveness=true | | firstFace.deepfake and secondFace.deepfake | Returned if check\_deepfake=true | | firstFace | First face detection details | | secondFace | Second face detection details | #### Error response (HTTP 400) ```json { "transactionId": "efb66e50-4c87-493d-b026-543dacdbe314", "result": { "status": "error", "code": 1, "info": "photo should not be empty" } } ``` **Engine & OCR 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 high-quality, well-lit, frontal photos * Make sure there’s only one visible face * Use check\_liveness in environments with higher spoofing risk * Typical similarity threshold for a valid match: ≥ 0.75 --- # 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