REST API Reference

Analysis

Analyze the provided facial images and determine liveness and other autocapture information.

POST /analyze

Analyze the provided facial images and determine liveness and other autocapture information.

Please Note:

• Recommended resolution for provided images is 480x640.

• All images within a single request must have the same width and height.

• The recommended number of pixels between the subject’s eyes is 90 when using a front camera, and 60 with a back camera.

Request schema:

Name	Type	Description
video	object	Video object
meta_data	meta_data
workflow_data	workflow_data

Example request:

POST /analyze HTTP/1.1
Host: example.com
Content-Type: text/plain

{
    "video": {
        "meta_data": {
            "client_device_brand": "Apple",
            "client_device_model": "iPhone 8",
            "client_os_version": "11.0.3",
            "client_version": "KnomiSLive_v:2.4.1_b:0.0.0_sdk_v:2.4.1_b:0.0.0",
            "localization": "en-US",
            "programming_language_version": "Swift 4.1",
            "username": "test"
        },
        "workflow_data": {
            "workflow": "charlie4",
            "frames": [
                {
                    "data": "<base64 encoded image>",
                    "tags": [],
                    "timestamp": 1581714134137
                },
                {
                    "data": "<base64 encoded image>",
                    "tags": [],
                    "timestamp": 1581714134158
                },
                {
                    "data": "<base64 encoded image>",
                    "tags": [],
                    "timestamp": 1581714134189
                }
            ]
        }
    }
}

Status Codes:

• 200 OK – Success

• 400 Bad Request – The request is not valid

• 500 Internal Server Error – Internal error. Please see Error Codes section for detailed information.

200 Response schema:

Name	Type	Description
video	object	Video object
autocapture_result	autocapture_result
liveness_result	liveness_result
version	string	The current version of the Aware Face Liveness library.

Example response:

HTTP/1.1 200 OK
Content-Type: text/plain

{
    "video": {
        "autocapture_result": {
            "captured_frame": "<base64 encoded image>",
            "captured_frame_is_constructed": false,
            "feedback": []
        },
        "liveness_result": {
            "decision": "LIVE",
            "feedback": [],
            "score": 100,
            "score_frr": 0.5301376318487142
        },
        "version": "Aware FaceLiveness Library, version x.x.x"
    }
}

400 Response schema:

Name	Type	Description
error	object
code	integer	Error code Values: -1 (Unknown Error), -2 (Invalid Input JSON), -3 (Missing Mandatory Field), -4 (Field Has Wrong Type), -5 (Invalid Base64 String), -6 (Invalid Value), -7 (Invalid Image Data), -8 (Invalid Image Size)
description	string	Error description

Example response:

HTTP/1.1 400 Bad Request
Content-Type: text/plain

{
    "error": {
        "code": -2,
        "description": "Request was not valid JSON."
    }
}

500 Response schema:

Name	Type	Description
error	object
code	integer	Error code (see table below)
description	string	Error description

Example response:

HTTP/1.1 500 Internal Server Error
Content-Type: text/plain

{
    "error": {
        "code": "",
        "description": ""
    }
}

Encrypted version of analyze endpoint.

POST /analyzeEncrypted

Encrypted version of analyze endpoint.

Please Note:

• Encrypted request data is generated by Knomi software.

Request schema:

Name	Type	Description
key	string	Encrypted request ‘key’ value
iv	string	Encrypted request ‘iv’ value
p	string	Encrypted request ‘p’ value

Example request:

POST /analyzeEncrypted HTTP/1.1
Host: example.com
Content-Type: text/plain

{
    "key": "string",
    "iv": "string",
    "p": "string"
}

Status Codes:

• 200 OK – Success

• 400 Bad Request – The request is not valid

• 500 Internal Server Error – Internal error. Please see Error Codes section for detailed information.

200 Response schema:

Name	Type	Description
video	object	Video object
autocapture_result	autocapture_result
liveness_result	liveness_result
version	string	The current version of the Aware Face Liveness library.

Example response:

HTTP/1.1 200 OK
Content-Type: text/plain

{
    "video": {
        "autocapture_result": {
            "captured_frame": "<base64 encoded image>",
            "captured_frame_is_constructed": false,
            "feedback": []
        },
        "liveness_result": {
            "decision": "LIVE",
            "feedback": [],
            "score": 100,
            "score_frr": 0.5301376318487142
        },
        "version": "Aware FaceLiveness Library, version x.x.x"
    }
}

400 Response schema:

Name	Type	Description
error	object
code	integer	Error code Values: -1 (Unknown Error), -2 (Invalid Input JSON), -3 (Missing Mandatory Field), -4 (Field Has Wrong Type), -5 (Invalid Base64 String), -6 (Invalid Value), -7 (Invalid Image Data), -8 (Invalid Image Size)
description	string	Error description

Example response:

HTTP/1.1 400 Bad Request
Content-Type: text/plain

{
    "error": {
        "code": -2,
        "description": "Request was not valid JSON."
    }
}

500 Response schema:

Name	Type	Description
error	object
code	integer	Error code (see table below)
description	string	Error description

Example response:

HTTP/1.1 500 Internal Server Error
Content-Type: text/plain

{
    "error": {
        "code": "",
        "description": ""
    }
}

Check liveness

Analyze the provided facial images and determine liveness.

POST /checkLiveness

Analyze the provided facial images and determine liveness.

Please Note:

• Recommended resolution for provided images is 480x640.

• All images within a single request must have the same width and height.

• The recommended number of pixels between the subject’s eyes is 90 when using a front camera, and 60 with a back camera.

Request schema:

Name	Type	Description
video	object	Video object
meta_data	meta_data
workflow_data	workflow_data

Example request:

POST /checkLiveness HTTP/1.1
Host: example.com
Content-Type: text/plain

{
    "video": {
        "meta_data": {
            "client_device_brand": "Apple",
            "client_device_model": "iPhone 8",
            "client_os_version": "11.0.3",
            "client_version": "KnomiSLive_v:2.4.1_b:0.0.0_sdk_v:2.4.1_b:0.0.0",
            "localization": "en-US",
            "programming_language_version": "Swift 4.1",
            "username": "test"
        },
        "workflow_data": {
            "workflow": "charlie4",
            "frames": [
                {
                    "data": "<base64 encoded image>",
                    "tags": [],
                    "timestamp": 1581714134137
                },
                {
                    "data": "<base64 encoded image>",
                    "tags": [],
                    "timestamp": 1581714134158
                },
                {
                    "data": "<base64 encoded image>",
                    "tags": [],
                    "timestamp": 1581714134189
                }
            ]
        }
    }
}

Status Codes:

• 200 OK – Success

• 400 Bad Request – The request is not valid

• 500 Internal Server Error – Internal error. Please see Error Codes section for detailed information.

200 Response schema:

Name	Type	Description
video	object	Video object
liveness_result	liveness_result
version	string	The current version of the Aware Face Liveness library.

Example response:

HTTP/1.1 200 OK
Content-Type: text/plain

{
    "video": {
        "liveness_result": {
            "decision": "LIVE",
            "feedback": [],
            "score_frr": 0.5301376318487142
        },
        "version": "Aware FaceLiveness Library, version x.x.x"
    }
}

400 Response schema:

Name	Type	Description
error	object
code	integer	Error code Values: -1 (Unknown Error), -2 (Invalid Input JSON), -3 (Missing Mandatory Field), -4 (Field Has Wrong Type), -5 (Invalid Base64 String), -6 (Invalid Value), -7 (Invalid Image Data), -8 (Invalid Image Size)
description	string	Error description

Example response:

HTTP/1.1 400 Bad Request
Content-Type: text/plain

{
    "error": {
        "code": -2,
        "description": "Request was not valid JSON."
    }
}

500 Response schema:

Name	Type	Description
error	object
code	integer	Error code (see table below)
description	string	Error description

Example response:

HTTP/1.1 500 Internal Server Error
Content-Type: text/plain

{
    "error": {
        "code": "",
        "description": ""
    }
}

Encrypted version of checkLiveness endpoint.

POST /checkLivenessEncrypted

Encrypted version of checkLiveness endpoint.

Please Note:

• Encrypted request data is generated by Knomi software.

Request schema:

Name	Type	Description
key	string	Encrypted request ‘key’ value
iv	string	Encrypted request ‘iv’ value
p	string	Encrypted request ‘p’ value

Example request:

POST /checkLivenessEncrypted HTTP/1.1
Host: example.com
Content-Type: text/plain

{
    "key": "string",
    "iv": "string",
    "p": "string"
}

Status Codes:

• 200 OK – Success

• 400 Bad Request – The request is not valid

• 500 Internal Server Error – Internal error. Please see Error Codes section for detailed information.

200 Response schema:

Name	Type	Description
video	object	Video object
liveness_result	liveness_result
version	string	The current version of the Aware Face Liveness library.

Example response:

HTTP/1.1 200 OK
Content-Type: text/plain

{
    "video": {
        "liveness_result": {
            "decision": "LIVE",
            "feedback": [],
            "score_frr": 0.5301376318487142
        },
        "version": "Aware FaceLiveness Library, version x.x.x"
    }
}

400 Response schema:

Name	Type	Description
error	object
code	integer	Error code Values: -1 (Unknown Error), -2 (Invalid Input JSON), -3 (Missing Mandatory Field), -4 (Field Has Wrong Type), -5 (Invalid Base64 String), -6 (Invalid Value), -7 (Invalid Image Data), -8 (Invalid Image Size)
description	string	Error description

Example response:

HTTP/1.1 400 Bad Request
Content-Type: text/plain

{
    "error": {
        "code": -2,
        "description": "Request was not valid JSON."
    }
}

500 Response schema:

Name	Type	Description
error	object
code	integer	Error code (see table below)
description	string	Error description

Example response:

HTTP/1.1 500 Internal Server Error
Content-Type: text/plain

{
    "error": {
        "code": "",
        "description": ""
    }
}

Analyze the provided facial images and determine liveness. This request includes two active liveness requests.

POST /checkActiveLiveness

Analyze the provided facial images and determine liveness. This request includes two active liveness requests.

Please Note:

• Recommended resolution for provided images is 480x640.

• All images within a single request must have the same width and height.

• The recommended number of pixels between the subject’s eyes is 90 when using a front camera, and 60 with a back camera.

Request schema:

array of faceLivenessRequest - The array must have a size of 3 containing 1 request with a passive workflow and 2 requests with an active workflow.

Example request:

POST /checkActiveLiveness HTTP/1.1
Host: example.com
Content-Type: text/plain

[
    {
        "video": {
            "meta_data": {
                "client_device_brand": "Apple",
                "client_device_model": "iPhone 8",
                "client_os_version": "11.0.3",
                "client_version": "KnomiSLive_v:2.4.1_b:0.0.0_sdk_v:2.4.1_b:0.0.0",
                "localization": "en-US",
                "programming_language_version": "Swift 4.1",
                "username": "test"
            },
            "workflow_data": {
                "workflow": "foxtrot4",
                "frames": [
                    {
                        "data": "<base64 encoded image>",
                        "tags": [],
                        "timestamp": 1594826616671
                    }
                ]
            }
        }
    },
    {
        "video": {
            "meta_data": {
                "client_device_brand": "Apple",
                "client_device_model": "iPhone 8",
                "client_os_version": "11.0.3",
                "client_version": "KnomiSLive_v:2.4.1_b:0.0.0_sdk_v:2.4.1_b:0.0.0",
                "localization": "en-US",
                "programming_language_version": "Swift 4.1",
                "username": "test"
            },
            "workflow_data": {
                "workflow": "active_up",
                "frames": [
                    {
                        "data": "<base64 encoded image>",
                        "tags": [
                            "ACTIVE_HEAD_UP"
                        ],
                        "timestamp": 1594826616692
                    }
                ]
            }
        }
    },
    {
        "video": {
            "meta_data": {
                "client_device_brand": "Apple",
                "client_device_model": "iPhone 8",
                "client_os_version": "11.0.3",
                "client_version": "KnomiSLive_v:2.4.1_b:0.0.0_sdk_v:2.4.1_b:0.0.0",
                "localization": "en-US",
                "programming_language_version": "Swift 4.1",
                "username": "test"
            },
            "workflow_data": {
                "workflow": "active_down",
                "frames": [
                    {
                        "data": "<base64 encoded image>",
                        "tags": [
                            "ACTIVE_HEAD_DOWN"
                        ],
                        "timestamp": 1594826616883
                    }
                ]
            }
        }
    }
]

Status Codes:

• 200 OK – Success

• 400 Bad Request – The request is not valid

• 500 Internal Server Error – Internal error. Please see Error Codes section for detailed information.

200 Response schema:

Name	Type	Description
video	object	Video object
liveness_result	active_liveness_result
version	string	The current version of the Aware Face Liveness library.

Example response:

HTTP/1.1 200 OK
Content-Type: text/plain

{
    "video": {
        "liveness_result": {
            "decision": "LIVE",
            "feedback": [],
            "score_frr": 0.5301376318487142,
            "details": {
                "active_liveness": {
                    "decision": "LIVE",
                    "feedback": [],
                    "score_frr": 0.5301376318487142
                },
                "passive_liveness": {
                    "decision": "LIVE",
                    "feedback": [],
                    "score_frr": 0.5301376318487142
                }
            }
        },
        "version": "Aware FaceLiveness Library, version x.x.x"
    }
}

400 Response schema:

Name	Type	Description
error	object
code	integer	Error code Values: -1 (Unknown Error), -2 (Invalid Input JSON), -3 (Missing Mandatory Field), -4 (Field Has Wrong Type), -5 (Invalid Base64 String), -6 (Invalid Value), -7 (Invalid Image Data), -8 (Invalid Image Size)
description	string	Error description

Example response:

HTTP/1.1 400 Bad Request
Content-Type: text/plain

{
    "error": {
        "code": -2,
        "description": "Request was not valid JSON."
    }
}

500 Response schema:

Name	Type	Description
error	object
code	integer	Error code (see table below)
description	string	Error description

Example response:

HTTP/1.1 500 Internal Server Error
Content-Type: text/plain

{
    "error": {
        "code": "",
        "description": ""
    }
}

Encrypted version of checkActiveLiveness endpoint.

POST /checkActiveLivenessEncrypted

Encrypted version of checkActiveLiveness endpoint.

Please Note:

• Encrypted request data is generated by Knomi software.

Request schema:

Name	Type	Description
key	string	Encrypted request ‘key’ value
iv	string	Encrypted request ‘iv’ value
p	string	Encrypted request ‘p’ value

Example request:

POST /checkActiveLivenessEncrypted HTTP/1.1
Host: example.com
Content-Type: text/plain

{
    "key": "string",
    "iv": "string",
    "p": "string"
}

Status Codes:

• 200 OK – Success

• 400 Bad Request – The request is not valid

• 500 Internal Server Error – Internal error. Please see Error Codes section for detailed information.

200 Response schema:

Name	Type	Description
video	object	Video object
liveness_result	active_liveness_result
version	string	The current version of the Aware Face Liveness library.

Example response:

HTTP/1.1 200 OK
Content-Type: text/plain

{
    "video": {
        "liveness_result": {
            "decision": "LIVE",
            "feedback": [],
            "score_frr": 0.5301376318487142,
            "details": {
                "active_liveness": {
                    "decision": "LIVE",
                    "feedback": [],
                    "score_frr": 0.5301376318487142
                },
                "passive_liveness": {
                    "decision": "LIVE",
                    "feedback": [],
                    "score_frr": 0.5301376318487142
                }
            }
        },
        "version": "Aware FaceLiveness Library, version x.x.x"
    }
}

400 Response schema:

Name	Type	Description
error	object
code	integer	Error code Values: -1 (Unknown Error), -2 (Invalid Input JSON), -3 (Missing Mandatory Field), -4 (Field Has Wrong Type), -5 (Invalid Base64 String), -6 (Invalid Value), -7 (Invalid Image Data), -8 (Invalid Image Size)
description	string	Error description

Example response:

HTTP/1.1 400 Bad Request
Content-Type: text/plain

{
    "error": {
        "code": -2,
        "description": "Request was not valid JSON."
    }
}

500 Response schema:

Name	Type	Description
error	object
code	integer	Error code (see table below)
description	string	Error description

Example response:

HTTP/1.1 500 Internal Server Error
Content-Type: text/plain

{
    "error": {
        "code": "",
        "description": ""
    }
}

Decryption

General decryption endpoint.

POST /decrypt

General decryption endpoint.

Please Note:

• Encrypted request data is generated by Knomi software.

• Will decrypt any package and return the original unencrypted JSON package.

Request schema:

Name	Type	Description
key	string	Encrypted request ‘key’ value
iv	string	Encrypted request ‘iv’ value
p	string	Encrypted request ‘p’ value

Example request:

POST /decrypt HTTP/1.1
Host: example.com
Content-Type: text/plain

{
    "key": "string",
    "iv": "string",
    "p": "string"
}

Status Codes:

• 200 OK – Success

• 400 Bad Request – The request is not valid

• 500 Internal Server Error – Internal error. Please see Error Codes section for detailed information.

200 Response schema:

Output JSON schema is identical to the original unencrypted package.

Example response:

HTTP/1.1 200 OK
Content-Type: text/plain

{}

400 Response schema:

Name	Type	Description
error	object
code	integer	Error code Values: -1 (Unknown Error), -2 (Invalid Input JSON), -3 (Missing Mandatory Field), -4 (Field Has Wrong Type), -5 (Invalid Base64 String), -6 (Invalid Value), -7 (Invalid Image Data), -8 (Invalid Image Size)
description	string	Error description

Example response:

HTTP/1.1 400 Bad Request
Content-Type: text/plain

{
    "error": {
        "code": -2,
        "description": "Request was not valid JSON."
    }
}

500 Response schema:

Name	Type	Description
error	object
code	integer	Error code (see table below)
description	string	Error description

Example response:

HTTP/1.1 500 Internal Server Error
Content-Type: text/plain

{
    "error": {
        "code": "",
        "description": ""
    }
}

General

Version of knomi faceliveness server

GET /version

Version of knomi faceliveness server

Returns the version of knomi faceliveness server

Status Codes:

• 200 OK – OK

• 500 Internal Server Error – Internal error. Please see Error Codes section for detailed information.

200 Response schema:

string

Example response:

HTTP/1.1 200 OK
Content-Type: text/plain

Aware FaceLiveness Library, version x.x.x

500 Response schema:

Name	Type	Description
error	object
code	integer	Error code (see table below)
description	string	Error description

Example response:

HTTP/1.1 500 Internal Server Error
Content-Type: text/plain

{
    "error": {
        "code": "",
        "description": ""
    }
}

Structure Reference

faceLivenessRequest Model Structure

Name	Type	Description
video	object	Video object
meta_data	meta_data
workflow_data	workflow_data

faceLivenessRequestEncrypted Model Structure

Name	Type	Description
key	string	Encrypted request ‘key’ value
iv	string	Encrypted request ‘iv’ value
p	string	Encrypted request ‘p’ value

activeLivenessRequest Model Structure

Name	Type	Description
activeLivenessRequest	(array of activeLivenessRequest)	The array must have a size of 3 containing 1 request with a passive workflow and 2 requests with an active workflow.

analyzeResponse Model Structure

Name	Type	Description
video	object	Video object
autocapture_result	autocapture_result
liveness_result	liveness_result
version	string	The current version of the Aware Face Liveness library.

faceLivenessResponse Model Structure

Name	Type	Description
video	object	Video object
liveness_result	liveness_result
version	string	The current version of the Aware Face Liveness library.

activeLivenessResponse Model Structure

Name	Type	Description
video	object	Video object
liveness_result	active_liveness_result
version	string	The current version of the Aware Face Liveness library.

decryptResponse Model Structure

Output JSON schema is identical to the original unencrypted package.

autocapture_result Model Structure

Autocapture result

Name	Type	Description
captured_frame	string	Captured frame in base64 format.
captured_frame_is_constructed	boolean	If the captured frame is constructed image or not. Request can set perform_construction field to tell server to construct the captured image if it can be done.
feedback	(array of string)	Autocapture feedback

liveness_result Model Structure

Liveness result object

Name	Type	Description
feedback	(array of string)	Liveness feedback.
score	number	Liveness score Values: -1.0 (Error), 0.0 (Not Live), 100.0 (Live)
decision	string	classify liveness score to result type Values: LIVE (score 100), SPOOF (score 0), TOO_BLURRY (blur detection resulted too high), FACE_TOO_LOW_RESOLUTION (eye separation check resulted in too few pixels), TOO_LOW_FACIAL_DYNAMIC_RANGE (face detected had too low of a facial dynamic range score), UNABLE_TO_CALCULATE_LIVENESS (error score -1), TIMESTAMP_TOO_OLD (timestamp is too old), TIMESTAMP_IN_FUTURE (timestamp is in the future)
score_frr	number	Score used to threshold by false rejection rate. See the manual for more info.

active_liveness_result Model Structure

Active Liveness result object

Name	Type	Description
feedback	feedback
score	score
decision	decision
score_frr	score_frr
details	object	Object containing separated passive and active liveness results.
passive_liveness	liveness_result
active_liveness	liveness_result

meta_data Model Structure

(Optional) Metadata assocated with the transaction

Name	Type	Description
username	string	(Optional) Username associated with the transaction
client_device_brand	string	(Optional) Client’s device brand
client_device_model	string	(Optional) Client’s device model
client_os_version	string	(Optional) Client’s os version
client_version	string	(Optional) Client’s application version
localization	string	(Optional) Client’s localization
programming_language_version	string	(Optional) Client’s programming language version

workflow_data Model Structure

Parameters used in the workflow

Name	Type	Description
workflow	string	The workflow to be used for the request. Values: charlie2, charlie4, charlie6, foxtrot2, foxtrot4, foxtrot6, hotel2, hotel4, hotel6, active_down, active_left, active_right, active_up
frames	(array of frames)	A list of frame object
security_level	integer	(Optional) The parameter controls the balance of usability versus security.
timestamp	number	(Optional) The timestamp the package was created.
face_detection_granularity	number	(Optional) Face detection granularity
face_detection_sensitivity	number	(Optional) Face detection sensitivity.
face_detection_min_size	number	(Optional) Face detection min size.
face_detection_max_size	number	(Optional) Face detection max size.
rotation	object	(Optional) The angle of rotation to be applied to the image before analysis.
perform_construction	boolean	(Optional) Perform construction on the captured image.

frame Model Structure

Frame object

Name	Type	Description
data	string	Base64 encoded image. It supports JPEG image format and JPEG quality level of 90 is recommended to use to ensure expected accuracy.
tags	number	(Optional) Tag associated with the image. It can be used to include tagging information about the frame
timestamp	number	Timestamp of image with format of millisecond. The timestamp needs to be in sequential order for the frames defined in the request.

400Error Model Structure

Name	Type	Description
code	integer	Error code Values: -1 (Unknown Error), -2 (Invalid Input JSON), -3 (Missing Mandatory Field), -4 (Field Has Wrong Type), -5 (Invalid Base64 String), -6 (Invalid Value), -7 (Invalid Image Data), -8 (Invalid Image Size)
description	string	Error description

500Error Model Structure

Name	Type	Description
code	integer	Error code (see table below)
description	string	Error description

Response 500 Error Information

Response 500 Error Information

Code	Description
100	The library failed to allocate memory.
114	The profile specified was not a valid PreFace 6 profile.
118	The specified minimum size is out of the range [0 1].
119	The specified maximum size is out of the range [0 1].
120	The specified minimum size is greater than the specified maximum size.
121	The specified sensitivity is out of the range [0 1].
122	The specified granularity is out of the range [0 1].
125	Interframe time must be a number greater than 0.
139	The image passed into the Video Library could not be parsed for analysis.
141	The value for the timestamp provided was invalid. Timestamps must be greater than the previous timestamp and greater than or equal to 0.00 seconds.
152	The image format specified is invalid.
153	The submitted images did not all have the same width and height.
155	The face detection mode specified is invalid.
312	The rotation angle must be 0 90 180 or 270.

AutoCapture Feedback

• IMAGE_RESOLUTION_TOO_LOW - Image resolution is too low to be compliant.

• NO_FACE_DETECTED - No face was detected in the image provided.

• MULTIPLE_FACES_DETECTED - Multiple faces were detected in the image provided.

• INVALID_POSE - The subject’s facial pose is invalid.

• FACE_TOO_FAR - The subject’s face is too far from the camera.

• FACE_TOO_CLOSE - The subject’s face is too close to the camera.

• FACE_ON_LEFT - The subject’s face is too far to the left.

• FACE_ON_RIGHT - The subject’s face is too far to the right.

• FACE_TOO_HIGH - The subject’s face is too high in the frame.

• FACE_TOO_LOW - The subject’s face is too low in the frame.

• INSUFFICIENT_LIGHTING - The lighting is too dark.

• LIGHT_TOO_BRIGHT - The lighting is too bright.

• TOO_MUCH_BLUR - The camera is out of focus.

• GLASSES_PRESENT - The subject is non-compliant due to the presence of eye-wear.

• GLASSES_ABSENT - The subject is non-compliant due to the absence of eye-wear.

• SMILE_PRESENT - The subject is non-compliant because they are smiling.

• SMILE_ABSENT - The subject is non-compliant because they are not smiling.

• FOREHEAD_COVERING - The subject’s forehead is covered.

• BACKGROUND_TOO_CLUTTERED - The background is too cluttered.

• BACKGROUND_TOO_BRIGHT - The background is too bright.

• BACKGROUND_TOO_DARK - The background is too dark.

• LEFT_EYE_CLOSED - The subject’s left eye is closed.

• RIGHT_EYE_CLOSED - The subject’s right eye is closed.

• LEFT_EYE_OBSTRUCTED - The subject’s left eye is obstructed.

• RIGHT_EYE_OBSTRUCTED - The subject’s right eye is obstructed.

• OFF_ANGLE_GAZE - The subject’s gaze is off angle.

• HEAVY_FRAMES - The subject is non-compliant due to the thickness of their eye-wear frames.

• GLARE - The frame is non-compliant due to excessive glare.

• DARK_GLASSES - The subject is non-compliant due to the presence of dark glasses.

• FACIAL_SHADOWING - Shadows detected on the subject’s face.

• RED_EYE - Red eye detected for the subject.

• UNNATURAL_LIGHTING_COLOR - An unnatural lighting color was detected in the frame.

• AWARE_INTERNAL_ERROR_1 - Internal Error 1