Face Factor

This section covers how to use the Face Factor for generating and verifying Private IDs.

class cryptonets_python_sdk.factor.FaceFactor(*args, **kwargs)

The FaceFactor class implements the following methods :

  1. is_valid: Verifies the face of the user.

  2. estimate_age: Predicts the age of the face.

  3. compare: Compare two faces for verification.

  4. enroll: Enrolls the face of the user.

  5. predict: Predicts the face of the user.

  6. delete: Deletes the user from the system

  7. antispoof_check: Check if the image is spoofed or not

  8. get_iso_face: Takes the face image and gives back the image in ISO Spec format

  9. compare_doc_with_face: Check if the images are of same person or not

Parameters:
api_keystr

The API key for using the FaceFactor server.

server_urlstr

The URL of the FaceFactor server.

logging_levelLoggingLevel (Optional)

LoggingLevel needed while performing operation

configConfigObject (Optional)

Configuration class object with parameters

Methods

is_valid([image_path, image_data, config])

Check if the image is valid for using in the face recognition

estimate_age([image_path, image_data, config])

Check if the image is valid and returns the age of the image

compare([image_path_1, image_path_2, ...])

Check if the images are of same person or not

enroll([image_path, image_data, config])

Enrolls the image in the face recognition server

predict([image_path, image_data, config])

Predicts the image in the face recognition server

delete(puid[, config_object])

Deletes a user by their PUID from the system

antispoof_check([image_path, image_data, config])

Check if the image is spoofed or not

get_iso_face([image_path, image_data, config])

Takes the face image and gives back the image in ISO Spec format

compare_doc_with_face([face_path, doc_path, ...])

Check if the images are of same person or not
Returns:
FaceFactor

Instance of the FaceFactor class.

compare(image_path_1: str | None = None, image_path_2: str | None = None, image_data_1: array | None = None, image_data_2: array | None = None, config: ConfigObject | None = None) → FaceCompareResult

Check if the images are of same person or not

Parameters:
image_path_1

Directory path to the first image file

image_path_2

Directory path to the second image file

config (Optional)

Additional configuration parameters for the operation

image_data_1 (Optional)

First Image data in numpy RGB format

image_data_2 (Optional)

Second Image data in numpy RGB format

Returns:
FaceCompareResult

status: int [0 if call successful -1 if unsuccessful]

message: str [Message from the operation]

result: int [1 if same, -1 if different]

distance: float [comparaison distance]

first_validation_result: int

second_validation_result: int

delete(puid: str, config_object: ConfigObject | None = None) → FaceDeleteResult

Deletes a user by their PUID from the system

Parameters:
puidstr

The PUID (Private User ID) of the user to delete

config_objectConfigObject (Optional)

Additional configuration parameters for the operation

Returns:
FaceDeleteResult

Result of the delete operation

enroll(image_path: str | None = None, image_data: array | None = None, config: ConfigObject | None = None) → FaceEnrollPredictResult

Enrolls the image in the face recognition server

Parameters:
image_path

Directory path to the image file

config (Optional)

Additional configuration parameters for the operation

image_data (Optional)

Image data in numpy RGB format

Returns:
FaceEnrollPredictResult
estimate_age(image_path: str | None = None, image_data: array | None = None, config: ConfigObject | None = None) → AgeEstimateResult

Check if the image is valid and returns the age of the image

Parameters:
image_path

Directory path to the image file

config (Optional)

Additional configuration parameters for the operation

image_data (Optional)

Image data in numpy RGB format

Returns:
AgeEstimateResult
operation_status_code: ApiReturnStatus [ApiReturnStatus.API_NO_ERROR (0) if successful, failure otherwise].

if failure, face_age_objects list will be None. The operation is considered successful if no face were detected in the image. In his case face_age_objects will be an empty list.

operation_message: str [Message explaining the error if any] face_age_objects: List[FaceAgeObjectResult]

get_iso_face(image_path: str | None = None, image_data: array | None = None, config: ConfigObject | None = None) → ISOFaceResult

Takes the face image and gives back the image in ISO Spec format

Parameters:
image_path

Directory path to the image file

config (Optional)

Additional configuration parameters for the operation

image_data (Optional)

Image data in numpy RGB format

Returns:
ISOFaceResult

status: int [0 if successful -1 if unsuccessful]

message: str [Message from the operation]

image: PIL.Image

confidence: float

iso_image_width: str

iso_image_height: str

iso_image_channels: str

is_valid(image_path: str | None = None, image_data: array | None = None, config: ConfigObject | None = None) → FaceValidationResult

Check if the image is valid for using in the face recognition

Parameters:
image_path

Directory path to the image file

config (Optional)

Additional configuration parameters for the operation

image_data (Optional)

Image data in numpy RGB format

Returns:
FaceValidationResult

error: int [0 if successful -1 if any error]

message: str [Message from the operation]

face_objects: List[FaceObjectResult]

predict(image_path: str | None = None, image_data: array | None = None, config: ConfigObject | None = None) → FaceEnrollPredictResult | List[FaceEnrollPredictResult]

Predicts the image in the face recognition server

Parameters:
image_path

Directory path to the image file

config (Optional)

Additional configuration parameters for the operation

image_data (Optional)

Image data in numpy RGB format

Returns:
FaceEnrollPredictResult