Face Factor

Factor implements the functionalities of each factors to generate and verify Private IDs .

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

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

The FaceFactor class implements the methods for enrolling and predicting the Face module as part of the Biometric Authentication.

It exposes five methods as part of the interface:

is_valid: Verifies the face of the user.
estimate_age: Predicts the age of the face.
compare: Compare two faces for verification.
enroll: Enrolls the face of the user.
predict: Predicts the face of the user.
delete: Deletes the user from the system

Parameters:

Name
api_key
Type
str
Description
The API key for using the FaceFactor server.
Name
server_url
Type
str
Description
The URL of the FaceFactor server.
Name
local_storage_path
Type
str(optional)
Description
Absolute path to the local storage.
Name
logging_level
Type
LoggingLevel (Optional)
Description
LoggingLevel needed while performing operation
Name
tf_num_thread
Type
int (Optional)
Description
Number of thread to use for Tensorflow model inference
Name
cache_type
Type
CacheType (Optional)
Description
To set the cache on / off
Name
config
Type
ConfigObject (Optional)
Description
Configuration class object with parameters

Methods

Method	Description
is_valid([image_path, image_data, config])	Check if the image is valid for using in the face recognition
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
get_iso_face([image_path, image_data, config])	Takes the face image and gives back the image in ISO Spec format

Delete

Returns:

Name
FaceFactor
Description
Instance of the FaceFactor class.

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

Check if the images are of same person or not

Parameters

Name
image_path_1
Description
Directory path to the first image file
Name
image_path_2
Description
Directory path to the second image file
Name
config
Type
Optional
Description
Additional configuration parameters for the operation
Name
image_data_1
Type
Optional
Description
First Image data in numpy RGB format
Name
image_data_2
Type
Optional
Description
Second Image data in numpy RGB format

Returns

FaceCompareResult

  status: int [0 if same, 1 if different, -1 if unsuccessful]

  message: str [Message from the operation]

  result: str

  distance_min: str

  distance_mean: str

  distance_max: str

  first_validation_result: str

  second_validation_result: str

Enroll

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

Parameters

Name
image_path
Description
Directory path to the first image file
Name
config
Type
Optional
Description
Additional configuration parameters for the operation
Name
image_data
Type
Optional
Description
Image data in numpy RGB format

Returns

FaceEnrollPredictResult

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

  message: str [Message from the operation]

  enroll_level: str

  guid: str

  puid: str

  token: str

Estimate Age

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

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

Parameters

Name
image_path
Description
Directory path to the first image file
Name
config
Type
Optional
Description
Additional configuration parameters for the operation
Name
image_data
Type
Optional
Description
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]

Face ISO

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

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

Parameters

Name
image_path
Description
Directory path to the first image file
Name
config
Type
Optional
Description
Additional configuration parameters for the operation
Name
image_data
Type
Optional
Description
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

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

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

Parameters

Name
image_path
Description
Directory path to the first image file
Name
config
Type
Optional
Description
Additional configuration parameters for the operation
Name
image_data
Type
Optional
Description
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

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

Predicts the image in the face recognition server

Parameters

Name
image_path
Description
Directory path to the first image file
Name
config
Type
Optional
Description
Additional configuration parameters for the operation
Name
image_data
Type
Optional
Description
Image data in numpy RGB format

Returns

FaceEnrollPredictResult

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

  message: str [Message from the operation]

  enroll_level: str

  guid: str

  puid: str

  token: str