API Reference

get_version

def get_version() -> str:

Name	get_version
Description	Retrieves the SDK version information from a library.
Input	None
Output	The version string is returned as a standard Python string.

get_device_id

def get_device_id() -> str:

Name	get_device_id
Description	Retrieves the Hardware ID from a library.
Input	None
Output	The Hardware ID is returned as a standard Python string.

init_sdk

def init_sdk(dict_path: str, online_key: str) -> int:

Name	init_sdk
Description	Initializes the SDK in online mode.
Input	dict_path (str): Path to the engine binary files directory online_key (str): Online key string
Output	Status code indicating the result of the initialization. 0: Success Non-zero: Initialization failed

init_sdk_offline

def init_sdk_offline(dict_path: str, offline_key_path: str) -> int:

Name	init_sdk_offline
Description	Initializes the SDK in offline mode.
Input	dict_path (str): Path to the engine binary files directory offline_key (str): Path to the offline license key file
Output	Status code indicating the result of the initialization. 0: Success Non-zero: Initialization failed

extract_template

def extract_template(image: np.ndarray, width: int, height: int, face_bbox: np.ndarray, template: np.ndarray, template_len: np.ndarray) -> int:

Name	extract_template
Description	Extracts a template from an image
Input	image (numpy.ndarray): Input image matrix width (int): Width of the input image height (int): Height of the input image face_bbox (numpy.ndarray): Face bounding box coordinates. Extracted face bbox will be stored template (numpy.ndarray): Template buffer. Extracted template will be stored template_len (numpy.ndarray): Length of the extracted template
Output	Status code indicating the result of the template extraction. >0: Success 0: No Face -1: SDK Activation Error -2: SDK Initialization Error

calculate_similarity

def calculate_similarity(feature_1: np.ndarray, feature_2: np.ndarray) -> float:

Name	calculate_similarity
Description	Calculates the similarity between two features
Input	feature_1 (numpy.ndarray): 1st feature feature_2 (numpy.ndarray): 2nd feature
Output	Similarity score between the two features The score ranges from 0.0 to 1.0 Default Threshold is 0.67