Face Recognition SDK - Server
This stands for face recognition docker, facial recognition docker, face matching docker, face comparison docker, face search engine docker, face identification docker, face search ID docker on server
We implemented face recognition SDK on docker container
We provide the Face Recognition SDK for both Windows and Linux.
Features
License
We offer lifetime licenses per machine for Servers (Windows, Linux).
To request a license, please contact us:
Email: contact@kby-ai.com
Telegram: @kbyai
WhatsApp: +19092802609
Skype: live:.cid.66e2522354b1049b
System Requirements
1. Windows
CPU: 2 cores or more (Recommended: 2 cores)
RAM: 4 GB or more (Recommended: 8 GB)
HDD: 4 GB or more (Recommended: 8 GB)
OS: Windows 7 or later
Architecture: x64
Dependency: OpenVINO™ Runtime (Version: 2022.3), ncnn Runtime(20220721), Vulkan SDK Runtime(1.3.250)
2. Linux
CPU: 2 cores or more (Recommended: 2 cores)
RAM: 4 GB or more (Recommended: 8 GB)
HDD: 4 GB or more (Recommended: 8 GB)
OS: Ubuntu 20.04 or later
Architecture: x64
Dependency: OpenVINO™ Runtime (Version: 2022.3)
Import SDK
Python
C++
Initializing SDK
Step one
First, obtain the machine code for activation and request a license based on the machine code.
Step Two
Next, activate the SDK using the received license.
If activation is successful, the return value will be SDK_SUCCESS. Otherwise, an error value will be returned.
Step Three
After activation, call the initialization function of the SDK.
The first parameter is the path to the model.
If initialization is successful, the return value will be SDK_SUCCESS. Otherwise, an error value will be returned.
Enums and Structure
1. SDK_ERROR
This enumeration represents the return value of the 'initSDK' and 'setActivation' functions.
2. FaceBox
This class represents the output of the face detection function that contains the detected face rectangle, liveness score, and facial angles such as yaw, roll, and pitch.
APIs
1. getMachineCode
First, obtain the machine code for activation and request a license based on the machine code.
2. setActivation
Next, activate the SDK using the received license.
If activation is successful, the return value will be SDK_SUCCESS. Otherwise, an error value will be returned.
3. initSDK
After activation, call the initialization function of the SDK.
The first parameter is the path to the model.
When using Windows, it is necessary to provide the complete file path for the model.
Example:
model_path = "C:\path\to\model"
If initialization is successful, the return value will be SDK_SUCCESS. Otherwise, an error value will be returned.
4. faceDetection
The Face SDK provides a single API for detecting faces, performing liveness detection, determining face orientation (yaw, roll, pitch), assessing face quality, detecting facial occlusion, eye closure, mouth opening, and identifying facial landmarks.
The function can be used as follows:
This function requires 5 parameters.
The first parameter: the byte array of the RGB image buffer.
The second parameter: the width of the image.
The third parameter: the height of the image.
The fourth parameter: the 'FaceBox' array allocated with 'maxFaceCount' for storing the detected faces.
The fifth parameter: the count allocated for the maximum 'FaceBox' objects.
The function returns the count of the detected face.
5. templateExtraction
The SDK provides a function that enables the generation of templates from RGB data. These templates can be used for face verification between two faces.
The function can be used as follows:
This function requires 4 parameters.
The first parameter: the byte array of the RGB image buffer.
The second parameter: the width of the image.
The third parameter: the height of the image.
The fourth parameter: the 'FaceBox' object obtained from the 'faceDetection' function.
If the template extraction is successful, the function will return 0. Otherwise, it will return -1.
6. similarityCalculation
The 'similarityCalculation' function takes a byte array of two templates as a parameter.
It returns the similarity value between the two templates, which can be used to determine the level of likeness between the two individuals.
Default Thresholds
If the similarity value between the two templates is high, it indicates that the faces are the same.
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