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FaceRecognition-C#

Overview

This repository demonstrates an advanced face recognition technology by implementing face comparison based on face feature extraction and face matching algorithm.
It includes capabilities for testing face recognition in 1:N matching scenarios.

In this repo, we integrated KBY-AI's face recognition solution into Windows Server SDK.
We can customize the SDK to align with your specific requirements.

◾FaceSDK(Server) Details

Face Liveness Detection	🔽 Face Recognition
Face Detection	Face Detection
Face Liveness Detection	Face Recognition(Face Matching or Face Comparison)
Pose Estimation	Pose Estimation
68 points Face Landmark Detection	68 points Face Landmark Detection
Face Quality Calculation	Face Occlusion Detection
Face Occlusion Detection	Face Occlusion Detection
Eye Closure Detection	Eye Closure Detection
Mouth Opening Check	Mouth Opening Check

◾FaceSDK(Server) Product List

No.	Repository	SDK Details
1	Face Liveness Detection - Linux	Face Livness Detection
2	Face Liveness Detection - Windows	Face Livness Detection
3	Face Recognition - Linux	Face Recognition
4	Face Recognition - Windows	Face Recognition
➡️	Face Recognition - C#	Face Recognition

To get Face SDK(mobile), please visit products here:

Screenshots

SDK License

This project uses KBY-AI's Face Recognition Server SDK, which requires a license per machine.

• To request the license, please provide us with the machine code obtained from the getMachineCode function.

• Ensure you copy the license.txt file to the bin/x64/Debug folder, as shown in the image below:

Please contact us:

🧙Email: contact@kby-ai.com
🧙Telegram: @kbyai
🧙WhatsApp: +19092802609
🧙Skype: live:.cid.66e2522354b1049b
🧙Facebook: https://www.facebook.com/KBYAI

About SDK

1. Initializing the SDK

• Step One

  First, obtain the machine code for activation and request a license based on the machine code.

  textBoxMachineCode.Text = FaceSDK.GetMachineCode();

• Step Two

  Next, activate the SDK using the received license.

  int ret = FaceSDK.SetActivation(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.

  ret = FaceSDK.InitSDK("data");

  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.

2. Enum and Structure

• SDK_ERROR

  This enumeration represents the return value of the initSDK and setActivation functions.

  Feature	Value	Name
  Successful activation or initialization	0	SDK_SUCCESS
  License key error	-1	SDK_LICENSE_KEY_ERROR
  AppID error (Not used in Server SDK)	-2	SDK_LICENSE_APPID_ERROR
  License expiration	-3	SDK_LICENSE_EXPIRED
  Not activated	-4	SDK_NO_ACTIVATED
  Failed to initialize SDK	-5	SDK_INIT_ERROR

• FaceBox

  This structure represents the output of the face detection function.

  Feature	Type	Name
  Face rectangle	int	x1, y1, x2, y2
  Face angles (-45 ~ 45)	float	yaw, roll, pitch
  Face quality (0 ~ 1)	float	face_quality
  Face luminance (0 ~ 255)	float	face_luminance
  Eye distance (pixels)	float	eye_dist
  Eye closure (0 ~ 1)	float	left_eye_closed, right_eye_closed
  Face occlusion (0 ~ 1)	float	face_occlusion
  Mouth opening (0 ~ 1)	float	mouth_opened
  68 points facial landmark	float [68 * 2]	landmarks_68
  Face templates	unsigned char [2048]	templates

  68 points facial landmark

  

3. APIs

Please refer to FaceSDK.cs, where all APIs are implemented.

• Face Detection

  The Face SDK provides a single API for detecting faces, 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:

  FaceBox[] faceBoxes = new FaceBox[10];
  int faceCount = FaceSDK.FaceDetection(pixels, imgBmp.Width, imgBmp.Height, faceBoxes, 10);

  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.

• Create Template

  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:

  FaceSDK.TemplateExtraction(pixels, imgBmp.Width, imgBmp.Height, ref faceBoxes[0]);

  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.

• Calculation similiarity

  The FaceSDK.SimilarityCalculation function takes a byte array of two templates as a parameter.

  float similarity = FaceSDK.SimilarityCalculation(faceBoxes[0].templates, personList[i].Templates);

  It returns the similarity value between the two templates, which can be used to determine the level of likeness between the two individuals.

4. Thresholds

The default thresholds are as the following below:

FaceRecognition-CSharp-.NET/FaceRecognition/Form1.cs

Lines 25 to 26 in 0b55245

	float identifyThreshold = 0.7f;