Welcome to the MiniAiLive!
This repository contains a C++ application that demonstrates face recognition capabilities using computer vision techniques. The demo utilizes OpenCV and dlib libraries for efficient face detection and recognition with 3D passive face liveness detection (face anti-spoofing).
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The SDK utilizes advanced computer vision techniques to detect faces in images or video frames, enabling a wide range of applications.
It can recognize known faces by comparing them with a pre-defined database of individuals.
- It can estimate the age of detected faces.
- It can determine the gender of detected faces.
- It can detect whether a face is from a live person or a static image.
- C++ compiler with C++11 support
- OpenCV (version 4.6.0)
Clone the repository:
git clone https://github.com/MiniAI/MiniAIFaceSDK.git
1. Download the `vcredist_x64.exe`, and `vc_redist.x64.exe` files from the provided link.
2. Double-click the downloaded file to start the installation.
3. Follow the on-screen instructions to complete the installation process.
4. Restart your system if prompted.
For more detailed installation instructions, please refer to the [official Microsoft documentation](https://docs.microsoft.com/en-us/cpp/windows/latest-supported-vc-redistributable).
Run the compiled executable:
./MiniAIFaceDemo.exe
We provide free license to test our SDK according to HWID. You can get the HWID in our SDK application. Follow the on-screen instructions to perform face detection and recognition.
- Face Database: Replace the sample face database with your own set of known faces. Ensure that you provide clear and properly labeled images for accurate recognition.
- Recognition Algorithm: Adjust the recognition algorithm parameters or explore other algorithms provided by dlib to optimize the recognition performance.
Contributions are welcome! If you'd like to contribute to this project, please follow these steps:
1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them with descriptive messages.
4. Push your changes to your forked repository.
5. Submit a pull request to the original repository.
No | Project | Feature |
---|---|---|
1 | FaceRecognition-Linux | 1:1 & 1:N Face Matching |
2 | FaceRecognition-Windows | 1:1 & 1:N Face Matching |
3 | FaceRecognition-Docker | 1:1 & 1:N Face Matching |
4 | FaceRecognition-Android | 1:1 & 1:N Face Matching, 2D & 3D Face Passive LivenessDetection |
5 | FaceRecognition-LivenessDetection-Windows | 1:1 & 1:N Face Matching, 2D & 3D Face Passive LivenessDetection |
6 | FaceLivenessDetection-Linux | 2D & 3D Face Passive LivenessDetection |
7 | FaceLivenessDetection-Windows | 2D & 3D Face Passive LivenessDetection |
8 | FaceLivenessDetection-Docker | 2D & 3D Face Passive LivenessDetection |
9 | FaceLivenessDetection-Android | 2D & 3D Face Passive LivenessDetection |
10 | FaceMatching-Android | 1:1 Face Matching |
11 | FaceMatching-Windows-Demo | 1:1 Face Matching |
12 | FaceAttributes-Android | Face Attributes, Age & Gender Estimation |
13 | ID-DocumentRecognition-Linux | IDCard, Passport, Driver License, Credit, MRZ Recognition |
14 | ID-DocumentRecognition-Windows | IDCard, Passport, Driver License, Credit, MRZ Recognition |
15 | ID-DocumentRecognition-Docker | IDCard, Passport, Driver License, Credit, MRZ Recognition |
16 | ID-DocumentRecognition-Android | IDCard, Passport, Driver License, Credit, MRZ Recognition |
17 | ID-DocumentLivenessDetection-Linux | ID Document LivenessDetection |
18 | ID-DocumentLivenessDetection-Windows | ID Document LivenessDetection |
19 | ID-DocumentLivenessDetection-Docker | ID Document LivenessDetection |
MiniAiLive is a leading AI solutions company specializing in computer vision and machine learning technologies. We provide cutting-edge solutions for various industries, leveraging the power of AI to drive innovation and efficiency.
For any inquiries or questions, please Contact US