Luxand FaceSDK – Sample Applications
FaceSDK is distributed with the following sample applications:
1. Live Recognition
This application receives video from a camera, allows tagging any subject with a name, and then display the name (recognizing the subject). The application utilizes Tracker API. The iOS/Android versions are published in the Apple AppStore and in Google Play (“Luxand Face Recognition” application). Try this sample online: Live Recognition
Source code is available on:
- Microsoft C# 2010+
- iOS (Objective-C)
- iOS (Swift)
- Android (Android Studio)
- Embracadero RAD Studio 12+
- C++/GTK 3.0+ (CMake 3.20+)
- Microsoft Visual C++ 2010+
- Microsoft Visual Basic .NET 2010+
- Java (NetBeans)
- WebAssembly (Wasm)
2. Face Tracking
This application receives video from a webcam and highlights all detected faces with rectangles. The application utilizes Tracker API.
Source code is available on:
- Microsoft C# 2010+
- Embracadero RAD Studio 12+
- Microsoft Visual C++ 2017+
- Microsoft Visual Basic .NET 2010+
- Java (NetBeans)
3. Lookalikes
This application allows the user to create a database of faces and run a search for the best matches (the most similar face from the database is shown). To run the Microsoft SQL example, you need to attach the database (located in the DB folder of the sample) to the Microsoft SQL Server.
Source code is available on:
- Microsoft Visual C++ 2017+
- Microsoft Visual C++ 2017+ (with SQLite)
- Microsoft C# 2010+
- Microsoft C# 2010+ (with MS SQL)
- Java (NetBeans)
4. Live Facial Features
This application tracks users’ facial features in real time using a web camera. The coordinates of facial features are smoothed by Tracker API to prevent jitter.
Source code is available on:
- Microsoft C# 2010+
- Embracadero RAD Studio 12+
- Java (NetBeans)
- Microsoft Visual C++ 2017+
- iOS (Objective-C)
- Android (Android Studio)
- Microsoft Visual Basic .NET 2010+
- WebAssembly (Wasm)
5. Age Gender Expression
Using Tracker API, this application recognizes the gender, age, and facial expression (smile, eyes open/closed) of a subject looking into a webcam.
Source code is available on:
- Microsoft C# 2010+
- Embracadero RAD Studio 12+
- Java (NetBeans)
- Microsoft Visual C++ 2017+
- iOS (Swift)
- Android (Android Studio)
- Microsoft Visual Basic .NET 2010+
6. Facial Features
This application opens a photo, detects a face in a photo (only one face, the one that can be detected best), detects facial features and draws a frame around the detected face and detected features.
Source code is available on:
- Microsoft C# 2010+
- Embracadero RAD Studio 12+
- Java (NetBeans)
- Microsoft Visual C++ 2017+
- iOS (Objective-C)
- Android (Android Studio)
- Microsoft Visual Basic .NET 2010+
- WebAssembly (Wasm)
7. IP Camera
This application opens an IP camera (allowing the user to specify its address, user name and password), displays the image from the camera and tracks faces. The application utilizes Tracker API.
Source code is available on:
- Microsoft C# 2010+
- Embracadero RAD Studio 12+
- Java (NetBeans)
- Microsoft Visual C++ 2017+
- Microsoft Visual Basic .NET 2010+
8. Portrait
This application is for the command line. The application receives a picture, detects a face and, if the face is found, crops it and saves it to a file.
Source code is available on:
- C++ (Microsoft Visual C++ 2010+)
9. Thermal
This application loads a thermal face detection model and allows you to open a grayscale thermal image (which you may have received from a thermal camera), detect faces on the image and draw frames around the detected faces.
Source code is available on:
- Microsoft C# 2010+
- Microsoft Visual C++ 2017+
- iOS (Objective-C)
- Android (Android Studio)
10. Active Liveness
This application asks a subject looking into a camera to rotate their head and smile in a certain way to detect liveness. The active liveness detection helps prevent spoofing attacks with photos or videos by requiring user interaction. Try this sample online: Active Liveness
Source code is available on:
- Microsoft C# 2010+
- Microsoft Visual C++ 2017+
- iOS (Swift)
- Android (Android Studio)
- Java (NetBeans)
- WebAssembly (Wasm)
11. Passive Liveness
This application automatically detects the liveness of a subject looking into a camera (without any assistance from the subject). Uses AI-based analysis to detect spoofing attempts without requiring user actions.
Source code is available on:
- Microsoft C# 2010+
- Microsoft Visual C++ 2017+
- iOS (Swift)
- Android (Android Studio)
- Java (NetBeans)
- Microsoft Visual Basic .NET 2010+
12. IBeta Liveness
This sample demonstrates IBeta-compliant liveness detection that analyzes faces to determine if they are real or presentation attacks (photo, video, mask, etc.). The sample includes desktop implementations for Windows and Linux, mobile implementations for iOS and Android, and advanced implementations supporting Flutter, React Native, and Python.
Desktop:
- Windows (Microsoft Visual C++ 2017+, Microsoft C# 2010+)
- Linux (C++, GTK 3.0+)
Mobile:
- iOS (Swift)
- Android (Android Studio)
Advanced:
- Python
- Flutter
- React Native
13. Advanced - Python
This sample provides comprehensive Python implementations demonstrating various FaceSDK capabilities. The sample includes multiple Python scripts for active liveness, passive liveness, facial features detection, live recognition, lookalikes search, portrait cropping, thermal image processing, and tracker memory management. The Python wrapper allows dynamic linking with .dll/.so/.dylib and provides cross-platform support for Windows, Linux (x86, ARM), and macOS.
Source code is available on:
- Python 3.x (Windows 32/64-bit)
- Python 3.x (Linux 32/64-bit, ARM 32/64-bit)
- Python 3.x (macOS x86_64)
Included Python scripts:
- ActiveLiveness.py - Active liveness detection with user interaction.
- PassiveLiveness.py - Automatic passive liveness detection.
- FacialFeatures.py - Facial feature detection in static images (Windows only, uses GDI+).
- LiveFacialFeatures.py - Real-time facial features from camera (Windows only).
- LiveFacialFeatures_tk.py - Cross-platform real-time facial features using Tkinter.
- LiveRecognition.py - Real-time face recognition from camera (Windows only).
- LiveRecognition_tk.py - Cross-platform face recognition using Tkinter.
- Lookalikes.py - Find similar faces in a database.
- Portrait.py - Command-line face detection and cropping.
- Thermal.py - Thermal image face detection.
- trackerMemoryTool.py - Tracker memory management utility.