SDK de Desarrollo para Terminales Faciales
Publicado 2026-09-11
中SDK de desarrollo Android y proyectos de ejemplo para terminales faciales (series VF10X / VF106): ejemplo de herramientas de prueba VF106 (con lectura de tarjetas, huella y escaneo QR) y ejemplo de SDK de reconocimiento facial (basado en Baidu Face SDK, con detección de vivacidad y comparación 1:N), listos para importar en Android Studio y compilar.
This page provides Android development SDKs and sample projects for Vguang face terminals (VF10X / VF106 series), ready to import into Android Studio for compilation and running, for secondary development and function verification.
VF106 Test Tools Sample Project
A complete terminal function testing app, built with Android Gradle, including the following modules:
- **Card reading (lib-readcard)**: read/write operations for IC cards, CPU cards, M1 cards, etc.;
- **Fingerprint (lib-fingerprint)**: fingerprint collection, matching and storage;
- **QR scanning (lib-zxing)**: 1D/2D barcode reading based on ZXing;
- **Temperature measurement**: includes thermometry UI and documentation;
- **Gradle Wrapper**: project includes gradlew / gradlew.bat, no separate Gradle installation needed.
Suitable for verifying terminal hardware functions, learning module call patterns, and as a base template for secondary development.
Face Recognition SDK Sample Project
A sample project focused on face recognition, based on Baidu Face SDK (com.baidu.idl.face), including:
- **Liveness detection**: RGB liveness and infrared liveness detection;
- **1:N face matching**: face database management and 1:N recognition;
- **Face collection**: face image collection and quality detection;
- **License files**: assets directory contains license.ini, license_t509.ini, license_yijia.ini and other authorization configs;
- **Signature file**: app/signature/facesdk-library.keystore for SDK authorization verification.
Suitable for Android app development requiring face recognition capabilities; refer to core classes such as FaceSDKManager and HomeActivity in the sample code.
Usage
1. Download and unzip the corresponding package;
2. Open Android Studio, select "Open an existing project", choose the unzipped project root directory;
3. Wait for Gradle sync to complete (first sync may need to download dependencies);
4. Connect a face terminal device (enable USB debugging), click Run to install and run;
5. Modify sample code or integrate into your own project as needed.
Notes
- The face recognition SDK requires correct license files and signature, otherwise functionality may be limited;
- License files in the sample project are for development and testing only; for commercial use, contact us for formal authorization;
- If you encounter build issues, check Android Studio version and Gradle plugin version compatibility.