Face Recognition, Face Liveness Detection, Face Anti-Spoofing, Face Detection, Face Landmarks, Face Compare, Face Matching, Face Pose, Face Expression, Face Attributes, Face Templates Extraction, Face Landmarks

Open Source Face Recognition SDK
The world's first completely free and open-source face recognition SDK for Windows and Linux from Faceplugin
π Overview
The Open Source Face Recognition SDK by Faceplugin is a powerful, privacy-focused solution for integrating face recognition capabilities into your applications. Built with deep learning models, this SDK provides high-accuracy face detection and recognition while ensuring complete data privacy through on-premise processing.
β¨ Key Features
- π 100% On-Premise: All processing happens locally - no data leaves your device
- π― High Accuracy: Powered by state-of-the-art deep learning models
- β‘ Real-Time Processing: Fast face detection and recognition capabilities
- π§ Easy Integration: Simple Python APIs for seamless development
- π Cross-Platform: Compatible with Windows and Linux systems
- π± GPU Optional: Works efficiently on CPU-only systems
- π Completely Free: Open source with no licensing fees
π― Current Capabilities
- Face detection and bounding box extraction
- Facial landmark detection
- Feature embedding generation
- Face similarity comparison
- Support for multiple image formats (JPG, PNG, etc.)
π οΈ Installation
Prerequisites
- Python 3.9 or higher
- Anaconda (recommended for dependency management)
- Windows or Linux operating system
Setup Instructions
Install Anaconda (if not already installed)
# Download from: https://www.anaconda.com/products/distributionCreate and activate conda environment
conda create -n facesdk python=3.9 conda activate facesdkInstall dependencies
pip install -r requirements.txtTest the installation
python run.py
π Quick Start
Basic Usage
from face_recognition_sdk import FaceRecognition
# Initialize the SDK
face_sdk = FaceRecognition()
# Process an image
image_path = "path/to/your/image.jpg"
face_info = face_sdk.GetImageInfo(image_path, faceMaxCount=10)
# Compare two faces
similarity = face_sdk.get_similarity(feature1, feature2)
Example: Face Comparison
# Compare two images
image1 = "test/1.jpg"
image2 = "test/2.png"
# Get face information from both images
faces1 = face_sdk.GetImageInfo(image1, faceMaxCount=1)
faces2 = face_sdk.GetImageInfo(image2, faceMaxCount=1)
if faces1 and faces2:
# Compare the first face from each image
similarity = face_sdk.get_similarity(faces1[0]['embedding'], faces2[0]['embedding'])
print(f"Similarity: {similarity}%")
# Check if it's the same person (threshold = 75)
is_same_person = similarity >= 75
print(f"Same person: {is_same_person}")
π§ API Reference
Core Functions
GetImageInfo(image_path, faceMaxCount)
Extracts face information from an image.
Parameters:
image_path(str): Path to the input imagefaceMaxCount(int): Maximum number of faces to detect
Returns:
- List of dictionaries containing:
bbox: Face bounding box coordinateslandmarks: Facial landmark pointsembedding: Feature embedding vector
get_similarity(feature1, feature2)
Compares two face feature embeddings.
Parameters:
feature1(array): First face embeddingfeature2(array): Second face embedding
Returns:
- Similarity score (0-100), where higher values indicate greater similarity
Configuration
- Default Threshold: 75 (for determining if two faces belong to the same person)
- Supported Formats: JPG, PNG, BMP, TIFF
- Face Detection: Automatic detection of multiple faces per image
π― Use Cases
This SDK is ideal for various applications:
π Security & Authentication
- Access Control Systems: Secure entry points with face recognition
- User Authentication: Biometric login for applications
- Surveillance: Real-time monitoring and alerting
π₯ Business Applications
- Time & Attendance: Automated employee check-in/check-out
- Customer Analytics: Retail customer tracking and analytics
- Smart Offices: Automated visitor management
π± Mobile & IoT
- Smart Devices: Integration with IoT devices
- Mobile Apps: Face recognition in mobile applications
- Augmented Reality: AR applications with facial recognition
π’ More Biometric SDKs from Faceplugin
This project is developed by Faceplugin, a provider of on-premise biometric and identity verification SDKs.
If you need capabilities beyond this open-source SDK, explore Faceplugin's commercial SDKs for:
| Solution | Description |
|---|---|
| π€ Face Recognition | Face recognition, verification, identification, attributes, and biometric authentication |
| π‘οΈ Face Liveness Detection | Detect presentation attacks during face verification and authentication |
| π ID Document Recognition | OCR, MRZ, barcode recognition, and document classification |
| π ID Document Liveness Detection | Detect presentation attacks involving identity documents |
Explore our complete suite of biometric and identity verification solutions, including face recognition, face liveness detection, ID document recognition and ID document liveness detection SDKs.
Face Recognition SDKs
- Face Recognition + Liveness β Android Β· Java, Kotlin
- Face Recognition + Liveness β iOS Β· Objective-C, Swift
- Face Recognition + Liveness β Flutter
- Face Recognition + Liveness β React Native
- Face Recognition + Liveness β Ionic Cordova
- Face Recognition + Liveness β Ionic Capacitor
- Face Recognition + Liveness β Docker for Linux
- Face Recognition + Liveness β Windows
- Face Recognition + Liveness β .NET MAUI
- Face Recognition + Liveness β .NET WPF
ID Document Recognition SDKs
- ID Document Recognition β Android Β· Java, Kotlin
- ID Document Recognition β iOS Β· Objective-C, Swift
- ID Document Recognition β Flutter
- ID Document Recognition β React Native
- ID Document Recognition β Ionic Cordova
- ID Document Recognition β Ionic Capacitor
- ID Document Recognition β Docker for Linux
- ID Document Recognition β Windows
ID Document Liveness Detection SDK
π€ Support & Contact
While there are many ways to support this project, starring βοΈ this GitHub repository is one of the simplest and most impactful. It increases discoverability and helps the project reach a wider audience. Thank you for your support π
π Get in Touch
- Email: info@faceplugin.com
- WhatsApp: +1 (469) 278-4822
- Telegram: @FacePluginSupport
- Website: faceplugin.com