Open Source Face Recognition SDK

The world's first completely free and open-source face recognition SDK for Windows and Linux

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.

• 🔒 100% On-Premise: All processing happens locally - no data leaves your device
• 🎯 High Accuracy: Powered by state-of-the-art deep learning models
• ⚡ Real-Time Processing: Fast face detection and recognition capabilities
• 🔧 Easy Integration: Simple Python APIs for seamless development
• 🌐 Cross-Platform: Compatible with Windows and Linux systems
• 📱 GPU Optional: Works efficiently on CPU-only systems
• 🆓 Completely Free: Open source with no licensing fees

• Face detection and bounding box extraction
• Facial landmark detection
• Feature embedding generation
• Face similarity comparison
• Support for multiple image formats (JPG, PNG, etc.)

• Python 3.9 or higher
• Anaconda (recommended for dependency management)
• Windows or Linux operating system

1. Install Anaconda (if not already installed)

   # Download from: https://www.anaconda.com/products/distribution

2. Create and activate conda environment

   conda create -n facesdk python=3.9
   conda activate facesdk

3. Install dependencies

   pip install -r requirements.txt

4. Test the installation

   python run.py

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)

# 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}")

Extracts face information from an image.

Parameters:

• image_path (str): Path to the input image
• faceMaxCount (int): Maximum number of faces to detect

Returns:

• List of dictionaries containing:
  • bbox: Face bounding box coordinates
  • landmarks: Facial landmark points
  • embedding: Feature embedding vector

Compares two face feature embeddings.

Parameters:

• feature1 (array): First face embedding
• feature2 (array): Second face embedding

Returns:

• Similarity score (0-100), where higher values indicate greater similarity

• 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

This SDK is ideal for various applications:

• Access Control Systems: Secure entry points with face recognition
• User Authentication: Biometric login for applications
• Surveillance: Real-time monitoring and alerting

• Time & Attendance: Automated employee check-in/check-out
• Customer Analytics: Retail customer tracking and analytics
• Smart Offices: Automated visitor management

• Smart Devices: Integration with IoT devices
• Mobile Apps: Face recognition in mobile applications
• Augmented Reality: AR applications with facial recognition

For higher accuracy requirements and enterprise features, contact us for our commercial SDK offerings:

• Enhanced Accuracy Models: Superior recognition performance
• Liveness Detection: Anti-spoofing capabilities
• Multi-Platform Support: Android, iOS, Web, and more
• Technical Support: Professional assistance and documentation

Contact us at: info@faceplugin.com

Explore our complete suite of face recognition and biometric solutions:

• Android (Java/Kotlin)
• iOS (Objective-C/Swift)
• React Native
• Flutter

• JavaScript
• React
• Vue.js
• .NET MAUI
• .NET WPF

• Liveness Detection
• Palm Recognition
• ID Card Recognition
• Document Liveness Detection

• Email: info@faceplugin.com
• Telegram: @faceplugin
• WhatsApp: +1 (938) 202-5720
• Website: faceplugin.com