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Faceplugin-ltd/Open-Source-Face-Recognition-SDK

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Faceplugin-ltd/Open-Source-Face-Recognition-SDK has 3,149 GitHub stars and 523 forks. GitHot measured +2 stars in 24 hours and +49 in 7 days. Last checked 2026-11-11 17:06 UTC. Last push 2026-10-02.

この数値の測り方

顔認識、顔の生体検知、顔のなりすまし防止、顔検出、顔のランドマーク、顔比較、顔照合、顔の姿勢、顔の表情、顔の属性、顔テンプレートの抽出、顔のランドマーク

できること

  • 🔒 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

計測したスター増加

24時間
+2
7日間
+49
15日間
更新が遅れています
1か月
更新が遅れています

期間ごとの純増数です。期間は重複しており、日別の値ではありません。未計測の値は空欄です。スター数は注目度の指標であり、品質の保証ではありません。

FacePlugin

Open Source Face Recognition SDK

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

Platform Python License Privacy


🚀 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.

✨ Key Features

  • 🔒 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

🎯 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.)

🛠️ Installation

Prerequisites

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

Setup Instructions

  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
    

📖 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}")

🔧 API Reference

Core Functions

GetImageInfo(image_path, faceMaxCount)

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

get_similarity(feature1, feature2)

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

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

🎯 Use Cases

This SDK is ideal for various applications:

🔐 Security & Authentication

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

👥 Business Applications

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

📱 Mobile & IoT

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

🏢 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
👤 Face Recognition Face recognition, verification, identification, attributes, and biometric authentication
🛡️ Face Liveness Detection Detect presentation attacks during face verification and authentication
🆔 ID Document Recognition OCR, MRZ, barcode recognition, and document classification
🔐 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

ID Document Recognition SDKs

ID Document Liveness Detection SDK


🤝 Support & Contact

While there are many ways to support this project, starring ⭐️ 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 🙏

📞 Get in Touch


Made with ❤️ by Faceplugin

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