{"id":25905347,"url":"https://github.com/nour-zayed/face-recogntion","last_synced_at":"2026-05-05T13:41:14.992Z","repository":{"id":279866475,"uuid":"940260492","full_name":"Nour-Zayed/Face-Recogntion","owner":"Nour-Zayed","description":"This project implements a real-time face recognition system using Computer Vision and Deep Learning. The system is capable of detecting and recognizing faces in real-time using a webcam, as well as from images and video files. 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The system is capable of detecting and recognizing faces in real-time using a webcam, as well as from images and video files. The project leverages OpenCV, dlib, and the face_recognition library to accurately detect, encode, and identify faces.\n\n## 🔹 Features\n\n1️⃣ **Real-Time Face Detection \u0026 Recognition**\n\nUses HOG (Histogram of Oriented Gradients) and CNN-based face detection for high accuracy.\n\nDetects faces in real-time using a webcam.\n\nRecognizes known faces by comparing them with stored encodings.\n\nCan process multiple faces simultaneously in a frame.\n\n2️⃣ **Face Encoding \u0026 Comparison**\n\nEach face is converted into a 128-dimensional numerical encoding.\n\nUses Euclidean distance to compare detected faces with stored encodings.\n\nSupports adding and removing faces from the database dynamically.\n\n3️⃣ **High Accuracy \u0026 Performance**\n\nUtilizes dlib’s deep learning-based face recognition model trained on a large dataset.\n\nWorks under different lighting conditions, facial angles, and expressions.\n\nSupports face landmark detection for better facial analysis.\n\n4️⃣ **OpenCV-Based Visualization**\n\nDraws bounding boxes and labels detected faces in real-time.\n\nDisplays the name of recognized individuals on the screen.\n\nIncludes a confidence score to indicate recognition accuracy.\n\n5️⃣ **Image \u0026 Video Processing Support**\n\nWorks with static images to detect and recognize faces.\n\nCan process pre-recorded videos for face recognition.\n\nSupports batch processing for analyzing multiple images at once.\n\n6️⃣ **Face Data Storage \u0026 Management**\n\nStores face encodings in a database or local file system.\n\nAllows adding new faces dynamically through a script or GUI.\n\nCan be integrated with cloud storage for centralized face management.\n\n7️⃣ **Scalability \u0026 Extensibility**\n\nCan be extended to support:\n\nEmotion recognition.\n\nAge \u0026 gender detection.\n\nMultiple cameras for large-scale deployments.\n\nIntegration with security systems \u0026 IoT devices.\n\n## 🖥️ How It Works?\n\nFace Detection: The system captures a video stream or loads an image.\n\nFace Landmark Detection: Key facial features (eyes, nose, mouth, chin) are detected.\n\nFace Encoding: Each detected face is converted into a 128-dimensional vector.\n\nFace Matching: The encoded face is compared with stored encodings to identify individuals.\n\nLabel Display: If a match is found, the person’s name is displayed; otherwise, it is marked as Unknown.\n\n## 📌 Applications\n\n🔹 Security \u0026 Access Control – Face-based authentication for restricted access.\n\n🔹 Attendance Systems – Automates attendance tracking in schools, offices, and events.\n\n🔹 Smart Surveillance – Integrates with CCTV cameras for real-time monitoring.\n\n🔹 Human-Computer Interaction – Enables hands-free user interaction in AI-driven applications.\n\n🔹 Retail \u0026 Customer Insights – Identifies customers and provides personalized experiences.\n\n\n🔧 **Future Enhancements**\n\n✔️ Improve accuracy with CNN-based deep learning models.\n\n✔️ Optimize performance for large-scale datasets with multi-threading.\n\n✔️ Add support for face masking detection for COVID-19 compliance.\n\n✔️ Implement age, gender, and emotion recognition using deep learning.\n\n✔️ Integrate with cloud storage for storing and retrieving face data.\n\n✔️ Develop a GUI-based application for easier user interaction.\n\n![Screenshot (142)](https://github.com/user-attachments/assets/61826556-f5b5-4270-8459-6f6186914486)\n\n\n![image](https://github.com/user-attachments/assets/bd97c86f-8ffe-4415-81a2-93e8db5d9d38)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnour-zayed%2Fface-recogntion","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnour-zayed%2Fface-recogntion","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnour-zayed%2Fface-recogntion/lists"}