This repository contains code for a face recognition system using YoloV8 for face detection and FaceNet for face recognition. YoloV8 efficiently detects faces in images, while FaceNet accurately matches and recognizes the detected faces by generating unique embeddings.
This project integrates YoloV8, a state-of-the-art object detection model, with FaceNet, a robust face recognition model. The system first uses YoloV8 to detect faces in an image or video. Once faces are detected, FaceNet generates embeddings for each face, which are then used to recognize and match faces against a database of known faces. This approach combines the speed of YoloV8 with the high accuracy of FaceNet, making it suitable for real-time face recognition applications.
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Clone the repository:
git clone https://github.com/todap/Face-Recognition-using-YoloV8-and-FaceNet.git cd Face-Recognition-using-YoloV8-and-FaceNet -
Create and activate a virtual environment (optional but recommended):
python3 -m venv venv source venv/bin/activate # On Windows use `venv\Scripts\activate`
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Install the required packages:
pip install -r requirements.txt
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Generate Face Embeddings:
python generate_face_embeddings.py
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Run Face Recognition:
python face_recognition.py
Dont forget to add your paths to directory