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A face recognition system built using Python and popular computer vision libraries. This project uses machine learning models to detect and recognize human faces in real-time through webcam input.

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Face Recognition

📌 Overview

A face recognition system built using Python and popular computer vision libraries. This project uses machine learning models to detect and recognize human faces in real-time through webcam input.

🛠️ Selected Technologies

1. Python 3.13.3

Used as the main programming language to implement the recognition logic and threading for performance.

Python


2. NumPy

Used for efficient numerical computations, especially for handling face embeddings and calculating distances between vectors.

NumPy


3. OpenCV

Used for image and video capture, as well as for rendering bounding boxes and text overlays on detected faces.

OpenCV


4. Dlib

Utilized for face detection, facial landmarks prediction, and face recognition using pretrained models.

Dlib


⚙️ Installation and Setup

1. Clone the Repository

Clone this repository to your local environment:

git clone https://github.com/Mulekotd/face-recognition.git
cd face-recognition

2. Create and Activate a Virtual Environment

python -m venv env
.\env\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Run the Project

python main.py

🤝 Feedback and Contributions

We welcome feedback, suggestions, and contributions from the community! If you have ideas for improvements or encounter any issues, please open an issue on GitHub.

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A face recognition system built using Python and popular computer vision libraries. This project uses machine learning models to detect and recognize human faces in real-time through webcam input.

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