Face Recognition

This project focuses on building a robust face recognition system using deep learning techniques. The main objective is to identify and verify individuals in images by analyzing and comparing facial features.

Designed by Freepik

Frameworks and Libraries

Project Architecture

The project is structured around a convolutional neural network (CNN) that is trained to extract and compare facial features from images. The architecture includes layers for convolution, pooling, and fully connected neural networks that together enable accurate face recognition.

Key Features

• Preprocessing of images for face detection and alignment
• Feature extraction using a pre-trained CNN.
• Face verification and identification

Usage

Clone the repository:

git clone https://github.com/yourusername/Face_Recognition_Project.git

Navigate to the project directory:

cd Face_Recognition_Project

Install the required dependencies:

pip install -r requirements.txt

Run the Jupyter Notebook to see the implementation:

jupyter notebook Face_Recognition.ipynb

Results

The face recognition system is capable of accurately identifying and verifying individuals in various images. The performance is demonstrated through a series of tests and visualizations in the provided Jupyter Notebook.