This repository contains the code for a project for face recognition, aiming to improve the accuracy and efficiency of automated facial identification in various applications.
The goal is to streamline facial identification processes, making them more efficient and accessible for real-world applications.
The dataset used in this project comprises a diverse set of facial images, including variations in lighting, pose, and expression. These images are crucial for training models to handle different real-world scenarios effectively.
- Deep Learning Models: ResNet
- Preprocessing: Face alignment, normalization, and data augmentation