Script for Face Detection and Recognition

This repository contains a Python script that utilizes OpenCV, RetinaFace, and face_recognition libraries to perform sophisticated face detection and recognition tasks. It's designed to efficiently process a large set of images, detect faces, and recognize individuals based on a target image. Here are the key features:

Face Detection: Leverages the RetinaFace model for accurate face detection in images. Face Recognition: Utilizes the face_recognition library to identify specific individuals by comparing detected faces against a target image. Image Normalization: Applies histogram equalization to the luminance channel of images to enhance recognition accuracy. Visual Feedback: Draws bounding boxes around detected faces, color-coded to distinguish between recognized and unrecognized faces. Concurrent Processing: Employs concurrent processing techniques to handle large image datasets efficiently. Customizable: Allows users to specify input and output directories, target face images, and toggle the face recognition feature. This script is ideal for research projects requiring face detection and recognition capabilities.