Face-Clustering

Our main goal is to develop a dependable system that allows users to input their image to identify and retrieve all related images from a database. We utilize the dlib library and its face recognition model, combining deep learning and traditional computer vision techniques for highly accurate results. Our system includes face detection, recognition, and image retrieval. It begins by using the face recognition model to identify faces in the input image, then uses facial landmarks and feature embeddings to match them with the database. We conclude by retrieving and presenting all images associated with the recognized individual. Our extensive experiments, which involved various lighting conditions, poses, and facial expressions, validate the system's exceptional accuracy and efficiency, making it suitable for real-world applications. Potential uses include access control, event management, and personal media organization.