Overview

This product is a portfolio style dashboard that showcases facial detection and recognition using deep learning technology. It provides a user interface for interacting with the backend and utilizes pre-trained models such as MTCNN for face detection and VGG Face for facial feature extraction. The dashboard allows users to upload query images, which are then processed for face detection and feature extraction. The similarity between the labeled faces and the query faces is calculated using the cosine distance metric, and the best match is displayed with a bounding box and name.

Features

User-friendly dashboard for face detection and recognition
Pre-trained MTCNN model for face detection
Pre-trained VGG Face model for facial feature extraction
Query image processing for face detection and feature extraction
Similarity calculation using cosine distance metric
Display of best match with bounding box and name

Summary

The facial recognition dashboard is a portfolio project that demonstrates the use of deep learning models for face detection and recognition. It provides a user-friendly interface for interacting with the backend and showcases the capabilities of pre-trained models like MTCNN and VGG Face. With easy installation and usage instructions, this project can be easily modified for different purposes.

Animikhaich

Facial Recognition Dashboard