Face Detection System

Face Detection System – Project Description

This project is a smart Face Detection System developed using Python and OpenCV. The main objective of this system is to detect and recognize human faces efficiently using computer vision techniques.

Initially, the user enters basic details such as Name, Age, and Address. After that, the Generate Dataset module captures multiple images of the user's face through a webcam. These images are stored as a dataset and are used for training the model.

In the next step, the Train Classifier module processes the collected dataset and trains the model using machine learning algorithms. This training enables the system to learn facial features and improve recognition accuracy.

Once the model is trained, the Detect Face feature is used to identify faces in real-time through the camera. The system compares the detected face with the trained dataset and recognizes the person if a match is found; otherwise, it labels the face as unknown.

Additionally, the system includes features like an Admin Dashboard for managing data and a Delete Data option to remove stored records when needed.

Overall, the system follows a complete workflow:
Data Input → Dataset Generation → Model Training → Face Detection

This project can be effectively used in applications such as security systems, attendance tracking, and surveillance systems.