Real-time Facemask Detection using CNN & Deep Learning

This project focuses on building a facemask detection system using CNN and deep learning techniques. The model was trained using TensorFlow and Keras, achieving high accuracy for real-time predictions. It takes input from images or live video streams to classify if a facemask is present.

Features

• Convolutional Neural Networks (CNN): For extracting essential image features.
• Real-time Detection: Operates on live video streams or image inputs.
• Accuracy: Reliable detection with optimized model architecture.
• Deep Learning Frameworks: TensorFlow and Keras were used for training and testing.

Model Training and Validation Accuracy and Loss Graph

Output

Requirements

• Python 3.x
• TensorFlow
• Keras
• OpenCV
• Numpy
• Matplotlib