This project is a Face Mask Detection system using Convolutional Neural Networks (CNNs). It classifies images as either "with mask" or "without mask," leveraging real-time video feeds. The system was built using Python, TensorFlow/Keras, and OpenCV, and it was trained on a dataset from Kaggle. This tool is particularly relevant for ensuring public safety during the COVID-19 pandemic.

• Real-time Detection: Identify mask compliance in live video feeds.
• High Accuracy: Achieved with CNN architectures.
• Easy to Use: Can be run on Google Colab or Jupyter Notebook.

The dataset is sourced from Kaggle. It includes images of people with and without face masks.