Face Mask Detection using CNN (MobileNetV2)

This project implements a Convolutional Neural Network (CNN) to detect face masks in images.
It uses transfer learning with MobileNetV2, data augmentation, and Grad-CAM visualization for interpretability.

• Detects with_mask vs without_mask classes.
• Achieved ~99% accuracy on the test set.
• Provides Grad-CAM heatmaps to visualize model attention.
• Includes pre-trained model (.h5) and sample images for testing.