Face-Mask-Detection

Why we included this project

Face mask detection is a solid entry point for computer vision, and this repository covers the route from training to deployment. A MobileNetV2 classifier trained on masked and unmasked face photos works with a Caffe-based face detector to label masks in still images, live webcam feeds, and a Streamlit interface. The code is organized as a clear pipeline: a training script, separate image and video detection scripts, and a Raspberry Pi setup for running the detector on low-cost hardware. That structure makes it a practical template for adapting a transfer-learning classifier to other visual inspection jobs, not just mask checks. Teams prototyping safety or occupancy monitoring systems will find the flow easier to follow than most research-oriented detection repos.