Project X #14 ~ Mask Detection with Deep Learning: Build Your Own Image Classifier

Learn how to build an AI-powered mask detection system with deep learning and TensorFlow. Step-by-step guide for image classification in Python.

Ever wonder how those systems work that can tell if someone’s wearing a face mask or not? Like the ones they started using during the pandemic in stores and buildings? Heck, maybe even something like FaceID.

Well, in this month’s Project X, we’re gonna build one from scratch.

Yep, we’re putting together a full face mask detection system using deep learning — the same kind of tech behind things like self-driving cars and facial recognition. Don’t worry if you’re new to this. I’ll walk you through it step by step.

We’ll start by loading the data and getting it cleaned up, then build a model using something called a CNN (that’s just short for Convolutional Neural Network — it’s really good at recognizing images).

After that, we’ll train it, test how well it works, and then run it on some new photos to see what it can do. We’ll be using Tensorflow and OpenCV for a lot of this.

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By the time we’re done, you’ll know how these systems actually work and have your own version up and running — one you can show off, improve, or even use in a real project.

This is the kind of hands-on stuff I love sharing here in Project X — real tools, real code, and real results. Let’s build something cool together.

I’ll link the previous Project X here where we built a Real-Time Weather App is Flet for future reference.

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These projects take a lot of time and resources for me to craft in a way that I can present them and share them for you all.

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Let’s get building out a Convolutional Neural Network!