Forest Fire Classifier is a tiny web app for detecting fire, smoke, fire+smoke, or no-fire in images. Upload a forest photo and get a prediction in ~500 ms. v2 is rebuilt with Next.js, TypeScript, and TensorFlow.js running server-side for consistent performance. Images are processed in memory only – nothing is stored. It’s open source, privacy-first, and built to showcase how far “college project → real product” can go.
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Maker
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Hey Product Hunt 👋
Forest Fire Classifier started life as a scrappy college project. v2 is the glow-up: a proper web app that can detect fire, smoke, fire+smoke, or no fire from images.
What it does:
• Upload a forest image → get class + confidence scores in ~500 ms
• All inference runs on the server with TensorFlow.js
• Images are processed in memory only – nothing is stored
Why I built it:
I wanted to see how far I could take a Teachable Machine model and turn it into something “portfolio-grade”: proper UX, a11y, rate-limited API, docs, and a clean developer experience for future versions.
Who it’s for:
• Devs curious about ML in production-ish web apps
• Learners looking for a real, inspectable Next.js + TS + TFJS project
• Anyone who enjoys seeing old college projects glow up
It’s completely free & open source – feel free to fork it, break it, or use the architecture as a reference for your own ML side project.
I’d love feedback on:
• The UX (especially the classifier flow)
• API design & documentation
• Anything that feels confusing or slow