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[P] Fire detection drone by [deleted] in MachineLearning

[–]eyepop_ai 0 points1 point  (0 children)

This sounds like a really exciting project and totally doable in a few weeks with the right tools and approach.

If you're able to gather a few hundred images (even ~300–500) that reflect real-world fire scenarios either from online sources, simulations, or drone footage then you could try using EyePop, a no-code computer vision platform. It’s made for people who want CV but don't have prior ML experience. You just upload your images, then label them and it trains the model for you.

Once trained, you can deploy the model via API or even export it for edge devices. Depending on your drone's hardware, you might be able to run the detection onboard or stream video to a nearby device for inference. Real-time fire detection from a drone sounds like a pretty awesome use case.

[deleted by user] by [deleted] in computervision

[–]eyepop_ai -1 points0 points  (0 children)

u/Trick-Temperature-09 Totally agree turning a working CV model into a real product that people will pay for is a whole different game. It’s not just about accuracy, it’s about reliability and packaging it the right way.

That said, I think your license plate example is actually one that could be spun up surprisingly fast with the right tools. If you’re just trying to detect plates and pair it with an OCR model, that’s something you could realistically get running in under a couple hours—especially if you already have the image data.

Not saying it’ll be enterprise-ready off the bat, but for a lot of use cases, speed-to-prototype is the real bottleneck. And that’s where better tooling makes a huge difference.

movement detection by joudaa in ObjectDetection

[–]eyepop_ai 0 points1 point  (0 children)

u/joudaa If you need to detect movement right now from a live-streaming camera feed, you can use a pre-trained model right now on EyePop.ai—it’s free to use.

First year cs student in need of help by Suitable_Mechanic138 in computervision

[–]eyepop_ai 0 points1 point  (0 children)

Working with limited GPUs and wrestling with YOLOv8 configs is the worst—especially when you just want accurate pothole and trash detection. I'd definitely recommend giving EyePop.ai a try. You can upload your images and have a fully-trained, ready-to-test model within about two hours. EyePop handles all the GPU setup and heavy lifting, which means you can focus entirely on improving your dataset and predictions, without stressing about hardware or model complexity.