Unidrone is super-simple and 100%-free set of YOLO-based neural networks to do detection with drones!
- ✨ YOLOV8-based – the AI models shared are all based on the populat YOLO architecture and are, as such, very easy to integrate into products and deploy on all sorts of inference hardware including at the edge
- ⚡ Open weights – all the models are shared as .pt files and can be used as starting points for training / finetuning the networks on your own data!
- 💡 Angle-agnostic – the training data for these models is a new set which looks to merge WALDO and NANO, two other drone-centric AI systems that I maintain, but reducing the output size for more mainstream use-cases and expanding the training-data scope to ensure the models work better at any angle from top-down (nadir imagery) to horizontal (looking forward).
- Clone this repo to get the sample code, and pull the weights from Hugginface at:
See the demo code in this repo to run some examples. To get started you can perform inference on an input mp4 video using:
Please feel free to write a PR if you'd like to add features to the sample code here or want to build a complete deployment pipeline for a specific platform for instance!
MIT License
Copyright (c) 2025 Stephan Sturges
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
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you can reach me at stephan (dot) sturges (at ) google mail (dot) com