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Aerial Solar Panels Computer Vision Project

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This project labels solar panels collected via a DJI Mavic Air 2 flying over Rancho Santa Fe, California in August 2022. Both rooftop and backyard solar panels are labeled. It was used as the basis for the Using Computer Vision with Drones for Georeferencing blog post and the open source DJI aerial georeferencing project.

53 images labeled with 267 polygons were used to train a computer vision model to detect solar panels from above. It's a demonstration of collecting and annotating data from a drone video and using that to train a machine learning model.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite this Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ aerial-solar-panels_dataset,
    title = { Aerial Solar Panels Dataset },
    type = { Open Source Dataset },
    author = { Brad Dwyer },
    howpublished = { \url{ https://universe.roboflow.com/brad-dwyer/aerial-solar-panels } },
    url = { https://universe.roboflow.com/brad-dwyer/aerial-solar-panels },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { jan },
    note = { visited on 2023-02-01 },
}

Source

Brad Dwyer

Last Updated

21 days ago

Project Type

Object Detection

Subject

solar-panels