ultralytics/xview-yolov3

xView 2018 Object Detection Challenge: YOLOv3 Training and Inference.

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Emerging

This project helps remote sensing analysts and researchers train a specialized object detection model to identify various objects within satellite imagery. You feed it raw xView satellite images, and it outputs a trained model that can pinpoint and classify objects with bounding boxes. This is designed for participants in challenges like xView who need to detect objects in complex aerial views.

324 stars. No commits in the last 6 months.

Use this if you need to train a YOLOv3 model for high-accuracy object detection in satellite imagery, especially for tasks involving the xView dataset.

Not ideal if you're looking for a general-purpose object detection solution for standard images, or if you don't have access to the xView satellite imagery data.

satellite-imagery-analysis remote-sensing geospatial-intelligence object-detection aerial-reconnaissance
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 21 / 25

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Stars

324

Forks

58

Language

Python

License

AGPL-3.0

Last pushed

Sep 21, 2025

Commits (30d)

0

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