tinh2044/YOLO12-UnderWater

YOLOv12 Underwater Object Detection is an open-source suite for underwater object detection, built on YOLOv12. It offers an end-to-end pipeline with GPU-accelerated training, customizable data augmentations, real-time inference via Gradio, and support for model export (ONNX & PyTorch).

14
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Experimental

This project helps marine biologists, environmental monitors, and operators of autonomous underwater vehicles automatically identify objects in underwater images and videos. It takes raw or low-quality underwater footage and outputs precise detections of marine life, vehicles, or pollution, even in challenging conditions like poor visibility or color distortion. Anyone working with visual data from underwater environments will find this tool useful for automating identification tasks.

No commits in the last 6 months.

Use this if you need to accurately detect and classify various objects in underwater images or video streams, improving the reliability of marine research or autonomous operations.

Not ideal if your object detection needs are for terrestrial environments or if you lack access to GPU hardware for training and real-time inference.

marine-biology environmental-monitoring underwater-robotics oceanography aquaculture
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 7 / 25
Community 0 / 25

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Language

Python

License

Last pushed

Jun 17, 2025

Commits (30d)

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