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| Main Authors: | , |
|---|---|
| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.16537441 |
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Table of Contents:
- <p>This dataset enables real-time object detection of sheep, wolves, dogs, wild dog, redfox, fox, coyote, cow and humans for robotic shepherding applications. Built from raw YOLOv5-style sources, it integrates <strong>class balancing</strong>, <strong>video-based diversity</strong>, and <strong>strong augmentations</strong> to enhance robustness. A <strong>recycling strategy</strong> is used for rare classes. Compatible with YOLOv5 to YOLOv12, RT-DETR, and ROS 2 deployments on legged robots, the dataset includes labels, images, statistics, and visualizations, ready for direct use in training detection models for autonomous livestock protection.</p>