Published January 3, 2025 | Version v1
Dataset Open

Aerial videos and images of goats (for computer vision purpose)

  • 1. ROR icon Institut de l'Elevage

Description

This dataset is part of the European H2020 project ICAERUS, specifically focused on the livestock monitoring use case. For more information, visit the project website: https://icaerus.eu.

Objective

Counting sheep and goats is a significant challenge for farmers managing flocks with hundreds of animals. Our objective is to develop a computer vision-based methodology to count sheep and goats as they pass through a corridor or gate. This approach utilizes low-altitude aerial videos (<15 m) recorded by drones.

Progress and Enhancements

Our ongoing efforts include:

To improve detection models like YOLO, we are enriching the dataset with:

  • Images of Non-White Small Ruminants: Current models struggle with detecting sheep that are not white due to their low frequency in flocks and thus datasets. By including images of brown and dark-colored goats, we aim to enhance model performance.
  • Environmental Diversity: Additional images and videos are being collected under varying conditions:
    • Backgrounds: Concrete, asphalt, grass, dirt, etc.
    • Lighting Conditions: Cloudy, sunny, and shaded (e.g., barn shadows).

 

Data set description

This dataset encompasses the following data:

  • Pradel: a directory encompassing images and videos from a goat farm in France, Ardeche.
    •     Videos: a directory encompassing short drone videos (8 videos ; Drone height: ~ 15 m ; Drone gimbal angle: NADIR and Oblique, Resolution: 3840x2160, FPS: 30, brown goats, various backgrounds). The videos are orignal or were cut.
    •        Images_from_videos: images extracted from the videos at 5 images per seconde (1606 images)
    •       Other_images: other images (8 of images ;Drone height: ~ 15m ; Drone gimbal angle: NADIR Resolution: 5280x3956)
  • Ferme nord: a directory encompassing images and videos from a goat farm in France, nord.
    •       Videos: a directory encompassing short drone videos (2 videos ; Drone height: ~ 15-30 m ; Drone gimbal angle: Oblique, Resolution: 3840x2160, FPS: 30, Dark brown goats, grass backgrounds). The videos were cut.
    •     Images_from_videos: images extracted from the videos at 5 images per seconde (442 images)      
  •      Summaries of images and videos

Future Work

We are actively annotating the collected images and plan to share them upon completion. These enhancements aim to improve detection accuracy for small ruminants in diverse scenarios.

Collaboration and Contact

We welcome collaborations on this topic. For inquiries or further information, please contact:
Adrien Lebreton
Email: adrien.lebreton@idele.fr

 

Files

Goat dataset.zip

Files (4.8 GB)

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md5:b3b6b4704cf6c8692f87e9ba98571412
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Additional details

Related works

Has part
Model: https://github.com/ICAERUS-EU/UC3_Livestock_Monitoring (Other)
Is supplement to
Dataset: 10.5281/zenodo.12094355 (DOI)

Funding

European Commission
ICAERUS - Innovations and Capacity building in Agricultural Environmental and Rural Uav Services 101060643