We propose an use of UAV images and videos to automatically recognize and count animals in extensive areas.
Four computer vision models are currently in this repository:
- Two models for cow recognition from UAV images in nadir position.
- Two models for sheep recognition from UAV videos.
An application script using the sheep detection model is also available for counting sheep in the video.
More details on models section.
The repository folders are structured as follow:
- data: some example videos and images to use application scripts. You can find on Zenodo others sheep video and cow images that you could download and add to data repository to test models and application scripts.
- models: models developed for animals detection.
- appplication: application scripts using sheep models to count animals.
- platform.json: organized information about the models.
The models developed are the following:
The model has been trained with YOLOv8 and is capable of detecting cow at a height of 100 meters from large images (resolution > 3000x4000 px).
The model has been trained with YOLOv8 and is able to detect cows from large images divided into several small images (resolution = 640x640 px).
The model has been trained with YOLOv8 and is able to detect sheep at a height of 5 to 10 meters.
The model has been trained with YOLOv8 and is able to detect sheep at a height of 5 to 10 meters. The dataset used to train the model is different from the previous one.
The script uses one of the sheep detection models, then tracks and counts sheep crossing a field on the video.
- Louise Helary - Institut de l'Elevage (IDELE) - Louise Helary
This project is funded by the European Union, grant ID 101060643.
