Drone images and their annotations of grazing cows

This dataset is part of the European H2020 project ICAERUS regarding the livestock monitoring use case. More information here: https://icaerus.eu/ By making available 1385 images and 4941 bounding boxes of cows, this dataset is a major contribution for public and research stakeholders to develop cow detection and counting models. This dataset encompasses the following data: - Farm_name: name of the farm were the images were collected (Mauron, Derval, Jalogny or Other_farms) -----JPGImages: a directory were the images are stored (1385 images, , RGB images taken from 60 ot 100m of altitude; images size of 4000*3000 or 5280*3956, images taken with DJI MAVIC3 E or DJI MAVIC3T). -------------DJI_YYYYMMDDHHMM_XXX: a directory by flight containing the images of a unique flight, with the date (YYYYMMDD), the hour in UTC+2 (HHMM), and XXX representing a mission number -----PASCAL_VOC1.1: a directory with the annotations of cows at the PASCAL format (4941 bouding boxes of cows) -------------DJI_YYYYMMDDHHMM_XXX: a directory by flight containing the annotations, one annotation file referred to an unique image and have the same name except the extension -----YOLO_V1: a directory with the annotations of cows at the YOLO format (4941 bouding boxes of cows) -------------DJI_YYYYMMDDHHMM_XXX: a directory by flight containing the annotations, one annotation file referred to an unique image and have the same name except the extension Nadir images were collected between June 2023 and March 2024 at a constant altitude of 100m or 60m during flight planned with DJI Pilot 2 regarding the take-off position or manually at a precise relative altitude.  When they were used, flight planned were designed to cover the entire pasture. It is why, in some flight there is a strong imbalance between images with “cattle” and image with “no cattle”. The file conditions_summary.xlsx detailed the following information for each flight: Relative altitude, Number of images, number of images containing cows, number of cow bounding boxes, Weather, Date, Drone used, Drone camera used, Image size. The Aerial images contain many .exif methadata (drone, camera, altitude etc.). These data can be used to train different deep learning models such as Yolo models or to validate pretrained models to detect cows on pastures. Other versions of this dataset will be available later in 2024. The authors of the dataset are opened to any collaboration regarding animal counting models. If you are interested in sheep counting based on drones’ images and AI, find other available data here: https://doi.org/10.5281/zenodo.10400302 For more information, please contact: adrien.lebreton@idele.fr