A wildlife conservation unmanned aerial vehicle (UAV) dataset derived from Mao et al.'s dataset WAID: Wildlife Aerial Images from Drone as introduced via their publication: "WAID: A Large-Scale Dataset for Wildlife Detection with Drones".
This subset was trimmed down to 8,000 images while the train set set accomodates for 2,000 and the validation set is 4,000 images strong featuring a 2,000 image strong test split. This dataset was used for benchmarking YOLOv8 vs YOLOv9 in extremely data-sparse conditions.
Note that the labels are in YOLO format, meaning the label files can be read as: class index, x_center, y_center, width, height.