.png & .txt

Doing manual annotations can sometimes be resource heavy, depending on the amount of data. This dataset was designed to created to use in conjunction with a semi-automatic annotation method based on linear interpolation. The dataset contains 799 images, where 679 lies in the trainingset, and the rest lies in the validationset. The images are taken from 6 different video streams, where a remote controlled wheel loader approaches a miniature dump truck at different angles. 4 of the videos are used in the trainingset. The labels can contain up to 5 classes which are:

0 - front wheel  1 - middle wheel 2 - back wheel 3 - tipping body 4 - cap

This dataset was used to train a YOLOv3 model, hence the labels will be written in the YOLO labeling format.