ptkis/apron-dataset

Information and scripts for the Apron Dataset

The Apron Dataset

This repository provides all relevant information and utility scripts of the Apron Dataset, which focuses on training and evaluating classification and detection models for airport-apron logistics. A detailed description can be found in the corresponding publication. The image data and annotations are available on request at wilddash.cc/aprondataset.

Annotation Format

Annotations are provided as csv files for each image, defining object instances by a bounding box, label id and the following meta parameters:

• occluded: non-occluded (0), occluded (1)
• atmosphere: clear (0), light rain (1), heavy rain (2), fog (3), snow (4)
• lighting: sunny (0), diffuse (1), artificial (2)
• timeofday: day (0), twilight (1), night (2)
• degradation: low (0), high (1)

The specifications of label ids, mappings and visualization colors are defined in datasets.py.

Dataset Variants

The provided dataset contains fine-grained annotations for 43 categories (ApronFine). Use map_dataset.py to map them to arbitrary target datasets. Mappings of the default variants ApronTop and ApronCoarse are provided.

Visualization

Use visualize_annotations.py to overlay annotations as colored bounding boxes on all images in a given directory.

Licence

The Apron Dataset is released to academic and non-academic entities for non-commercial purposes such as academic research, teaching, scientific publications or personal experimentation (LICENCE).

Citing

If you use the dataset for your research, please use the following BibTeX entry:

@InProceedings{Steininger_2022_ACCV,
    author    = {Steininger, Daniel and Kriegler, Andreas and Pointner, Wolfgang and Widhalm, Verena and Simon, Julia and Zendel, Oliver},
    title     = {Towards Scene Understanding for Autonomous Operations on Airport Aprons},
    booktitle = {Proceedings of the Asian Conference on Computer Vision (ACCV) Workshops},
    month     = {December},
    year      = {2022},
    pages     = {147-163}
}