Wellington Camera Traps

Overview

This data set contains 270,450 images from 187 camera locations in Wellington, New Zealand. The cameras (Bushnell 119537, 119476, and 119436) recorded sequences of three images when triggered. Each sequence was labelled by citizen scientists and/or professional ecologists from Victoria University of Wellington into 17 classes: 15 animal categories (for example, the most common labels are bird, cat, and hedgehog), empty, and unclassifiable. Approximately 17% of images are labeled as empty. Images within each sequence share the same species label (even though the animal may not have been recorded in all three images).

Citation, license, and contact information

If you use this data set, please cite the associated manuscript:

Victor Anton, Stephen Hartley, Andre Geldenhuis, Heiko U Wittmer 2018. Monitoring the mammalian fauna of urban areas using remote cameras and citizen science. Journal of Urban Ecology; Volume 4, Issue 1.

This data set is released under the Community Data License Agreement (permissive variant).

For questions about this data set, contact Victor Anton.

Data format

Annotations are provided in .csv format as well as in COCO Camera Traps .json format. In the .csv format, empty images are referred to as “nothinghere”; in the .json format, empty images are referred to as “empty” for consistency with other data sets on this site.

For information about mapping this dataset’s categories to a common taxonomy, see this page.

Downloading the data

Images are available in the following cloud storage folders:

• gs://public-datasets-lila/wellington-unzipped/images (GCP)
• s3://us-west-2.opendata.source.coop/agentmorris/lila-wildlife/wellington-unzipped/images (AWS)
• https://lilawildlife.blob.core.windows.net/lila-wildlife/wellington-unzipped/images (Azure)

A link to a zipfile is also provided below, but – whether you want the whole data set, a specific folder, or a subset of the data (e.g. images for one species) – we recommend checking out our guidelines for accessing images without using giant zipfiles.

Download links:

Posted by Dan Morris.