Processed datasets for CLIBD

In this data repo we provide the pre-processed data used in the paper CLIBD: Bridging Vision and Genomics for Biodiversity Monitoring at Scale You can find more information in our github repo.

Dataset Sources

The data we used to train and test our models include BIOSCAN-1M and BIOSCAN-5M. In addition, to perform Bayesian Zero Shot Learning, we also employed the INSECT dataset that was introduced in Fine-grained ZSL with DNA as Side Information.

Download the datasets

To clone the repo:

GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/bioscan-ml/bioscan-clibd

For BIOSCAN-1M:

git lfs pull --include="data/BIOSCAN_1M/**"
python merge_bioscan_1m.py

For BIOSCAN-5M:

git lfs pull --include="data/BIOSCAN_5M/**"
python merge_bioscan_5m.py

For INSECT:

git lfs pull --include="data/INSECT/**"

Acknowledgement

We would like to express our gratitude for the use of the INSECT dataset, which played a pivotal role in the completion of our experiments. Additionally, we acknowledge the use and modification of code from the Fine-Grained-ZSL-with-DNA repository, which facilitated part of our experimental work. The contributions of these resources have been invaluable to our project, and we appreciate the efforts of all developers and researchers involved.

This reseach was supported by the Government of Canada’s New Frontiers in Research Fund (NFRF) [NFRFT-2020-00073], Canada CIFAR AI Chair grants, and the Pioneer Centre for AI (DNRF grant number P1). This research was also enabled in part by support provided by the Digital Research Alliance of Canada (alliancecan.ca).

For more information, please check our paper.