Trained model for detecting and identifying birds in drone imagery, accompanying:
Wilson, J. P., T. Amano, T. Bregnballe, A. Corregidor-Castro, R. Francis, D. Gallego-García, et al. (2026). Big Bird: A global dataset of birds in drone imagery annotated to species level. Remote Sensing in Ecology and Conservation. https://doi.org/10.1002/rse2.70059
Trained on:
Insert Dataset DOI.
Model Overview
This model performs object detection and fine‑grained classification of birds in aerial drone images. It predicts hierarchical labels including:
Unique label ID
Taxonomic information: class → order → family → genus → species
Traits: age category (chick, juvenile, adult), sex (male, female, monomorphic)
Training Images: high‑resolution drone RGB imagery.
Model Type: Faster RCNN with resnet-101 backbone.
Intended Use
Primary use cases
Automated processing of large drone image collections for ecological surveys
Generating species counts and spatial patterns from aerial surveys
Supporting conservation monitoring and research workflows
Not intended for
Real‑time inference on live video streams
Predicting species not present in the training dataset
Making decisions without ecological validation
Limitations & Ethical Considerations
This model reflects biases in the training data (e.g., species representation, habitat contexts). Users should:
Validate outputs with domain experts
Be cautious of false positives in complex scenes
Understand that model performance may vary with altitude, sensor quality, and lighting
Evaluation
Model performance metrics (precision/recall, mAP, per‑class accuracy, etc.) were reported in Wilson et al. (2026). Users are encouraged to evaluate the model on their own images and share results.
How to Download
You can use the huggingface_hub Python client to download model weights and labels:
Please cite the original paper when using this model:
bibtex
1@article{Wilson2026,
2 title={Big Bird: A global dataset of birds in drone imagery annotated to species level},
3 author={Joshua P. Wilson and Tatsuya Amano and Thomas Bregnballe and Alejandro Corregidor-Castro and Roxane Francis and {Diego Gallego-García} and Jarrod C. Hodgson and Landon R. Jones and {César R. Luque-Fernández} and Dominik Marchowski and John McEvoy and Ann E. McKellar and W. Chris Oosthuizen and Christian Pfeifer and Martin Renner and {José Hernán Sarasola} and {Mateo Sokač} and Roberto Valle and Adam Zbyryt and Richard A. Fuller},
4 journal={Remote Sensing in Ecology and Conservation},
5 year={2026},
6 doi={10.1002/rse2.70059}
7}
