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---
configs:
- config_name: default
default: true
features:
- name: image
dtype: image
- name: objects
sequence:
- name: bbox
list: float32
- name: categories
dtype: int32
license: cc-by-4.0
task_categories:
- object-detection
size_categories:
- n<1K
---
# GYMNSA Pear Rust Detection
A dataset for object detection of pear rust on leaevs. The dataset contains 746 images with 16,251 bounding box annotations across 1 category.
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{mass2025annotated,
title={Annotated image dataset with different stages of European pear rust for UAV-based automated symptom detection in orchards},
author={Ma{\ss}, Virginia and Alirezazadeh, Pendar and Seidl-Schulz, Johannes and Leipnitz, Matthias and Fritzsche, Eric and Ibraheem, Rasheed Ali Adam and Geyer, Martin and Pflanz, Michael and Reim, Stefanie},
journal={Data in Brief},
volume={58},
pages={111271},
year={2025},
publisher={Elsevier}
}
```
Maß, Virginia; Alirezazadeh, Pendar; Seidl-Schulz, Johannes; Leipnitz, Matthias; Fritzsche, Eric; Ibraheem, Rasheed Ali Adam; Geyer, Martin; Pflanz, Michael; Reim, Stefanie (2024), “GYMNSA dataset”, Mendeley Data, V1, doi: 10.17632/44kjgc4gkc.1