---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: objects
    struct:
    - name: bbox
      list:
        list: float64
    - name: categories
      list:
        class_label:
          names:
            '0': Flower
            '1': Shoot
            '2': Maybe
            '3': Leaf
  splits:
  - name: train
    num_bytes: 360647800
    num_examples: 1698
  download_size: 392683479
  dataset_size: 360647800
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-4.0
task_categories:
- object-detection
size_categories:
- 1K<n<10K
---
# Erwiam Blight Detection

A dataset for detection of fire blight in an apple orchard. The dataset contains 1,698 images with 15,761 bounding box annotations across 4 categories.

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

## Citation

```bibtex
@article{mass2024annotated,
  title={Annotated image dataset of fire blight symptoms for object 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={56},
  pages={110826},
  year={2024},
  publisher={Elsevier}
}
```

Maß, Virginia; Alirezazadeh, Pendar; Seidl-Schulz, Johannes; Leipnitz, Matthias; Fritzsche, Eric; Ibraheem, Rasheed Ali Adam; Geyer, Martin; Pflanz, Michael; Reim, Stefanie (2024), “ERWIAM dataset”, Mendeley Data, V1, doi: 10.17632/fpmnncmg84.1

*This dataset was reformatted from its original format to match HuggingFace standards.*