| --- |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| license: cc-by-4.0 |
| task_categories: |
| - object-detection |
| size_categories: |
| - n<1K |
| dataset_info: |
| features: |
| - name: image |
| dtype: image |
| - name: objects |
| struct: |
| - name: bbox |
| list: |
| list: float64 |
| - name: categories |
| list: int64 |
| splits: |
| - name: train |
| num_bytes: 207085842 |
| num_examples: 746 |
| download_size: 207063224 |
| dataset_size: 207085842 |
| --- |
| |
| # 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 |
