Create README.md

README.md

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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