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README.md

@@ -26,4 +26,33 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- object-detection
+size_categories:
+- 10K<n<100K
 ---
+# Grapevine Bunch Detection
+
+This dataset provides real-world RGB images of grape bunches in vineyard fields located in Vairão, Portugal. Images were captured using a handheld smartphone in natural agricultural field conditions, offering diverse perspectives of grape clusters under typical vineyard environments. It serves as a practical resource for developing and evaluating object detection models in precision agriculture applications. The dataset contains 10,010 images with 11,672 bounding box annotations across 1 category.
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+The original train/test/val split has been preserved in the `split` column.
+
+## Citation
+
+```bibtex
+@article{pinheiro2023deep,
+  title={Deep Learning YOLO-Based Solution for Grape Bunch Detection and Assessment of Biophysical Lesions},
+  author={Pinheiro, Isabel and Moreira, Germano and Queirós da Silva, Daniel and Magalhães, Sandro and Valente, António and Moura Oliveira, Paulo and Cunha, Mário and Santos, Filipe},
+  journal={Agronomy},
+  volume={13},
+  pages={1120},
+  year={2023},
+  publisher={MDPI}
+}
+```
+
+
+*This dataset was reformatted from its original format to match HuggingFace standards.*