Update README.md

README.md

@@ -34,4 +34,45 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- image-classification
+size_categories:
+- 10K<n<100K
 ---
+# Maize Tomato Weed Classification
+
+A dataset for classification of weeds and crops in maize and tomato fields. The dataset contains 55,828 images across 12 classes:  
+Images per class:
+- atriplex: 2,459
+- chenopodium: 3,375
+- convolvulus: 2,302
+- cyperus: 3,215
+- datura: 1,271
+- lolium: 1,063
+- maize: 25,273
+- portulaca: 2,052
+- salsola: 2,409
+- solanum: 4,084
+- sorghum: 1,703
+- tomato: 6,622
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+## Citation
+
+```bibtex
+@article{mesias2025drone,
+  title={Drone imagery dataset for early-season weed classification in maize and tomato crops},
+  author={Mes{\'\i}as-Ruiz, Gustavo A and Pe{\~n}a, Jos{\'e} M and de Castro, Ana I and Dorado, Jos{\'e}},
+  journal={Data in Brief},
+  volume={58},
+  pages={111203},
+  year={2025},
+  publisher={Elsevier}
+}
+```
+
+Mesías-Ruiz, G. A., Peña Barragán, J. M., Castro, A. I. D., & Dorado, J. (2024). DIWEED: Drone Imagery dataset for early-season WEED classification [Data set]. DIGITAL.CSIC. http://doi.org/10.20350/DIGITALCSIC/16559
+
+*This dataset was reformatted from its original format to match HuggingFace standards.*