Update README.md

README.md

@@ -22,4 +22,36 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- image-classification
+size_categories:
+- 1K<n<10K
 ---
+
+# Mint Leaf Classification
+
+A dataset for health classification of mint leaves. The dataset contains 5,384 images across 4 classes: Dried, Fresh, Spoiled, Sunlight.  
+Images per class:
+- Dried: 1,881
+- Fresh: 1,773
+- Spoiled: 1,669
+- Sunlight: 61
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+## Citation
+
+```bibtex
+@article{jadhav2023mint,
+  title={Mint leaves: dried, fresh, and spoiled dataset for condition analysis and machine learning applications},
+  author={Jadhav, Rohini and Suryawanshi, Yogesh and Bedmutha, Yashashree and Patil, Kailas and Chumchu, Prawit},
+  journal={Data in Brief},
+  volume={51},
+  pages={109717},
+  year={2023},
+  publisher={Elsevier}
+}
+```
+
+Bedmutha, Yashashree; Suryawanshi, Yogesh; PATIL, Kailas; chumchu, prawit (2023), “Pudina Leaf Dataset: Freshness Analysis”, Mendeley Data, V1, doi: 10.17632/nvbpydc3fs.1