Update README.md

README.md

@@ -24,4 +24,40 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-nc-4.0
+task_categories:
+- image-classification
+size_categories:
+- 1K<n<10K
 ---
+
+# Tea Leaf Disease Classification
+
+A dataset for disease classification of tea leaves. The dataset contains 5,867 images across 6 classes: algal_spot, brown_blight, gray_blight, healthy, helopeltis, red_spot.  
+Images per class:
+- algal_spot: 1,000
+- brown_blight: 867
+- gray_blight: 1,000
+- healthy: 1,000
+- helopeltis: 1,000
+- red_spot: 1,000
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+## Citation
+
+```bibtex
+@article{BALASUNDARAM2025103784,
+title = {Tea leaf disease detection using segment anything model and deep convolutional neural networks},
+journal = {Results in Engineering},
+volume = {25},
+pages = {103784},
+year = {2025},
+issn = {2590-1230},
+doi = {https://doi.org/10.1016/j.rineng.2024.103784},
+url = {https://www.sciencedirect.com/science/article/pii/S2590123024020279},
+author = {Ananthakrishnan Balasundaram and Prem Sundaresan and Aryan Bhavsar and Mishti Mattu and Muthu Subash Kavitha and Ayesha Shaik}
+}
+```
+
+https://www.kaggle.com/datasets/saikatdatta1994/tea-leaf-disease