Update README.md

README.md

@@ -30,4 +30,43 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- image-classification
+size_categories:
+- 1K<n<10K
 ---
+
+# MangoClassify 12 Variety Classification
+
+A dataset for variety classification of common mangoes. The dataset contains 3,900 images across 12 classes:  
+Images per class:
+- Amrapali: 600
+- Banana: 212
+- Bari 4: 240
+- Fazli: 120
+- GobindoBhog: 41
+- GopalBhog: 406
+- Harivanga: 575
+- Himsagar: 502
+- Khrishapat: 380
+- Langra: 506
+- RaniBhog: 92
+- Sundari: 226
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+## Citation
+
+```bibtex
+@article{rahman2025mangoclassify,
+  title={MangoClassify-12: A high-resolution image dataset of twelve indigenous Bangladeshi mango cultivars},
+  author={Rahman, Md Sajedur and Nahin, Md Mahfuz Ahmed and Rahman, Md Mahbubur and Rani, Mollika and Islam, Md Ashraful and Bashir, Al and Shafkat, Ahmad and Mallik, Bijon and Majeed, Yaqoob},
+  journal={Data in Brief},
+  pages={112037},
+  year={2025},
+  publisher={Elsevier}
+}
+```
+
+Md. Sajedur Rahman, Md. Mahfuz Ahmed Nahin, Mollika Rani, and MD Ashraful Islam. (2025). MangoClassify-12: Native Mango Dataset from BD [Dataset]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/12460544