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README.md

@@ -20,4 +20,34 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- image-classification
+size_categories:
+- n<1K
 ---
+# Luffa Quality Classification
+
+This dataset provides real RGB images of luffa plants captured in a field environment in Bangladesh using a handheld smartphone. Collected during October 2023, the images depict natural variations in luffa quality relevant to agricultural disease classification. It serves as a practical resource for developing computer vision models in agricultural quality assessment under real-world field conditions. The dataset contains 343 images across 2 classes: Faulty, Fresh.  
+Images per class:
+- Faulty: 160
+- Fresh: 183
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+## Citation
+
+```bibtex
+@article{sheikh2024luffafolio,
+  title={LuffaFolio: A Multidimensional Image Dataset of Smooth Luffa},
+  author={Sheikh, Md Ripon and Islam, Md. Masudul and Himel, Galib Muhammad Shahriar},
+  journal={Data in Brief},
+  volume={53},
+  pages={110149},
+  year={2024},
+  publisher={Elsevier}
+}
+```
+
+
+*This dataset was reformatted from its original format to match HuggingFace standards.*