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README.md

@@ -24,4 +24,36 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- image-classification
+size_categories:
+- 1K<n<10K
 ---
+# Paddynet Lcc Classification
+
+This dataset features field images of paddy crops collected across multiple locations in Bangladesh during the rice growing season (mid-April to late June). Images were captured using handheld RGB cameras on consumer smartphones (Nokia 3 and Samsung S8) and include a mix of real field observations and synthetic augmentations. The dataset contains 2,785 images across 4 classes: 2, 3, 4, 5.  
+Images per class:
+- 2: 692
+- 3: 1,103
+- 4: 513
+- 5: 477
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+## Citation
+
+```bibtex
+@article{siddique2023paddynet,
+  title={Paddynet: An organized dataset of paddy leaves for a smart fertilizer recommendation system},
+  author={Siddique, Md. Moradul and Islam, Torikul and Tusher, Yeasir Arefin and Ema, Romana Rahman and Adnan, Md. Nasim and Galib, Syed Md.},
+  journal={Data in Brief},
+  volume={50},
+  pages={109516},
+  year={2023},
+  publisher={Elsevier}
+}
+```
+
+
+*This dataset was reformatted from its original format to match HuggingFace standards.*