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README.md

@@ -46,4 +46,43 @@ configs:
   - split: train
     path: raw/train-*
   default: true
+license: cc-by-4.0
+task_categories:
+- image-classification
+size_categories:
+- 1K<n<10K
 ---
+# Roseleafset Disease Classification
+
+RoseLeafSet is a set of close-up smartphone photos of rose leaves collected in rose nurseries around Savar, Dhaka, Bangladesh, between October 30 and November 6, 2024, labelled into four foliar conditions: black spot, dry leaf, healthy leaf and leaf holes. Images were taken with a Vivo IQOO Z9x phone at 3264 x 2448 pixels. The default raw config holds the 3,113 original photos (class-imbalanced: 1,288 black spot, 324 dry leaf, 818 healthy, 683 leaf holes); the augmented config holds the authors' class-balanced augmented set of 2,500 images per class (10,000 total), derived from contrast-enhanced, padded versions of the originals.  The dataset contains raw and augmented versions.  
+The raw dataset contains 3,113 images.  
+Images per class:
+- Black Spot: 1,288
+- Dry Leaf: 324
+- Healthy Leaf: 818
+- Leaf Holes: 683
+
+The augmented dataset contains 10,000 images.  
+Images per class:
+- Black Spot: 2,500
+- Dry Leaf: 2,500
+- Healthy Leaf: 2,500
+- Leaf Holes: 2,500
+
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+## Citation
+
+```bibtex
+<!-- TODO: add BibTeX citation -->
+```
+
+<!-- TODO: add plain text citation -->
+
+The dataset itself can be cited as:
+
+Jinia, J. T., Rahman, M. S., Mojumdar, M. U., &amp; Bijoy, M. H. I. (2025). *RoseLeafSet: Real-World Leaf Image Dataset for AI-Based Agricultural Solutions* [Dataset]. Mendeley Data. https://doi.org/10.17632/9G668BFHY5.3
+
+
+*This dataset was reformatted from its original format to match HuggingFace standards.*