Create README.md

README.md

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+---
+configs:
+- config_name: default
+  default: true
+  features:
+  - name: image
+    dtype: image
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': Anthracnose
+          '1': Bacterial-Spot
+          '2': Downy-Mildew
+          '3': Healthy-Leaf
+          '4': Pest-Damage
+license: cc-by-4.0
+task_categories:
+- image-classification
+size_categories:
+- 1K<n<10K
+---
+
+# IDDMSLD Spinach Leaf Disease Classification
+
+A dataset for disease classification of spinach leaves. The dataset contains 3,006 images across 5 classes: Anthracnose, Bacterial-Spot, Downy-Mildew, Healthy-Leaf, Pest-Damage.  
+Images per class:
+- Anthracnose: 102
+- Bacterial-Spot: 752
+- Downy-Mildew: 240
+- Healthy-Leaf: 1,399
+- Pest-Damage: 513
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+## Citation
+
+```bibtex
+@article{sayeem2025iddmsld,
+  title={IDDMSLD: An image dataset for detecting Malabar spinach leaf diseases},
+  author={Sayeem, Adnan Rahman and Omi, Jannatul Ferdous and Hasan, Mehedi and Mojumdar, Mayen Uddin and Chakraborty, Narayan Ranjan},
+  journal={Data in Brief},
+  volume={58},
+  pages={111293},
+  year={2025},
+  publisher={Elsevier}
+}
+```
+
+Sayeem , Adnan Rahman; Omi  , Jannatul Ferdous; Hasan , Mehedi; Mojumdar, Mayen Uddin  (2024), “Malabar Spinach Disease Detection Dataset”, Mendeley Data, V2, doi: 10.17632/sy69db2nz5.2