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': Bean
+          '1': Bitter melon
+          '2': Brinjal
+          '3': Cucumber
+          '4': Garlic
+          '5': Green Chili
+          '6': Ladies finger
+          '7': Onion
+          '8': Pointed gourd
+          '9': Potato
+          '10': Radish
+          '11': Tomato
+license: cc-by-4.0
+task_categories:
+- image-classification
+size_categories:
+- 1K<n<10K
+---
+
+# Vegetable Classification Banglades
+
+A dataset for image classification of various types of vegetables. The dataset contains 4,319 images across 12 classes: Bean, Bitter melon, Brinjal, Cucumber, Garlic, Green Chili, Ladies finger, Onion, Pointed gourd, Potato, Radish, Tomato.
+Images per class:
+- Bean: 454
+- Bitter melon: 306
+- Brinjal: 373
+- Cucumber: 342
+- Garlic: 349
+- Green Chili: 497
+- Ladies finger: 308
+- Onion: 357
+- Pointed gourd: 329
+- Potato: 365
+- Radish: 310
+- Tomato: 329
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+## Citation
+
+```bibtex
+@article{ahmed2025banglaveg,
+  title={BanglaVeg: A curated vegetable image dataset from Bangladesh for precision agriculture},
+  author={Ahmed, Md Jobayer and Saha, Ratu and Dutta, Arpon Kishore and Mojumdar, Mayen Uddin and Chakraborty, Narayan Ranjan},
+  journal={Data in Brief},
+  volume={59},
+  pages={111441},
+  year={2025},
+  publisher={Elsevier}
+}
+```
+
+Ahmed, Md Jobayer; Saha, Ratu; Dutta , Arpon Kishore ; Mojumdar, Mayen Uddin  (2025), “Vegetable Image Dataset for Classification Models: A Bangladeshi Perspective”, Mendeley Data, V4, doi: 10.17632/b9rvg4f2st.4