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': Class_A
+          '1': Class_B
+          '2': Defect
+  - name: crop_type
+    dtype: string
+license: cc-by-4.0
+task_categories:
+- image-classification
+size_categories:
+- 1K<n<10K
+---
+
+# Banana Guava Quality Classification
+
+A dataset for quality classification of bananas and guavas. The dataset contains 1,748 images across 3 classes: Class_A, Class_B, Defect.  
+Images per class:
+- Class_A: 671
+- Class_B: 469
+- Defect: 608
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+## Citation
+
+```bibtex
+@article{kumari2024banana,
+  title={Banana and Guava dataset for machine learning and deep learning-based quality classification},
+  author={Kumari, Abiban and Singh, Jaswinder},
+  journal={Data in Brief},
+  volume={57},
+  pages={111025},
+  year={2024},
+  publisher={Elsevier}
+}
+```
+
+KUMARI, ABIBAN; Singh, Jaswinder (2024), “Fruits (Banana and Guava) datasets for non-destructive quality classifications”, Mendeley Data, V2, doi: 10.17632/56td5w4wz2.2