Project-AgML/MangoClassify-12_variety_classification

1---2dataset_info:3  features:4  - name: image5    dtype: image6  - name: label7    dtype:8      class_label:9        names:10          '0': Amrapali11          '1': Banana12          '2': Bari 413          '3': Fazli14          '4': GobindoBhog15          '5': GopalBhog16          '6': Harivanga17          '7': Himsagar18          '8': Khrishapat19          '9': Langra20          '10': RaniBhog21          '11': Sundari22  splits:23  - name: train24    num_bytes: 1785550385525    num_examples: 390026  download_size: 1851685766727  dataset_size: 1785550385528configs:29- config_name: default30  data_files:31  - split: train32    path: data/train-*33license: cc-by-4.034task_categories:35- image-classification36size_categories:37- 1K<n<10K38---39 40# MangoClassify 12 Variety Classification41 42A dataset for variety classification of common mangoes. The dataset contains 3,900 images across 12 classes:  43Images per class:44- Amrapali: 60045- Banana: 21246- Bari 4: 24047- Fazli: 12048- GobindoBhog: 4149- GopalBhog: 40650- Harivanga: 57551- Himsagar: 50252- Khrishapat: 38053- Langra: 50654- RaniBhog: 9255- Sundari: 22656 57This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.58 59## Citation60 61```bibtex62@article{rahman2025mangoclassify,63  title={MangoClassify-12: A high-resolution image dataset of twelve indigenous Bangladeshi mango cultivars},64  author={Rahman, Md Sajedur and Nahin, Md Mahfuz Ahmed and Rahman, Md Mahbubur and Rani, Mollika and Islam, Md Ashraful and Bashir, Al and Shafkat, Ahmad and Mallik, Bijon and Majeed, Yaqoob},65  journal={Data in Brief},66  pages={112037},67  year={2025},68  publisher={Elsevier}69}70```71 72Md. Sajedur Rahman, Md. Mahfuz Ahmed Nahin, Mollika Rani, and MD Ashraful Islam. (2025). MangoClassify-12: Native Mango Dataset from BD [Dataset]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/12460544