---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Amrapali
          '1': Bari-4
          '2': Bari-7
          '3': Fazlee
          '4': Harivanga
          '5': Kanchon Langra
          '6': Katimon
          '7': Langra
          '8': Mollika
          '9': Nilambori
  splits:
  - name: train
    num_bytes: 3170873222
    num_examples: 2012
  download_size: 3269490389
  dataset_size: 3170873222
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
---
# Mangifera2012 Variety Classification

A dataset for variety classification of mangoes. The dataset contains 2,012 images across 10 classes:  
Images per class:
- Amrapali: 252
- Bari-4: 235
- Bari-7: 176
- Fazlee: 156
- Harivanga: 202
- Kanchon Langra: 210
- Katimon: 163
- Langra: 202
- Mollika: 221
- Nilambori: 195

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

## Citation

```bibtex
@article{bharati2025comprehensive,
  title={A comprehensive image dataset of Bangladeshi mango variety},
  author={Bharati, Rup Kumar and Islam, Md Masudul and Sheikh, Md Ripon and Himel, Galib Muhammad Shahriar},
  journal={Data in Brief},
  volume={60},
  pages={111560},
  year={2025},
  publisher={Elsevier}
}
```

Sheikh, Md Ripon; Islam, Md Masudul; Himel, Galib Muhammad Shahriar (2024), “Mangifera2012: An Image Dataset of Various Bangladeshi Mangoes”, Mendeley Data, V1, doi: 10.17632/w5jg84txj8.1

*This dataset was reformatted from its original format to match HuggingFace standards.*