---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': Damaged
          '1': Fresh
          '2': Severely Damaged
  - name: crop_type
    dtype: string
  - name: plant_id
    dtype: int64
  splits:
  - name: train
    num_bytes: 10632989700
    num_examples: 4464
  download_size: 10744868382
  dataset_size: 10632989700
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
---
# Bruised Vegetable Classification

A dataset for classification of Bruised Vegetable Classification. The dataset contains 4,464 images across 3 classes.

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

## Citation

```bibtex
@article{samanta2025nature,
  title={Nature's best vs. bruised: A veggie edibility evaluation database},
  author={Samanta, Bidisha and Banerjee, Sriparna and Das, Ranadhir and Chaudhuri, Sheli Sinha and Djemal, Khalifa and Feiz, Amir Ali},
  journal={Data in Brief},
  volume={60},
  pages={111483},
  year={2025},
  publisher={Elsevier}
}
```

Samanta, Bidisha ; Banerjee, Sriparna; Das, Ranadhir; Sinha Chaudhuri, Sheli; Djemal, Khalifa  (2024), “Nature's Best vs. Bruised: A Veggie Evaluation”, Mendeley Data, V2, doi: 10.17632/b2mvj3kjfx.2

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