Datasets:
File size: 1,495 Bytes
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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.* |