Datasets:
File size: 1,598 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Bad
'1': Good
'2': Mixed
- name: crop
dtype:
class_label:
names:
'0': Apple
'1': Banana
'2': Guava
'3': Lemon
'4': Lime
'5': Orange
'6': Pomegranate
splits:
- name: train
num_bytes: 4009003647
num_examples: 19526
download_size: 3291544075
dataset_size: 4009003647
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- 10K<n<100K
---
# Fruitnet Quality Classification
A dataset for image classification of Fruitnet Quality Classification. The dataset contains 19,526 images across 3 classes: Bad, Good, Mixed.
Images per class:
- Bad: 6,788
- Good: 11,664
- Mixed: 1,074
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{meshram2022fruitnet,
title={FruitNet: Indian fruits image dataset with quality for machine learning applications},
author={Meshram, Vishal and Patil, Kailas},
journal={Data in Brief},
volume={40},
pages={107686},
year={2022},
publisher={Elsevier}
}
```
PATIL, Kailas; MESHRAM, Vishal (2022), “FruitNet: Indian Fruits Dataset with quality (Good, Bad & Mixed quality)”, Mendeley Data, V3, doi: 10.17632/b6fftwbr2v.3
*This dataset was reformatted from its original format to match HuggingFace standards.* |