Datasets:
File size: 2,083 Bytes
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configs:
- config_name: augmented
data_files:
- split: train
path: augmented/train-*
- config_name: raw
data_dir: raw
default: true
license: cc-by-nc-nd-4.0
task_categories:
- image-classification
size_categories:
- 10K<n<100K
dataset_info:
- config_name: augmented
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Formalin-mixed
'1': Fresh
'2': Rotten
- name: fruit
dtype: string
splits:
- name: train
num_bytes: 4662871872
num_examples: 73389
download_size: 4504232734
dataset_size: 4662871872
- config_name: raw
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Formalin-mixed
'1': Fresh
'2': Rotten
- name: fruit
dtype: string
splits:
- name: train
num_bytes: 838669224
num_examples: 10154
download_size: 923365461
dataset_size: 838669224
---
# FruitVision Quality Classification
A dataset for quality classification of apples, bananas, mangoes, grapes, and oranges. The dataset contains raw and augmented versions.
The raw dataset contains 10,154 images.
Images per class:
- Formalin-mixed: 3,176
- Fresh: 3,800
- Rotten: 3,178
The augmented dataset contains 73,389 images.
Images per class:
- Formalin-mixed: 22,228
- Fresh: 30,400
- Rotten: 20,761
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{bijoy2025fruitvision,
title={FruitVision: A benchmark dataset for fresh, rotten, and formalin-mixed fruit detection},
author={Bijoy, Md Hasan Imam and Tasnim, Syeda Zarin and Awsaf, Syed Ali and Hasan, Md Zahid},
journal={Data in Brief},
volume={61},
pages={111752},
year={2025},
publisher={Elsevier}
}
```
Bijoy, Md Hasan Imam; Tasnim, Syeda Zarin; Awsaf, Syed Ali; Hasan, Md Zahid (2025), “FruitVision: A Benchmark Dataset for Fresh, Rotten, and Formalin-mixed Fruit Detection”, Mendeley Data, V2, doi: 10.17632/xkbjx8959c.2 |