Datasets:
File size: 1,539 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': grade-1
'1': grade-2
'2': grade-3
- name: quality
dtype:
class_label:
names:
'0': quality-1
'1': quality-2
'2': quality-3
'3': quality-4
splits:
- name: train
num_bytes: 129205249
num_examples: 1080
download_size: 127371587
dataset_size: 129205249
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc0-1.0
task_categories:
- image-classification
size_categories:
- 1K<n<10K
---
# Pomegranate Quality Classification
A dataset for classification of Pomegranate quality. The dataset contains 1,080 images across 3 classes: G1_Q1, G2_Q1, G3_Q1.
Images per class:
- G1_Q1: 360
- G2_Q1: 360
- G3_Q1: 360
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{kumar2021image,
title={Image dataset of pomegranate fruits (Punica granatum) for various machine vision applications},
author={Kumar, Arun and Rajpurohit, Vijay S and Gaikwad, Nilesh N},
journal={data in Brief},
volume={37},
pages={107249},
year={2021},
publisher={Elsevier}
}
```
Dr. Vijay S Rajpurohit, and Kshitijarun Y Bidari. (2020). Pomegranate Fruit Dataset [Dataset]. Kaggle. https://doi.org/10.34740/KAGGLE/DS/551234
*This dataset was reformatted from its original format to match HuggingFace standards.* |