Datasets:
File size: 1,396 Bytes
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dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': Major Defect
'1': Minor Defect
'2': No Defect
splits:
- name: train
num_bytes: 741149609
num_examples: 982
download_size: 741179545
dataset_size: 741149609
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: cc-by-4.0
task_categories:
- image-classification
size_categories:
- n<1K
---
# Pomegranate Thermal Defect Classification
A dataset for classification of Pomegranate defects using thermal imagery. The dataset contains 982 images across 3 classes: Major Defect, Minor Defect, No Defect.
Images per class:
- Major Defect: 303
- Minor Defect: 340
- No Defect: 339
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
## Citation
```bibtex
@article{gaikwad2025dataset,
title={Dataset creation of thermal images of pomegranate for internal defect detection},
author={Gaikwad, Ashvini and Deshpande, Manoj and Bhole, Varsha},
journal={Data in brief},
volume={60},
pages={111538},
year={2025},
publisher={Elsevier}
}
```
gaikwad, ashvini (2024), “Pomegranate Thermal Images”, Mendeley Data, V1, doi: 10.17632/djcgvgtcfm.1
*This dataset was reformatted from its original format to match HuggingFace standards.* |