Datasets:

Project-AgML
/

pomegranate_thermal_defect_classification

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

@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.