Datasets:

Project-AgML
/

pomegranate_quality_classification

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

@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.