Datasets:

Project-AgML
/

tomato_maturity_classification

dataset_info:
  - config_name: augmented
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': Immature
              '1': Mature
    splits:
      - name: train
        num_bytes: 4039039098
        num_examples: 4000
    download_size: 2260274666
    dataset_size: 4039039098
  - config_name: raw
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': Immature
              '1': Mature
    splits:
      - name: train
        num_bytes: 144554160
        num_examples: 1000
    download_size: 144583939
    dataset_size: 144554160
configs:
  - config_name: augmented
    data_files:
      - split: train
        path: augmented/train-*
  - config_name: raw
    data_files:
      - split: train
        path: raw/train-*
    default: true
license: cc-by-4.0
task_categories:
  - image-classification
size_categories:
  - 1K<n<10K

Tomato Maturity Classification

A dataset for maturity classification of tomatoes. The dataset contains raw and augmented versions.
The raw dataset contains 1,000 images.
Images per class:

Immature: 500
Mature: 500

The augmented dataset contains 4,000 images.
Images per class:

Immature: 2,000
Mature: 2,000

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

@article{khatun2023extensive,
  title={An extensive real-world in field tomato image dataset involving maturity classification and recognition of fresh and defect tomatoes},
  author={Khatun, Tania and Razzak, Abdur and Islam, Md Shofiul and Uddin, Mohammad Shorif},
  journal={Data in Brief},
  volume={51},
  pages={109688},
  year={2023},
  publisher={Elsevier}
}

Khatun, Tania; Razzak, Abdur ; Islam, Md. Shofiul ; Uddin, Prof. Dr. Mohammad Shorif (2023), “Tomato Maturity Detection and Quality Grading Dataset”, Mendeley Data, V1, doi: 10.17632/s42kpg8h37.1

This dataset was reformatted from its original format to match HuggingFace standards.