Datasetpublic

Project-AgML/tomato_quality_classification

Tomato Quality Classification A dataset for quality classification of Tomatoes. The dataset contains raw and augmented versions.The raw dataset contains 1,986 images.Images per class: Fresh: 1,350 Rotten: 636 The augmented dataset contains 6,000 images.Images per class: Fresh: 3,000 Rotten: 3,000 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… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/tomato_quality_classification.

sourceHugging Facecc-by-4.0updated 2mo agoView on Hugging Face

0likes95downloads

Dataset Card

Tomato Quality Classification

A dataset for quality classification of Tomatoes. The dataset contains raw and augmented versions. The raw dataset contains 1,986 images. Images per class:

—Fresh: 1,350
—Rotten: 636

The augmented dataset contains 6,000 images. Images per class:

—Fresh: 3,000
—Rotten: 3,000

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

Citation

bibtex

@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.