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Project-AgML/fresh_rotten_fruit_classification

Fresh Rotten Fruit Classification A dataset for quality classification of 8 types of fruit. The dataset contains raw and augmented versions.The raw dataset contains 3,200 images.Images per class: Fresh: 1,600 Rotten: 1,600 The augmented dataset contains 12,335 images.Images per class: Fresh: 6,194 Rotten: 6,141 This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library. Citation @article{SULTANA2022108552, title = {An… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/fresh_rotten_fruit_classification.

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Fresh Rotten Fruit Classification

A dataset for quality classification of 8 types of fruit. The dataset contains raw and augmented versions. The raw dataset contains 3,200 images. Images per class:

—Fresh: 1,600
—Rotten: 1,600

The augmented dataset contains 12,335 images. Images per class:

—Fresh: 6,194
—Rotten: 6,141

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

Citation

bibtex

@article{SULTANA2022108552,
title = {An extensive dataset for successful recognition of fresh and rotten fruits},
journal = {Data in Brief},
volume = {44},
pages = {108552},
year = {2022},
issn = {2352-3409},
doi = {https://doi.org/10.1016/j.dib.2022.108552},
url = {https://www.sciencedirect.com/science/article/pii/S2352340922007594},
}

Sultana, Nusrat; Jahan, Musfika; Uddin, Mohammad Shorif (2022), “Fresh and Rotten Fruits Dataset for Machine-Based Evaluation of Fruit Quality”, Mendeley Data, V1, doi: 10.17632/bdd69gyhv8.1

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