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Project-AgML/papaya_leaf_disease_detection

Papaya Leaf Disease Detection A dataset for disease detection of Papaya leaves. The dataset contains 1,050 images with 7,616 bounding box annotations across 5 categories.The dataset can be used as a classification dataset based on the label column, which contains integer based labels for the following classes:Anthracnose: 0Bacterial Spot: 1Curl: 2Ring Spot: 3Healthy: 4 This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/papaya_leaf_disease_detection.

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Papaya Leaf Disease Detection

A dataset for disease detection of Papaya leaves. The dataset contains 1,050 images with 7,616 bounding box annotations across 5 categories. The dataset can be used as a classification dataset based on the label column, which contains integer based labels for the following classes: Anthracnose: 0 Bacterial Spot: 1 Curl: 2 Ring Spot: 3 Healthy: 4

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

Citation

bibtex

@article{mustofa2024bdpapayaleaf,
  title={BDPapayaLeaf: A dataset of papaya leaf for disease detection, classification, and analysis},
  author={Mustofa, Sumaya and Ahad, Md Taimur and Emon, Yousuf Rayhan and Sarker, Arpita},
  journal={Data in Brief},
  volume={57},
  pages={110910},
  year={2024},
  publisher={Elsevier}
}

Sarker, Arpita ; Mustofa, Sumaya; Ahad, Md Taimur (2024), “BDPapayaLeaf: A annotation based image dataset of papaya leaf disease.”, Mendeley Data, V2, doi: 10.17632/p997fvf526.2