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Project-AgML/plant_leaf_disease_classification

Plant Leaf Disease Classification A dataset for disease classification of leaves from Bitter Gourd, Bottle Gourd, Tomato, Eggplant, Cauliflower, and Cucumber. The dataset contains 12,786 images across 16 classes:Images per class: Anthracnose: 601 Anthracnose lesions: 535 Black Rot: 560 Downey mildew: 1,254 Downy mildew: 1,076 Eggplant Cercopora leaf spot: 723 Eggplant begomovirus: 720 Eggplant fresh leaf: 771 Eggplant verticillium wilt: 730 Fresh leaf: 2,122 Fusarium wilt: 502… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/plant_leaf_disease_classification.

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Dataset Card

Plant Leaf Disease Classification

A dataset for disease classification of leaves from Bitter Gourd, Bottle Gourd, Tomato, Eggplant, Cauliflower, and Cucumber. The dataset contains 12,786 images across 16 classes: Images per class:

—Anthracnose: 601
—Anthracnose lesions: 535
—Black Rot: 560
—Downey mildew: 1,254
—Downy mildew: 1,076
—Eggplant Cercopora leaf spot: 723
—Eggplant begomovirus: 720
—Eggplant fresh leaf: 771
—Eggplant verticillium wilt: 730
—Fresh leaf: 2,122
—Fusarium wilt: 502
—Mosaic virus: 600
—Tomato Bacterial spot: 589
—Tomato Fresh leaf: 594
—Tomato leaf curl virus: 755
—Tomato spotted wilt: 654

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

Citation

bibtex

@article{hasan2024comprehensive,
  title={Comprehensive smart smartphone image dataset for plant leaf disease detection and freshness assessment from Bangladesh vegetable fields},
  author={Hasan, Mahamudul and Gani, Raiyan and Rashid, Mohammad Rifat Ahmmad and Tarin, Taslima Khan and Kamara, Raka and Mou, Mahbuba Yasmin and Rabbi, Sheikh Fajlay},
  journal={Data in Brief},
  volume={56},
  pages={110775},
  year={2024},
  publisher={Elsevier}
}

Rashid, Mohammad Rifat Ahmmad; Tarin, Taslima Khan ; Kamara, Raka ; Mou, Mahbuba Yasmin ; Rabbi, Sheikh Fajlay ; Hasan, Mahamudul (2024), “Plant Leaf Freshness and Disease Detection Dataset From Bangladesh”, Mendeley Data, V3, doi: 10.17632/n67gctmjyj.3