Project-AgML/plant_doc_classification

Plant Doc Classification

A dataset for disease classification of various plants. The dataset contains 2,569 images across 28 classes: Images per class:

• —Apple Scab Leaf: 93
• —Apple leaf: 91
• —Apple rust leaf: 88
• —Bell_pepper leaf: 61
• —Bell_pepper leaf spot: 71
• —Blueberry leaf: 114
• —Cherry leaf: 57
• —Corn Gray leaf spot: 68
• —Corn leaf blight: 191
• —Corn rust leaf: 116
• —Peach leaf: 111
• —Potato leaf early blight: 116
• —Potato leaf late blight: 105
• —Raspberry leaf: 119
• —Soyabean leaf: 65
• —Squash Powdery mildew leaf: 130
• —Strawberry leaf: 96
• —Tomato Early blight leaf: 88
• —Tomato Septoria leaf spot: 150
• —Tomato leaf: 63
• —Tomato leaf bacterial spot: 110
• —Tomato leaf late blight: 111
• —Tomato leaf mosaic virus: 54
• —Tomato leaf yellow virus: 75
• —Tomato mold leaf: 91
• —Tomato two spotted spider mites leaf: 2
• —grape leaf: 69
• —grape leaf black rot: 64

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

Citation

@inproceedings{10.1145/3371158.3371196,
author = {Singh, Davinder and Jain, Naman and Jain, Pranjali and Kayal, Pratik and Kumawat, Sudhakar and Batra, Nipun},
title = {PlantDoc: A Dataset for Visual Plant Disease Detection},
year = {2020},
isbn = {9781450377386},
publisher = {Association for Computing Machinery},
url = {https://doi.org/10.1145/3371158.3371196},
doi = {10.1145/3371158.3371196},
booktitle = {Proceedings of the 7th ACM IKDD CoDS and 25th COMAD},
pages = {249–253},
numpages = {5},
series = {CoDS COMAD 2020}
}

https://github.com/pratikkayal/PlantDoc-Dataset