PlantDoc Computer Vision Project

Singh et. al 2019

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Classes (30)
Apple Scab Leaf
Apple leaf
Apple rust leaf
Bell_pepper leaf
Bell_pepper leaf spot
Blueberry leaf Cherry leaf
Corn Gray leaf spot
Corn leaf blight
Corn rust leaf
Peach leaf
Potato leaf
Potato leaf early blight
Potato leaf late blight
Raspberry leaf Soyabean leaf Soybean leaf
Squash Powdery mildew leaf
Strawberry leaf
Tomato Early blight leaf
Tomato Septoria leaf spot
Tomato leaf
Tomato leaf bacterial spot
Tomato leaf late blight
Tomato leaf mosaic virus
Tomato leaf yellow virus
Tomato mold leaf
Tomato two spotted spider mites leaf
grape leaf
grape leaf black rot
Description

Overview

The PlantDoc dataset was originally published by researchers at the Indian Institute of Technology, and described in depth in their paper. One of the paper’s authors, Pratik Kayal, shared the object detection dataset available on GitHub.

PlantDoc is a dataset of 2,569 images across 13 plant species and 30 classes (diseased and healthy) for image classification and object detection. There are 8,851 labels. Read more about how the version available on Roboflow improves on the original version here.

And here's an example image:

Tomato Blight

Fork this dataset (upper right hand corner) to receive the raw images, or (to save space) grab the 416x416 export.

Use Cases

As the researchers from IIT stated in their paper, “plant diseases alone cost the global economy around US$220 billion annually.” Training models to recognize plant diseases earlier dramatically increases yield potential.

The dataset also serves as a useful open dataset for benchmarks. The researchers trained both object detection models like MobileNet and Faster-RCNN and image classification models like VGG16, InceptionV3, and InceptionResnet V2.

The dataset is useful for advancing general agriculture computer vision tasks, whether that be health crop classification, plant disease classification, or plant disease objection.

Using this Dataset

This dataset follows Creative Commons 4.0 protocol. You may use it commercially without Liability, Trademark use, Patent use, or Warranty.

Provide the following citation for the original authors:

@misc{singh2019plantdoc,
    title={PlantDoc: A Dataset for Visual Plant Disease Detection},
    author={Davinder Singh and Naman Jain and Pranjali Jain and Pratik Kayal and Sudhakar Kumawat and Nipun Batra},
    year={2019},
    eprint={1911.10317},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            plantdoc-t1vmu_dataset,
                            title = { PlantDoc Dataset },
                            type = { Open Source Dataset },
                            author = { Singh et. al 2019 },
                            howpublished = { \url{ https://universe.roboflow.com/cucumber-ghfev/plantdoc-t1vmu } },
                            url = { https://universe.roboflow.com/cucumber-ghfev/plantdoc-t1vmu },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { oct },
                            note = { visited on 2024-12-14 },
                            }