Tomates Object Detection Dataset and Pre-Trained Model by CNNTomato

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Explore Dataset

Here are a few use cases for this project:

Agricultural Disease Detection: This model can be used by farmers or agricultural professionals to quickly and accurately diagnose tomato plant diseases. By uploading a picture of a potentially affected plant, users can obtain information on the type of disease, potentially saving substantial time and resources that can be directed to efficient disease control measures.
Greenhouse Monitoring: Growers maintaining greenhouse settings can deploy this computer vision model for routine checks to identify any emergence of disease in tomato plants.
Agricultural Research: Research institutions and universities can use the model as part of their studies into tomato diseases or plant pathology in general. It could help in providing more accurate, consistent data in the research of diseases specific to tomato crops.
Educational Tool: The model could be integrated into an educational app or tool to help students studying agriculture or botany learn about tomato plant diseases more interactively.
Home Gardening App: An app for home gardeners can implement this model to help users identify and treat diseases in their homegrown tomato plants, making gardening more accessible and successful for beginners.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite this Project

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

@misc{ tomates_dataset,
    title = { Tomates Dataset },
    type = { Open Source Dataset },
    author = { CNNTomato },
    howpublished = { \url{ https://universe.roboflow.com/cnntomato/tomates } },
    url = { https://universe.roboflow.com/cnntomato/tomates },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2022 },
    month = { may },
    note = { visited on 2023-12-04 },
}