Plagas Rose Instance Segmentation Dataset and Pre-Trained Model by Plagas

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Explore Dataset

Here are a few use cases for this project:

Agricultural Surveillance System The Plagas Rose computer vision model could be integrated into an agricultural surveillance system. This would allow for real-time monitoring and detection of the MachaNegra classes, potentially alerting farmers to the onset of these specific elements before they harm the plants.
Smart Gardening Applications The model can be used to create smart gardening apps. These apps could help users identify MachaNegra on their roses, instruct them how to treat the plant and when they need professional help, ensuring they maintain the health of their garden.
Plant Research and Botany Researchers can use this model to classify and study the occurrence and impact of MachaNegra on various species of roses in different regions. This could provide valuable data in understanding the causes, effects, and possible preventative measures related to this disease.
Educational Purposes The model can be used as a teaching tool in botany and biology classes, enabling students to learn about plant diseases and their identification.
Agricultural Drone Imaging Combined with drone technology, the model can be used to scan large fields of roses for MachaNegra, helping to streamline the detection process and potentially saving significant funds in preventive maintenance.

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{ plagas-rose_dataset,
    title = { Plagas Rose Dataset },
    type = { Open Source Dataset },
    author = { Plagas },
    howpublished = { \url{ https://universe.roboflow.com/plagas/plagas-rose } },
    url = { https://universe.roboflow.com/plagas/plagas-rose },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { may },
    note = { visited on 2023-12-02 },
}