Eggplant fruit disease detection Object Detection Dataset and Pre-Trained Model by BSCS

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Explore Dataset

Here are a few use cases for this project:

Agricultural Health Monitoring: This model could be used by farmers or agricultural engineers to monitor the health status of eggplant crops in fields. Regular monitoring could lead to early disease detection, thereby enabling faster responses and potentially saving a significant portion of the crop yield.
Plant Disease Identification App: Developers could integrate this model into a mobile app. End-users such as amateur gardeners or small scale farmers could use the app to take pictures of their eggplants and get information about potential diseases affecting them.
Greenhouse Management: In tech-equipped greenhouses, the model could be integrated within the existing system to automatically monitor eggplant crops. It would notify the greenhouse keepers when it identifies Fruit Rot, Melon Thrips, and Fruit borers, leading to more efficient and proactive pest/disease management.
Agricultural Research: This model could be used in academic or farming research projects to quantify the effects of different cultivation methods on eggplant pests and diseases. It could provide useful data to researchers studying these particular plant diseases.
Automated Sorting Systems: In industrial farming facilities, this model could be integrated into sorting systems to automatically isolate fruits with rot or infestations from healthy ones, reducing the risk of disease spreading while increasing the overall quality of produce.

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.

YOLOv5

This project has a YOLOv5 model checkpoint available for inference with Roboflow Deploy. YOLOv5 is a proven and tested, production ready, state-of-the-art real-time object detection model.

Cite This Project

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

@misc{
                            eggplant-fruit-disease-detection_dataset,
                            title = { Eggplant fruit disease detection Dataset },
                            type = { Open Source Dataset },
                            author = { BSCS },
                            howpublished = { \url{ https://universe.roboflow.com/bscs-sdztk/eggplant-fruit-disease-detection } },
                            url = { https://universe.roboflow.com/bscs-sdztk/eggplant-fruit-disease-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-04-25 },
                            }