annotation Object Detection Dataset and Pre-Trained Model by umut workspace

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Explore Dataset

Here are a few use cases for this project:

Food Safety Inspection: The model can be utilized to automate the inspection process in grape production units. The system would efficiently sort out fresh grapes from rotten ones, thereby reducing manual labor and increasing productivity.
Agriculture Technology: Farmers often need to survey their grapevine fields to check for rotten grapes. This model can be integrated into drone or IoT based solutions to provide real-time insights about the health of their crop, supporting better grape management.
Retail Grocery Quality Control: Retail grocery stores could make use of this model to only shelf fresh grapes, ensuring customer satisfaction and reducing waste.
Grape-based Wine Production: Wine manufacturers could use this model for quality control, by ensuring only the freshest grapes are used in their wine production process.
Smart Home Applications: Developers can utilize this technology in smart refrigerators to alert users about rotten grapes, helping reduce food waste and ensuring healthier food consumption.

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{
                            annotation-shtem_dataset,
                            title = { annotation Dataset },
                            type = { Open Source Dataset },
                            author = { umut workspace },
                            howpublished = { \url{ https://universe.roboflow.com/umut-workspace/annotation-shtem } },
                            url = { https://universe.roboflow.com/umut-workspace/annotation-shtem },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-05-09 },
                            }