Instance Segmentation Instance Segmentation Dataset and Pre-Trained Model by Yolo Custom Object Detection

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Explore Dataset

Here are a few use cases for this project:

Grocery Inventory Management: The Onion Detector can be used in supermarkets and grocery stores to automatically monitor and manage the inventory and stock of onions by accurately identifying and counting the onions in the storage area or on display shelves.
Onion Harvesting Automation: Developing harvest automation equipment using the Onion Detector model can help farmers and agricultural companies to detect and separate onions from weeding plants or soil, significantly improving the speed and efficiency of onion harvesting processes.
Quality Control in Food Industry: The Onion Detector can be integrated into the production line of food processing plants, enabling the system to automatically detect onions in various stages of processing—such as sorting, cleaning, and grading—to ensure a consistent quality of the final product.
Onion Waste Reduction: The model can be used in a retail, restaurant, or home setting to identify onions that may be starting to spoil, enabling consumers or foodservice operators to prioritize using these onions before they need to be discarded, ultimately limiting food waste.
Smart Kitchen Assistance: By integrating the Onion Detector into smart kitchen appliances, users could receive automatic recipe suggestions based on the available ingredients, including onions, making it easier to determine meal options without manually searching recipe databases.

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{
                            instance-segmentation-wagk9_dataset,
                            title = { Instance Segmentation Dataset },
                            type = { Open Source Dataset },
                            author = { Yolo Custom Object Detection },
                            howpublished = { \url{ https://universe.roboflow.com/yolo-custom-object-detection/instance-segmentation-wagk9 } },
                            url = { https://universe.roboflow.com/yolo-custom-object-detection/instance-segmentation-wagk9 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-04-29 },
                            }