yolov8 Object Detection Dataset and Pre-Trained Model by PIT

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Explore Dataset

Here are a few use cases for this project:

Quality Control in Manufacturing: This model could be used to automatically identify and categorize different nuts and parts on a production line, thereby improving efficiency and reducing instances of human error.
Automated Sorting Systems: The yolov8 model can be employed in automated sorting or recycling facilities to distinguish between different nut classes and objects, promoting efficient material separation.
Construction and Building Automation: The model can be used in building construction sites or heavy machinery setups where diverse types of nuts and parts are used, aiding workers in quickly identifying the correct components.
Repair and Maintenance: The model could be useful in auto repair shops or electronics repair services to control inventories of spare parts and also to help technicians identify the exact part they need.
Robotics and Automation: Robots involved in assembly lines or repairs could utilize this model to quickly identify parts, enhancing their functionality, speed, and usefulness.

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{
                            yolov8-u7rpc_dataset,
                            title = { yolov8 Dataset },
                            type = { Open Source Dataset },
                            author = { PIT },
                            howpublished = { \url{ https://universe.roboflow.com/pit/yolov8-u7rpc } },
                            url = { https://universe.roboflow.com/pit/yolov8-u7rpc },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-04-28 },
                            }