David Tock

Void Detection

Object Detection

Void Detection Computer Vision Project

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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.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new 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{
                            void-detection-q1vmu_dataset,
                            title = { Void Detection Dataset },
                            type = { Open Source Dataset },
                            author = { David Tock },
                            howpublished = { \url{ https://universe.roboflow.com/david-tock-z6iow/void-detection-q1vmu } },
                            url = { https://universe.roboflow.com/david-tock-z6iow/void-detection-q1vmu },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { apr },
                            note = { visited on 2024-04-27 },
                            }
                        

Connect Your Model With Program Logic

Find utilities and guides to help you start using the Void Detection project in your project.

Source

David Tock

Last Updated

3 days ago

Project Type

Object Detection

Subject

Void-gaps-in-retail

Views: 10

Views in previous 30 days: 7

Downloads: 2

Downloads in previous 30 days: 2

License

CC BY 4.0

Classes

\ empty_container floor freezer_bottom hidden low top_void void void_device voiid