CONSOLE_POB Object Detection Dataset and Pre-Trained Model by object detectio

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Explore Dataset

Here are a few use cases for this project:

Quality Control in Production Line: CONSOLE_POB can be used in the manufacturing industry, particularly in companies that produce various types of bottles, to identify defects in the bottles classed as U_pob, M_pob. Automated quality control can save time and resources.
Recycling Centers: This model could help sort bottles at recycling centers. By identifying U_pob and M_pob defective bottles, these can be separated for repair or specific recycling processes.
Beverage Industry: Beverage companies can use the model to ensure the quality of their product packaging, by detecting defects in the bottles before they are filled and sealed.
Retail Industry: In stores and supermarkets, the model could be used to maintain inventory quality by scanning items on arrival and removing any defective bottles from the supply chain before they reach the shelves.
Research & Development: Companies designing new bottle designs or manufacturing methods could use this model to test the frequency and type of defects in their prototypes, providing valuable data to refine their processes.

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{
                            console_pob_dataset,
                            title = { CONSOLE_POB Dataset },
                            type = { Open Source Dataset },
                            author = { object detectio },
                            howpublished = { \url{ https://universe.roboflow.com/object-detectio/console_pob } },
                            url = { https://universe.roboflow.com/object-detectio/console_pob },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-05-08 },
                            }