BTP2 Object Detection Dataset and Pre-Trained Model by BTP

Images

2196 images

Explore Dataset

Here are a few use cases for this project:

Quality Inspection in Manufacturing: The model can be used in manufacturing industries to identify defects or dirt in products during the production process, ensuring high quality standards.
Vehicle Maintenance: Detailing companies or vehicle maintenance services can use this model to detect damages or dirt on vehicles. This can help professionals estimate repair costs or cleaning efforts more precisely.
Used Goods Marketplace: The model can be employed in used goods marketplaces to check for any damage or dirt in the items listed for sale, assisting in accurate pricing and condition verification.
Art Restoration and Conservation: Art conservators could use this model to identify areas of damage or dirt on paintings or artifacts, helping in the preservation and restoration processes.
Building Maintenance and Inspection: Property managers can implement this model to identify damage or dirt build-up in buildings, enabling prompt maintenance and ensuring clean, comfortable living or working conditions.

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{
                            btp2_dataset,
                            title = { BTP2 Dataset },
                            type = { Open Source Dataset },
                            author = { BTP },
                            howpublished = { \url{ https://universe.roboflow.com/btp-vfgzu/btp2 } },
                            url = { https://universe.roboflow.com/btp-vfgzu/btp2 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-06-21 },
                            }