Cobble Object Detection Dataset and Pre-Trained Model by OCST

Images

974 images

Explore Dataset

Here are a few use cases for this project:

Industrial Process Monitoring: "Cobble" can be used in monitoring systems for factories that manufacture cobblestone-style products or floorings. It can reliably identify cobble patterns and flag irregularities to ensure product quality and consistency.
Architecture and Interior Design: This model can be useful in architecture and interior design applications to identify and categorize different styles of cobble patterns. Designers could use this computer vision model to rapidly identify suitable cobble patterns in a large database, enhancing their design process.
Construction Industry: Builders and contractors can use "Cobble" to identify cobblestone materials in planned construction projects, helping streamline their material procurement process. It reduces the time spent on manually locating specific cobble classes.
Archeological Research: Researchers can deploy the "Cobble" model to help identify and categorize cobblestone patterns in ancient ruins or archeological sites, speeding up the examination process.
Landscape Design: Landscape artists could use "Cobble" model to visualize how various cobble patterns would look in a particular outdoor design, assisting in creating visually appealing and sustainable landscapes.

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{
                            cobble-q5er5_dataset,
                            title = { Cobble Dataset },
                            type = { Open Source Dataset },
                            author = { OCST },
                            howpublished = { \url{ https://universe.roboflow.com/ocst/cobble-q5er5 } },
                            url = { https://universe.roboflow.com/ocst/cobble-q5er5 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-06-27 },
                            }