sva-lab Object Detection Dataset and Pre-Trained Model by sva

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Explore Dataset

Here are a few use cases for this project:

Historical Architecture Recognition: The 'sva-lab' computer vision model could be used by architectural historians or heritage organizations to identify and classify distinctive architectural classes, such as towers with clocks (ceas). This could help them to catalog and preserve historical buildings and structures.
Urban Planning and Development: Urban planners and developers might use this model to analyze and categorize the types of existing buildings within a city or town (towers, buildings with flagpoles/steag), assisting in planning new infrastructure and evaluating city landscapes.
Tourism Applications: The 'sva-lab' model can be used in the tourism industry to develop interactive AR or VR experiences. As tourists walk around a city, they could point their camera to a building or a monument, and the model could offer real-time information about the architectural class it belongs to.
Educational Use: The model can be a useful tool for academic research and education, especially in disciplines such as history, architecture, and societal studies. It can automate the process of identifying and cataloging buildings based on their architectural elements, saving time and effort.
Real Estate Industry: Real estate agencies can utilize 'sva-lab' to automatically recognize the architectural features of properties during valuation or listing, enabling them to provide detailed and accurate descriptions to potential buyers or tenants quickly.

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{
                            sva-lab_dataset,
                            title = { sva-lab Dataset },
                            type = { Open Source Dataset },
                            author = { sva },
                            howpublished = { \url{ https://universe.roboflow.com/sva-hrmkq/sva-lab } },
                            url = { https://universe.roboflow.com/sva-hrmkq/sva-lab },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-05-13 },
                            }