Projectt Object Detection Dataset and Pre-Trained Model by SMDataset

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Explore Dataset

Here are a few use cases for this project:

Real Estate Platform Enhancement: Integrate Projectt with real estate websites or applications to automatically identify and categorize property listings with house and window-related features, providing potential buyers or renters with a more refined and efficient browsing experience.
Urban Planning and Analysis: Utilize Projectt in urban planning projects to evaluate the density and diversity of house types in a neighborhood or city, using the identified classes of houses and windows to inform zoning regulations or to optimize sustainable urban development.
Historical Architecture Research: Apply Projectt to analyze historical photographs or archival images, enabling researchers to study the evolution of house styles and window designs in different regions over time, aiding in the preservation of architectural heritage.
Augmented Reality (AR) Home Design Apps: Incorporate Projectt into AR home design applications to allow users to visualize how prospective window styles, sizes, and placements might look on their house, making it easier for homeowners to decide on the best options for renovation projects.
Maintenance and Utility Assessment: Leverage Projectt's house and window identification capabilities to streamline infrastructure maintenance tasks, such as identifying areas in need of window replacements or energy upgrades, improving the efficiency of local utility companies and public services.

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{
                            projectt_dataset,
                            title = { Projectt Dataset },
                            type = { Open Source Dataset },
                            author = { SMDataset },
                            howpublished = { \url{ https://universe.roboflow.com/smdataset-ykzlb/projectt } },
                            url = { https://universe.roboflow.com/smdataset-ykzlb/projectt },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-07-27 },
                            }