en-suite Computer Vision Project

hashwide

Updated 2 years ago

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Description

Here are a few use cases for this project:

  1. Real Estate Industry: The "En-suite" model can be used in real estate portals and websites to automatically classify property images. It can help in sorting and tagging photographs to highlight properties that come with attached bathrooms.

  2. Interior Design: The model can be used by interior designers or remodeling firms to categorize their designs or projects based on the type of bathrooms. It can also help them in identifying trends and preferences in bathroom designs.

  3. Virtual Tours: The "En-suite" model can be integrated into a virtual tour application to identify attached bathrooms in real time. This will enhance the depth and detail of virtual tours for prospective home buyers or renters.

  4. Maintenance and Renovation: Companies specializing in home renovation and maintenance can use "En-suite" to identify if there's an attached bathroom in a given image, helping them to plan out tasks and resource allocation more accurately.

  5. Smart Home Applications: The model could be used for advanced smart home applications. For example, automatically assessing the utilization of different parts of a house, such as the frequency of bathroom usage, to optimize energy management.

Supervision

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            en-suite_dataset,
                            title = { en-suite Dataset },
                            type = { Open Source Dataset },
                            author = { hashwide },
                            howpublished = { \url{ https://universe.roboflow.com/hashwide-9wmoa/en-suite } },
                            url = { https://universe.roboflow.com/hashwide-9wmoa/en-suite },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-11-14 },
                            }