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KP-SS Outdoor Wall Segmentation Computer Vision Project

Gabriel Biler

Updated 18 days ago

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Instance Segmentation Model roboflow-3-n-seg
Classes (2)
Walls
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Description

Here are a few use cases for this project:

  1. Architecture Analysis: This model could be used by architects or engineers to analyze existing outdoor wall structures in urban or suburban areas, providing insight on patterns, trends, and variations in design for future projects.

  2. Real Estate Appraisals: Appraisers could use this model to more accurately estimate property values by rapidly categorizing and analyzing different types of exterior wall materials (brick, wood, vinyl, etc.) and their extent across a property.

  3. Urban Planning: Municipalities could harness this model's capabilities to identify and segment the layout of homes or buildings, helping them plan urban developments, design road networks or conduct a census.

  4. Augmented Reality Applications: AR developers could use this technology to more accurately overlay digital renderings or data upon real-world physical structures like walls in their applications.

  5. Home Renovation: DIY enthusiasts or home improvement professionals could use this model to better plan their projects, by accurately estimating the surface area of their external walls for paint, tiles, or other materials.

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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{
                            kp-ss-outdoor-wall-segmentation_dataset,
                            title = { KP-SS Outdoor Wall Segmentation Dataset },
                            type = { Open Source Dataset },
                            author = { Gabriel Biler },
                            howpublished = { \url{ https://universe.roboflow.com/gabriel-biler-mgmfm/kp-ss-outdoor-wall-segmentation } },
                            url = { https://universe.roboflow.com/gabriel-biler-mgmfm/kp-ss-outdoor-wall-segmentation },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { oct },
                            note = { visited on 2024-11-05 },
                            }

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