windows-resize Object Detection Dataset and Pre-Trained Model by Inspection Team

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Explore Dataset

Here are a few use cases for this project:

Home Inspection Services: Inspectors can use the model to identify and classify various types of window damages, greatly increasing the efficiency of property inspections.
Real Estate Photography: Photographers can leverage the model to automatically pinpoint any visible flaws on windows, ensuring high-quality photos for real estate listings.
Repair and Maintenance Services: Professionals can use the model to assess the state of windows and determine necessary repairs, from identifying scratches and stains to detect dents and bends.
Insurance Claim Processing: Insurance companies can utilize the model to assist claim adjusters in identifying window damage from photos submitted during claim processes.
Quality Control in Manufacturing: Window manufacturers can leverage the model to identify defects such as scratches, stains, dents, and bends in the production line, thereby maintaining high quality control before shipment.

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{
                            windows-resize_dataset,
                            title = { windows-resize Dataset },
                            type = { Open Source Dataset },
                            author = { Inspection Team },
                            howpublished = { \url{ https://universe.roboflow.com/inspection-team/windows-resize } },
                            url = { https://universe.roboflow.com/inspection-team/windows-resize },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { sep },
                            note = { visited on 2024-04-28 },
                            }