STROITELI_HACK_2023 Object Detection Dataset and Pre-Trained Model by AIBuilding

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Explore Dataset

Here are a few use cases for this project:

Construction Quality Assurance: An organization responsible for ensuring the quality of construction outcomes could use the STROITELI_HACK_2023 model to automatically analyze construction sites' photos. It can help to identify instances of poor workmanship (like bad walls, roofs, floors), classify areas as being in rough or finished condition, detect the presence of important components such as radiators or sockets, and highlight any accumulated trash.
Real Estate Image Analysis: Real estate companies could use the model to analyze property images for listing purposes or for estimating the value of properties. By identifying the condition and presence of different rooms and elements (like kitchens, bathrooms, windows, doors), more accurate descriptions can be generated.
Construction Progress Tracking: Construction companies can use this model to track site progress over time. By identifying and cataloging different elements and their condition at various stages, companies can get a visual and analytical understanding of work completion levels.
Home Improvement Planning: Homeowners can use the model to plan and visualize their home improvements. By identifying various rooms and their current condition, they can better plan renovation and remodeling tasks.
Smart Home Integration: The model could be integrated into a smart home system where it can be used to visually identify status or changes in the house like detecting a newly installed sink in the bathroom or a new radiator in the living room. The system can then automate tasks accordingly, for instance suggesting shopping list for bathroom accessories after a new sink detected.

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{
                            stroiteli_hack_2023_dataset,
                            title = { STROITELI_HACK_2023 Dataset },
                            type = { Open Source Dataset },
                            author = { AIBuilding },
                            howpublished = { \url{ https://universe.roboflow.com/aibuilding/stroiteli_hack_2023 } },
                            url = { https://universe.roboflow.com/aibuilding/stroiteli_hack_2023 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-04-28 },
                            }