WCM - softa Object Detection Dataset and Pre-Trained Model by TIP S0f4

Images

8597 images

Explore Dataset

Here are a few use cases for this project:

Furniture Retail: Retailers can use the WCM-softa model to help customers visualize various sofa options in their stores. With a photo of the customer's room, the model can insert images of sofas, couches, or sofa beds to allow customers to see how each piece would fit into their space.
Interior Design Planning: Interior designers can use this tool to prepare designs and present them to their clients. By identifying and considering existing sofas or couches in the space, they can better plan the layout and reorganize the furniture.
Real Estate Virtual Tours: Real estate websites can use the model to create more interactive and detailed virtual home tours. Users can change the types of sofas, couches, or sofa beds in a room to match their tastes and see a potential home in a more personalized way.
Advertising and Marketing: The tool can be used to automatically identify whether an image includes a couch, sofa, or a sofa bed, which can be useful for targeted advertising. If these items are present, it can suggest that the viewer may be interested in home decor or furniture-related promotions.
Assistive Technology for Visually Impaired: The WCM-softa model can aid visually impaired people in their day-to-day lives by using image recognition to describe their surroundings. For example, by identifying couches or sofas in their living space, it can guide them to sit or avoid stumbling.

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{
                            wcm-softa_dataset,
                            title = { WCM - softa Dataset },
                            type = { Open Source Dataset },
                            author = { TIP  S0f4 },
                            howpublished = { \url{ https://universe.roboflow.com/tip-s0f4/wcm-softa } },
                            url = { https://universe.roboflow.com/tip-s0f4/wcm-softa },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-04-29 },
                            }