FIEP Mestrado Object Detection Dataset and Pre-Trained Model by fiepmestrado

Images

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Explore Dataset

Here are a few use cases for this project:

Furniture E-commerce: This model can be utilized by online furniture retailers to automatically classify different types of furniture and other items in uploaded images, thereby enhancing product listings and improving search functionality.
Interior Design Planning: Interior designers can use this model to identify different types of furniture and items in images of rooms as they are creating design plans. By recognizing these different items, the model could be used to provide recommendations for similar or complementary pieces.
Augmented Reality App Development: Developers designing AR apps for furniture placement or home decoration can use the model to better categorize real-world objects, allowing the app to suggest similar virtual items or to provide a visually fitting AR experience that aligns well with the existing environment.
Cognitive Therapies: Therapists working in cognitive rehabilitation can leverage this model as part of therapy apps that help patients identify objects, improving cognition and memory.
Waste Management and Recycling: Since the model recognizes cardboard-based items, it can be applied in a recycling context to identify cardboard waste, facilitating its sorting and recycling process. The model could, for instance, be implement at recycling facilities to facilitate automatic sorting.

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{
                            fiep-mestrado_dataset,
                            title = { FIEP Mestrado Dataset },
                            type = { Open Source Dataset },
                            author = { fiepmestrado },
                            howpublished = { \url{ https://universe.roboflow.com/fiepmestrado/fiep-mestrado } },
                            url = { https://universe.roboflow.com/fiepmestrado/fiep-mestrado },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-04-28 },
                            }