tile the real best Object Detection Dataset and Pre-Trained Model by bruh

Images

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Explore Dataset

Here are a few use cases for this project:

Construction and Architecture: This model can help architects and constructors to detect and classify different types of tiles used in various construction projects. It might be used to analyze building materials in urban planning or in the design phase of construction projects.
Interior Design: Interior designers can use this model to identify different tile types in home or office design projects, which would support them in creating matching or complementary design schemes.
Historic Building Analysis: Researchers and historians might use this AI model to classify and recognize tile types on historic buildings, aiding in the identification of time periods, cultures, and architectural styles.
Satellite Image Analysis: For space companies or astronomers who analyze satellite images, this model can help identify buildings and their tile makeups. This could assist in urban planning or environmental research.
E-commerce Retail: Companies selling tiles could utilize the model to automate and improve classification and tagging process of their inventories, making the online search and discovery process easier and more intuitive for customers.

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{
                            tile-the-real-best_dataset,
                            title = { tile the real best Dataset },
                            type = { Open Source Dataset },
                            author = { bruh },
                            howpublished = { \url{ https://universe.roboflow.com/bruh-s0vei/tile-the-real-best } },
                            url = { https://universe.roboflow.com/bruh-s0vei/tile-the-real-best },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-04-29 },
                            }