UGA image detection Object Detection Dataset and Pre-Trained Model by UGA Internship Image Detection

Images

1082 images

Explore Dataset

Here are a few use cases for this project:

DIY Assistance: The UGA Image Detection model could be used in an app to assist DIY enthusiasts and construction workers. The app could provide real-time guidance, identifying whether the tool being used is suitable for the material in focus. For example, it could indicate whether a hcs wood blade or a rigid scraper blade should be used for a particular type of wood.
E-commerce Platform: This AI model could be used on e-commerce platforms to automatically categorize and tagging images of tools that are being sold. It would identify if the item is a button, a blade or a scraper, enhancing accuracy in categorization and product searching.
Inventory Management: Companies that deal with large numbers of tools (such as construction companies) could use the model to automatically track and manage their inventory. By identifying whether a tool is missing a blade, companies could ensure their tools are always ready for use.
Safety Applications: The model could be used in safety applications, ensuring that users are using the correct tools for specific tasks. For instance, checking if a person is using a flexible scraper for a task that may require a rigid scraper.
E-Learning Platform: An e-learning platform that offers courses for DIY, home improvement or professional craftsman programs could use this model. This would ensure users are being shown the correct tool used for specific jobs during video lessons. It could also be used for testing purposes, asking users to find the correct tool or part within an image.

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{
                            uga-image-detection_dataset,
                            title = { UGA image detection Dataset },
                            type = { Open Source Dataset },
                            author = { UGA Internship Image Detection },
                            howpublished = { \url{ https://universe.roboflow.com/uga-internship-image-detection-mba1c/uga-image-detection } },
                            url = { https://universe.roboflow.com/uga-internship-image-detection-mba1c/uga-image-detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-07-27 },
                            }