rb-sign Object Detection Dataset and Pre-Trained Model by Eagle

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Explore Dataset

Here are a few use cases for this project:

Autonomous Robots: The "rb-sign" computer vision model can be used in autonoumous robots or drone systems to identify different colored armors and signs for navigation, target identification, avoiding obstacles, or for participation in robotic competitions.
Augmented Reality Games: This classifier model could be utilized in AR games where participants need to identify and interact with different classes of objects, including red, blue, grey armors, and various signs, adding an interactive and colorful element to the game environment.
Traffic Management Systems: The model can be used to identify different-colored signs (red_sign, blue_sign) in smart vehicle systems to alert drivers or autonomous vehicles about road conditions, directions, or other information.
Military Training Simulations: Trainees could use this model to identify different armors during simulation exercises, enhancing the quality and realism of the training experience.
Industrial Automation: The model can help in sorting or identification tasks on assembly lines, for instance, sorting based on the color of armor.

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{
                            rb-sign_dataset,
                            title = { rb-sign Dataset },
                            type = { Open Source Dataset },
                            author = { Eagle },
                            howpublished = { \url{ https://universe.roboflow.com/eagle-d7gcb/rb-sign } },
                            url = { https://universe.roboflow.com/eagle-d7gcb/rb-sign },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jul },
                            note = { visited on 2024-04-29 },
                            }