Object Detection


RedChipeada Computer Vision Project

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Here are a few use cases for this project:

  1. Autonomous Vehicle Navigation: The "RedChipeada" model could be utilized for identifying and interpreting traffic signals to aid autonomous vehicles in decision making and ensuring a safe driving environment.

  2. Traffic Monitoring Systems: Government agencies or traffic management bodies could use the model to enhance traffic monitoring systems, identifying traffic signals status in real-time, to manage traffic and improve road safety.

  3. Driving Tests Simulator: Driving test institutes or driving schools could integrate the model into their simulation software for the practice of signal recognition, aiding learners in understanding different traffic signals and their meanings more intuitively.

  4. Traffic Signal Maintenance: City maintenance teams could use the model to monitor the conditions of city traffic signals and more effectively schedule repairs or replacements, reducing costs and ensuring the integrity of road signaling.

  5. Augmented Reality Navigation Applications: The model could be incorporated into AR-based navigation applications to provide the user with real-time interpretation and alerts of upcoming traffic signs while they are driving or walking.

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{ redchipeada_dataset,
    title = { RedChipeada Dataset },
    type = { Open Source Dataset },
    author = { Chipeados },
    howpublished = { \url{ } },
    url = { },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { jun },
    note = { visited on 2023-12-09 },

Find utilities and guides to help you start using the RedChipeada project in your project.



Last Updated

6 months ago

Project Type

Object Detection




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