Object Detection

imane Computer Vision Project

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Here are a few use cases for this project:

  1. Traffic Monitoring Systems: The "imane" model can be used in traffic monitoring systems to automatically identify and categorize different traffic signs in real-time. This could greatly aid in efficient traffic management, analysis of traffic patterns, and detection of potential hazards.

  2. Autonomous Vehicles: Autonomous vehicles could utilize this computer vision model to accurately recognize road signs allowing for safer navigation and adherence to traffic rules.

  3. Driver Assistance Systems: This model can be integrated into Advanced Driver Assistance Systems (ADAS) to alert drivers about the various traffic signs while driving, thereby improving road safety.

  4. Traffic Sign Inventory Management: Road maintenance and traffic departments can use it for traffic sign inventory management. It will help in identifying the signs which are missing, damaged or faded and need repair or replacement.

  5. Road Sign Learning Applications: This model could be used in educational applications to help learners study different types of traffic signs, test their knowledge, or practice identifying signs in different driving scenarios.

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{ imane_dataset,
    title = { imane Dataset },
    type = { Open Source Dataset },
    author = { Datasets },
    howpublished = { \url{ } },
    url = { },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { may },
    note = { visited on 2023-12-11 },

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



Last Updated

6 months ago

Project Type

Object Detection




Prohibitory, mandatory, stop, warning, yield

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CC BY 4.0

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