Grad_Project Computer Vision Project

Project

Updated 2 years ago

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Classes (20)
Parking-Sign
Pedestrian_Crossing Round-About Warning
do_not_enter
do_not_u_turn
no_parking
no_waiting
speed_limit_100
speed_limit_120
speed_limit_20
speed_limit_30
speed_limit_40
speed_limit_50
speed_limit_60
speed_limit_70
speed_limit_80
stop
traffic_sign_90
u_turn

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Description

Here are a few use cases for this project:

  1. Smart Traffic Management: Grad_Project can be used in traffic control centers to monitor traffic signs in real-time, providing traffic controllers with valuable information on traffic flow restrictions, warnings, and up-to-date traffic behavior data to optimize traffic signals and proactively address congestion issues.

  2. Autonomous Vehicle Navigation: The model can be integrated into self-driving car systems to identify traffic signs and make real-time decisions, such as adjusting the vehicle's speed, recognizing pedestrian crossings for increased safety, and obeying traffic restrictions like no U-turns or no parking zones.

  3. Traffic Sign Maintenance: Grad_Project can assist local authorities and road maintenance crews by identifying damaged or obscured traffic signs that require repair or cleaning, helping to maintain a safe and efficient road network.

  4. Driving Assistance Systems: The model can be incorporated into Advanced Driver Assistance Systems (ADAS) to alert drivers of upcoming traffic signs, providing critical information on speed limits, warnings, and restrictions, allowing drivers to make informed decisions in real-time and avoid traffic violations.

  5. Education and Training: Grad_Project can be used in driving schools and simulation tools for teaching new drivers to recognize various traffic signs and their meanings, facilitating learning and reinforcing safe driving practices.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            grad_project-sbq7e_dataset,
                            title = { Grad_Project Dataset },
                            type = { Open Source Dataset },
                            author = { Project },
                            howpublished = { \url{ https://universe.roboflow.com/project-wyyo5/grad_project-sbq7e } },
                            url = { https://universe.roboflow.com/project-wyyo5/grad_project-sbq7e },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-11-21 },
                            }
                        
                    

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