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  3. U.S. traffic sign character recognition dataset
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U.S. traffic sign character recognition dataset

Specialized dataset designed for training and validating highly accurate traffic sign detection and character recognition systems for autonomous vehicles operating in the U.S. Comprises over 10,000 images extracted from more than 15 hours of dash-cam footage recorded in the San Francisco Bay Area.

Specifications

Modalities
2D images
Location
Mountain View and South Bay areas (San Francisco)
Licensable
Yes
Sensor setup
1x dash-camera
Data volume
15 hours 52 mins of recording @30 FPS
Total images
10,868 annotated images
Year of collection
2024 and 2025
Time of day
Afternoon, evening, morning, noon, night, dusk, dawn
Licensable
Yes
Environment distribution
Sunny: 38.32%; partly cloudy: 33.50%; mostly sunny: 16.03%; cloudy: 12.15%

Accelerate model development & training processes

  • Diverse sign coverage

    Strategically captured to include a rich mix of regulatory, warning and informational signs, ensuring broad applicability and robustness in real-world deployments.

  • Optimized driving route

    Route planning that ensures high exposure to diverse road signs while covering varied terrain and infrastructure in San Francisco.

  • Environment and weather diversity

    Captured across varied times of day, from dawn to night and in real-world weather conditions, this dataset helps improve model generalization and resilience.

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Case Study

Explore our success stories

  • Curating high-quality data for the training and validation of ADAS and AV models

    An autonomous vehicle shown driving on a busy highway.

    Discover how TELUS Digital used our proven field operations testing (FOT) experience to create a high-quality dataset for training advanced driver assistance systems (ADAS) and autonomous vehicles (AV).


    • 12TBdata captured daily


    • 7500kmapproximate total distance covered

    Download case study

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