Select Language

AI社区

公开数据集

Bosch Small Traffic Lights Dataset

Bosch Small Traffic Lights Dataset

544M
646 浏览
1 喜欢
13 次下载
0 条讨论
Autonomous Driving 2D Box,Image Caption

AbstractWe present the Bosch Small Traffic Lights Dataset, an accurate dataset for vision-based traffic light detection.......

数据结构 ? 544M

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Abstract

    We present the Bosch Small Traffic Lights Dataset, an accurate dataset for vision-based traffic light detection. Vision-only based traffic light detection and tracking is a vital step on the way to fully automated driving in urban environments. We hope that this dataset allows for easy testing of objection detection approaches, especially for small objects in larger images.

    The scenes cover a decent variety of road scenes and typical difficulties:

    • Busy street scenes inner-city

    • Suburban multilane roads with varying traffic density

    • Dense stop-and-go traffic

    • Road-works

    • Strong changes in illumination/exposure

    • Overcast sky with light rain

    • Flickering/Fluctuating traffic lights

    • Multiple visible traffic lights

    • Image parts that can be confused with traffic lights (e.g. large round tail lights)

    Data description

    This dataset contains 13427 camera images at a resolution of 1280x720 pixels and contains about 24000 annotated traffic lights. The annotations include bounding boxes of traffic lights as well as the current state (active light) of each traffic light.
    The camera images are provided as raw 12bit HDR images taken with a red-clear-clear-blue filter and as reconstructed 8-bit RGB color images. The RGB images are provided for debugging and can also be used for training. However, the RGB conversion process has some drawbacks. Some of the converted images may contain artifacts and the color distribution may seem unusual.
    Dataset specifications:

    • Training set:

      • 5093 images

      • Annotated about every 2 seconds

      • 10756 annotated traffic lights

      • Median traffic lights width: ~8.6 pixels

      • 15 different labels

      • 170 lights are partially occluded

    • Test set:

      • 8334 consecutive images

      • Annotated at about 15 fps

      • 13486 annotated traffic lights

      • Median traffic light width: 8.5 pixels

      • 4 labels (red, yellow, green, off)

      • 2088 lights are partially occluded

    For the test set, every frame is annotated and temporal information was used to improve the label accuracy. The test-set was recorded independently from the training set, but within the same region. The data-set was created to prototype traffic light detection approaches, it is not intended to cover all cases and not to be used for production.

    Example images:

    References

    The dataset has been created as part of our ICRA 2017 publication
    A Deep Learning Approach to Traffic Lights: Detection, Tracking, and Classification (video)
    If you publish work based on this data, please cite the following article:

    @inproceedings{BehrendtNovak2017ICRA,
      title={A Deep Learning Approach to Traffic Lights: Detection, Tracking, and Classification},
      author={Behrendt, Karsten and Novak, Libor},
      booktitle={Robotics and Automation (ICRA), 2017 IEEE International Conference on},
      organization={IEEE}
    }

    Sample scripts

    Sample scripts for reading the dataset are available at https://github.com/bosch-ros-pkg/bstld. Contributions are very welcome.

    Acknowledgements

    This work was conducted at the Bosch North America Research department, Palo Alto, California.

    License

    The dataset is released explicitly for non-commercial use only. The full license can be viewed here.
    Additional data, such as unlabeled frames, odometry, and other vehicle information may be available for researchers on request.

    ×

    帕依提提提温馨提示

    该数据集正在整理中,为您准备了其他渠道,请您使用

    注:部分数据正在处理中,未能直接提供下载,还请大家理解和支持。
    暂无相关内容。
    暂无相关内容。
    • 分享你的想法
    去分享你的想法~~

    全部内容

      欢迎交流分享
      开始分享您的观点和意见,和大家一起交流分享.
    所需积分:10 去赚积分?
    • 646浏览
    • 13下载
    • 1点赞
    • 收藏
    • 分享