KITTI Road Dataset

KITTI Road is road and lane estimation benchmark that consists of 289 training and 290 test images. It contains three different categories of road scenes:
* uu - urban unmarked (98/100)
* um - urban marked (95/96)
* umm - urban multiple marked lanes (96/94)
* urban - combination of the three above
Ground truth has been generated by manual annotation of the images and is available for two different road terrain types: road - the road area, i.e, the composition of all lanes, and lane - the ego-lane, i.e., the lane the vehicle is currently driving on (only available for category "um"). Ground truth is provided for training images only.

KITTI道路识别基准数据集，由289张训练图像和290张测试图像组成。该数据集涵盖三种不同的道路场景类别：uu - 城市无标记道路（98/100），um - 城市标记道路（95/96），umm - 城市多重标记车道（96/94）。此外，还包括城市类别，即上述三种类型的组合。真实标签通过手动标注图像生成，并针对两种不同的道路地形类型提供：道路 - 指道路区域，即所有车道组成的部分，以及车道 - 自我车道，即车辆当前行驶的车道（仅适用于类别“um”）。真实标签仅对训练图像提供。