KITTI Road Dataset
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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。




