文章目录
- KITTI数据集
- 数据集结构
- 数据集内容
- data_object_calib 样本标定数据
- data_object_label_2 3D点云标注文件
KITTI数据集
数据集结构
- KITTI数据集网盘 提取码:0bjl
KITTI
├── devkit_object
| ├── cpp
| ├── mapping
| ├── matlab
| └── readme.txt
│—— data_object_calib
│ ├── testing
│ │ └── calib
│ └── training
│ └── calib
│—— data_object_label_2
│ ├── testing
│ └── label_2
│—— data_object_image_2
│ ├── testing
│ │ └── image_2
│ └──training
│ └── image_2
│—— data_object_velodyne
│ ├── testing
│ │ └── velodyne
│ └── training
│ └── velodyne
│—— data_road
│ ├── testing
│ │ ├── calib
│ │ └── image_2
│ └── training
│ ├── calib
│ ├── gt_image_2
│ └── image_2
│—— depth_2
数据集内容
- data_object_calib 每个样本的标定数据 (测试集7518个,训练集7481个)
- data_object_label_2 3D点云标注文件(只有训练集7481个)
- data_object_image_2 RGB图像 (测试集7518个,训练集7481个)
- data_object_velodyne 激光雷达数据(测试集7518个,训练集7481个)
- data_road 包含测试集和训练集 每集中包含标定参数以及RGB图像 训练集中还多个gt_image_2
- depth_2 7481张深度图像
data_object_calib 样本标定数据
P0:校对后的 camera0 投影矩阵,3x4 数组
P1:校对后的 camera1 投影矩阵,3x4 数组
P2:校对后的 camera2 投影矩阵,3x4 数组
P3:校对后的 camera3 投影矩阵,3x4 数组
R0_rect:校准旋转矩阵,4x4 数组
Tr_velo_to_cam:从 Velodyne 坐标到相机坐标的变换矩阵,4x4 数组
Tr_imu_to_velo:从 IMU 坐标到 Velodyne 坐标的变换矩阵,4x4 数组
data_object_label_2 3D点云标注文件
#Values Name Description
----------------------------------------------------------------------------1 type (类别信息:车 货车 卡车...)Describes the type of object: 'Car', 'Van', 'Truck','Pedestrian', 'Person_sitting', 'Cyclist', 'Tram','Misc' or 'DontCare'1 truncated (是否被截断:0-1截断程度)Float from 0 (non-truncated) to 1 (truncated), wheretruncated refers to the object leaving image boundaries1 occluded (是否被遮挡:0完全可见 1部分遮挡 2大部分遮挡 3未知)Integer (0,1,2,3) indicating occlusion state:0 = fully visible, 1 = partly occluded2 = largely occluded, 3 = unknown1 alpha (物体观察角度:[-pi, pi](弧度))Observation angle of object, ranging [-pi..pi]4 bbox (2D图像标注框:左上角右下角坐标)2D bounding box of object in the image (0-based index):contains left, top, right, bottom pixel coordinates3 dimensions (3D点云标注框:高 宽 长(m))3D object dimensions: height, width, length (in meters)3 location (3D点云标注框:相机坐标系底面中心点坐标(m))3D object location x,y,z in camera coordinates (in meters)1 rotation_y (物体正前方向与相机水平方向角度)Rotation ry around Y-axis in camera coordinates [-pi..pi]1 score (得分)Only for results: Float, indicating confidence indetection, needed for p/r curves, higher is better.