简介
基于CARLA Simulator生成KITTI 2D/3D目标检测数据集格式的仿真数据集。除了对车辆和行人生成Label外，还对仿真环境中的20余种物体生成Label(树木、交通信号灯等）。
数据收集流程
数据集格式
training
|__ calib/ # 相机、雷达等传感器的矫正数据
|__ image/ # 相机产生的RGB图像
|__ label/ # object 的标签
|__ velodyne/ # 激光雷达的测量数据
|__ train.txt
|__ trainval.txt
|__ val.txt
label：
#Values Name Description
----------------------------------------------------------------------------
1 type Describes the type of object: 'Car','Pedestrian',
'TrafficSigns', etc.
1 truncated Float from 0 (non-truncated) to 1 (truncated), where
truncated refers to the object leaving image boundaries
1 occluded Integer (0,1,2,3) indicating occlusion state:
0 = fully visible, 1 = partly occluded
2 = largely occluded
1 alpha Observation angle of object, ranging [-pi..pi]
4 bbox 2D bounding box of object in the image (0-based index):
contains left, top, right, bottom pixel coordinates
3 dimensions 3D object dimensions: height, width, length (in meters)
3 location 3D object location x,y,z in camera coordinates (in meters)
1 rotation_y Rotation ry around Y-axis in camera coordinates [-pi..pi]
1 score Only for results: Float, indicating confidence in
detection, needed for p/r curves, higher is better.
label种类
label标定的目标主要分为两类，第一类是我们自己生成的actors(Car 和 Pedestrian)；第二类是地图中存在的环境目标(None，Buildings，Fences，Other，Pedestrians，Poles，RoadLines，Roads，Sidewalks，TrafficSigns，Vegetation，Vehicles，Walls，Sky，Ground，Bridge，RailTrack，GuardRail，TrafficLight，Static，Dynamic，Water，Terrain)
使用
Carla版本：carla 0.9.12
python generator.py
SynchronyModel.py，场景类，负责建立client，设置server，生成actors，驱动server计算并获取数据
data_utils.py，包含点坐标转换、生成label等工具函数
data_descriptor.py, KITTI格式的描述类
DataSave.py，数据保存类，生成保存数据路径，保存数据
export_utils，保存数据的工具函数
image_converter.py, 图片格式转换函数
visual_utils，可视化工具函数