Brief Introduction
Generate a simulation dataset in KITTI 2D/3D object detection dataset format based on CARLA Simulator.
Dataset format
training
|__ calib/ # Correction data from sensors such as cameras and radars
|__ image/ # RGB image generated by camera
|__ label/ # Object tags
|__ velodyne/ # Measurement data of LiDAR
|__ 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.
Type of label
The targets of label calibration are mainly divided into two categories. The first category is the actors (Car and Pedestrian) generated by ourselves; The second type is the environmental targets present in the map (None, Buildings，Fences，Other，Pedestrians，Poles，RoadLines，Roads，Sidewalks，TrafficSigns，Vegetation，Vehicles，Walls，Sky，Ground，Bridge，RailTrack，GuardRail，TrafficLight，Static，Dynamic，Water，Terrain)
Usage Method
Carla version: Carla 0.9.15
python generator.py
SynchronyModel.py，# Scenario class, responsible for establishing clients, setting up servers, generating actors, driving servers to calculate and obtain data
data_utils.py，# Contains tool functions such as point coordinate conversion and label generation
data_descriptor.py, # KITTI format description class
DataSave.py，# Data saving class, generating a path to save data, saving data
export_utils，# Tool functions for saving data
image_converter.py, # Image format conversion function
visual_utils，# Visualization tool functions