Test with ouster lidar
Closed this issue · 8 comments
I would like to test model on ouster lidar data. How can I set the following parameters? what is the difference between two X_MIN, and X_CENTER_MIN etc and what is X_STEP?
// pillar size
#define X_STEP 0.32f
#define Y_STEP 0.32f
#define X_MIN -74.88f
#define X_MAX 74.88f
#define Y_MIN -74.88f
#define Y_MAX 74.88f
#define Z_MIN -2.0f
#define Z_MAX 4.0f
#define X_CENTER_MIN -80.0f
#define X_CENTER_MAX 80.0f
#define Y_CENTER_MIN -80.0f
#define Y_CENTER_MAX 80.0f
#define Z_CENTER_MIN -10.0f
#define Z_CENTER_MAX 10.0f
#define PI 3.141592653f
// paramerters for preprocess
#define BEV_W 468
#define BEV_H 468
#define MAX_PILLARS 32000 //20000 //32000
#define MAX_PIONT_IN_PILLARS 20
#define FEATURE_NUM 10
#define PFE_OUTPUT_DIM 64
#define THREAD_NUM 4
With ouster sample data, it is detecting trees as people.
Used ouster lidar Signal 1 and Signal 2 Values instead of intensity and elongation (waymo):
intensity = np.tanh(Signal1 / 255.0)
elongation = np.tanh(Signal2 / 255.0)
and got the following results: cars are detected (most of them) but people are barely being detected:
There is a person on the road that is very close to lidar but not being detected.
X_MIN， X_MAX are used to define point cloud range in preprocess and BEV size, where
X_CENTER_MIN& X_CENTER_MAX define ranges that are used when making post processing where objs out of that range are not detected
What variables should be changed when one uses different lidar like ouster 2(128)? Thanks
Thanks for the suggestion but at the moment, I don't have annotated cloud point data collected by my lidar. So, for now I will use waymo setting as default, and when I get my own data, I will train model as you suggested.
Hello , I need to know if signal2 is the refelctivitty or the range in ouster lidar because I want to map it to elongation like you have done but i don't it is which value.
Thank you