Closed irmuun20 closed 1 year ago
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, XMAX are used to define point cloud range in preprocess and BEV size, where $H{BEV} = (X{MAX} - X{MIN})/X_{STEP}$
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
Hi, I think it's due to the data difference, the model I provide is trained from waymo dataset velodyne 64 lidar. Maybe you should train a new model with your new dataset, and deploy it as TRT model, then run inference, in README I provide the details on how to deploy your own model.
BW, Hao
irmuun20 @.***> 于2023年3月13日周一 08:20写道:
What variables should be changed when one uses different lidar like ouster 2(128)? Thanks
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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
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?