Channels error when trying to train with 360 degree point cloud data (Argoverse)

[chayangkultan96]

Channels error when trying to train with 360 degree point cloud data (Argoverse)

[sshaoshuai]

(1) For the training of SECOND/PartA2 configurations, you should make sure your voxelized channels in the height direction shoud match with MODEL.RPN.RPN_HEAD.ARGS['num_input_features'], or you just simply make sure your voxelized height channels should be 40, such as in my default config the channels should be '(1 - (-3)) / 0.1 = 40'.
(2) Is there any scenes that don't have any ground truth boxes in your training data? If so, maybe you should update the dataloader to make sure the input training data has at least one ground truth box.

[chayangkultan96]

(1) For the training of SECOND/PartA2 configurations, you should make sure your voxelized channels in the height direction shoud match with MODEL.RPN.RPN_HEAD.ARGS['num_input_features'], or you just simply make sure your voxelized height channels should be 40, such as in my default config the channels should be '(1 - (-3)) / 0.1 = 40'.
(2) Is there any scenes that don't have any ground truth boxes in your training data? If so, maybe you should update the dataloader to make sure the input training data has at least one ground truth box.

Thanks for your reply. Just a quick follow up question:

(1) Could you elaborate a little more on why 40 is the chosen number and how it eventually mapped to num_input_features which was set to 256 in the default setting? Maybe I'm missing something. How would I go about making sure that they are equal for my setting?

(2) Good point, there are some scenes without ground truth data, I'll make the changes and see how it works.

[sshaoshuai]

You could refer to the code here https://github.com/sshaoshuai/PCDet/blob/master/pcdet/models/rpn/rpn_unet.py#L484 for the mapping to the BEV feature channels, which is more clear. Just carefully set the height range and voxel size to make sure it has 40 levels after voxelization.

[chayangkultan96]

Thanks I understand it now. @sshaoshuai Another question not related to this issue. Does other part of the code except for the dataloader depends on KITTI label coordinate? i.e. xyz centers being defined as bottom of object instead of true center. What is the convention for xyz through out the code?

Thanks!

[chayangkultan96]

(1) For the training of SECOND/PartA2 configurations, you should make sure your voxelized channels in the height direction shoud match with MODEL.RPN.RPN_HEAD.ARGS['num_input_features'], or you just simply make sure your voxelized height channels should be 40, such as in my default config the channels should be '(1 - (-3)) / 0.1 = 40'.
(2) Is there any scenes that don't have any ground truth boxes in your training data? If so, maybe you should update the dataloader to make sure the input training data has at least one ground truth box.

Also, I rechecked my dataset, there are no frames that does not have GT data, I'm still occasionally getting this error, any thoughts on this? Thanks!

[sshaoshuai]

I do not know why it happens with these information, maybe you could try to catch the bugs and print the variables here.

[bugerry87]

Converting the Argoverse dataset to Kitti format?
Hm... while I try to get through this mess of dicts and pickles.
This data management requires some refactoring.

Hope I can contribute something soon.