simaker
simaker
I had the same problem, but in my case the Memory of the GPU was completely full. Training on a RTX 2070 solved the problem
you also have to change it in the configfile
which resolution has the used lidar?
I also changed to V1.5 bit still get the same Error: `RuntimeError: Error(s) in loading state_dict for VoxelNet: Unexpected key(s) in state_dict: "rpn.blocks.1.1.weight", "rpn.blocks.1.2.weight", "rpn.blocks.1.2.bias", "rpn.blocks.1.2.running_mean", "rpn.blocks.1.2.running_var", "rpn.blocks.1.2.num_batches_tracked", "rpn.blocks.1.4.weight", "rpn.blocks.1.5.weight",...
> It is possible to do that. > You need to set `point_len: 512` to `point_len: 0` to avoid using LiDAR modules. > And then you need to set `score_fusion_arch:...
but why do i have to set test_mode: 0 and not 1? in the config it says: ` test_mode: 1 #0:image;1:LiDAR;2:fusion`
okay thank you. And how do i have to change this [line](https://github.com/ZwwWayne/mmMOT/blob/master/modules/tracking_net.py#L49)? I don't know what you mean by > check the score_fusion_arch to set fusion_module
it is possible. Just convert your data that it fits the KITTI-Format (add reflection intesity if necessary). Then replace your data with the data in the KITTI Dataset. The datapreparation...
just create the whole KITTI-Dataset and replace your files with the files in the Testfolder and use the modified evaluation step. The results (coordinates etc. ) will be stored in...
I'm not shure but i think you have to have to edit the train and val and test txt files. Tere it is defined what files are used for training...