prbonn/contrastive_association

Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans

contrastive_association's Issues

size mismatch for encoder.contextBlock.conv_A1.weight

when i run the code:
python evaluate_4dpanoptic.py --ckpt_ps pre_trained/panoptic_pq_564.pth --ckpt_ag pre_trained/aggregation_aq_724.ckpt
I face this problem：
File "save_panoptic_features.py", line 46, in
main()
File "/home/wxiao/anaconda3/envs/strack/lib/python3.7/site-packages/click/core.py", line 1128, in call
return self.main(*args, **kwargs)
File "/home/wxiao/anaconda3/envs/strack/lib/python3.7/site-packages/click/core.py", line 1053, in main
rv = self.invoke(ctx)
File "/home/wxiao/anaconda3/envs/strack/lib/python3.7/site-packages/click/core.py", line 1395, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/home/wxiao/anaconda3/envs/strack/lib/python3.7/site-packages/click/core.py", line 754, in invoke
return __callback(*args, **kwargs)
File "save_panoptic_features.py", line 33, in main
model.load_state_dict(checkpoint['state_dict'])
File "/home/wxiao/anaconda3/envs/strack/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1224, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for PanopticCylinder:
size mismatch for encoder.contextBlock.conv_A1.weight: copying a param with shape torch.Size([3, 1, 3, 16, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 1, 3, 16]).
size mismatch for encoder.contextBlock.conv_A2.weight: copying a param with shape torch.Size([1, 3, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 1, 3, 3, 32]).
size mismatch for encoder.contextBlock.conv_B1.weight: copying a param with shape torch.Size([1, 3, 3, 16, 32]) from checkpoint, the shape in current model is torch.Size([32, 1, 3, 3, 16]).
size mismatch for encoder.contextBlock.conv_B2.weight: copying a param with shape torch.Size([3, 1, 3, 32, 32]) from checkpoint, the shape in current model is torch.Size([32, 3, 1, 3, 32]).
size mismatch for encoder.downBlock0.conv_A1.weight: copying a param with shape torch.Size([3, 1, 3, 32, 64]) from checkpoint, the shape in current model is torch.Size([64, 3, 1, 3, 32]).
size mismatch for encoder.downBlock0.conv_A2.weight: copying a param with shape torch.Size([1, 3, 3, 64, 64]) from checkpoint, the shape in current model is torch.Size([64, 1, 3, 3, 64]).
size mismatch for encoder.downBlock0.conv_B1.weight: copying a param with shape torch.Size([1, 3, 3, 32, 64]) from checkpoint, the shape in current model is torch.Size([64, 1, 3, 3, 32]).
size mismatch for encoder.downBlock0.conv_B2.weight: copying a param with shape torch.Size([3, 1, 3, 64, 64]) from checkpoint, the shape in current model is torch.Size([64, 3, 1, 3, 64]).
size mismatch for encoder.downBlock0.pool.weight: copying a param with shape torch.Size([3, 3, 3, 64, 64]) from checkpoint, the shape in current model is torch.Size([64, 3, 3, 3, 64]).

Hope someone can help me !!!

Can not evaluate and save result on test set

Can you explain what is coordinate_T in this line