when i use the model epoch_295.pth in GoogleDrive and put it in ./checkpoints ,run eval.py, it comes a error like this:
load model from /root/data/Seg_Pytorch/BiSeNet-master/checkpoints/epoch_295.pth ...
Traceback (most recent call last):
File "eval.py", line 97, in
main(params)
File "eval.py", line 82, in main
model.module.load_state_dict(torch.load(args.checkpoint_path))
File "/root/miniconda3/envs/pytorch10/lib/python3.6/site-packages/torch/nn/modules/module.py", line 721, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for BiSeNet:
Missing key(s) in state_dict: "supervision1.weight", "supervision1.bias", "supervision2.weight", "supervision2.bias".
Unexpected key(s) in state_dict: "saptial_path.convblock1.bn.num_batches_tracked", "saptial_path.convblock2.bn.num_batches_tracked", "saptial_path.convblock3.bn.num_batches_tracked", "context_path.features.bn1.num_batches_tracked", "context_path.features.layer1.0.bn1.num_batches_tracked", "context_path.features.layer1.0.bn2.num_batches_tracked", "context_path.features.layer1.0.bn3.num_batches_tracked", "context_path.features.layer1.0.downsample.1.num_batches_tracked",
You said the net structure has been modified, so the pretrained model does not match the current model, so do you have any other pre-trained mode recommend for this network?
when i use the model epoch_295.pth in GoogleDrive and put it in ./checkpoints ,run eval.py, it comes a error like this:
load model from /root/data/Seg_Pytorch/BiSeNet-master/checkpoints/epoch_295.pth ... Traceback (most recent call last): File "eval.py", line 97, in
main(params)
File "eval.py", line 82, in main
model.module.load_state_dict(torch.load(args.checkpoint_path))
File "/root/miniconda3/envs/pytorch10/lib/python3.6/site-packages/torch/nn/modules/module.py", line 721, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for BiSeNet:
Missing key(s) in state_dict: "supervision1.weight", "supervision1.bias", "supervision2.weight", "supervision2.bias".
Unexpected key(s) in state_dict: "saptial_path.convblock1.bn.num_batches_tracked", "saptial_path.convblock2.bn.num_batches_tracked", "saptial_path.convblock3.bn.num_batches_tracked", "context_path.features.bn1.num_batches_tracked", "context_path.features.layer1.0.bn1.num_batches_tracked", "context_path.features.layer1.0.bn2.num_batches_tracked", "context_path.features.layer1.0.bn3.num_batches_tracked", "context_path.features.layer1.0.downsample.1.num_batches_tracked",
You said the net structure has been modified, so the pretrained model does not match the current model, so do you have any other pre-trained mode recommend for this network?