Closed lu-jincheng closed 4 years ago
I figured it out. It is caused by the torch version differences between training and evaluating time.
I figured it out. It is caused by the torch version differences between training and evaluating time.
I have the same problem, both my train and test are under the same environment.
it works! but the output seems not good
Did you train with the single scan file as the example? I wouldn't expect it to be generalized well. For better generalization, please consider using larger scale dataset.
Did you train with the single scan file as the example? I wouldn't expect it to be generalized well. For better generalization, please consider using larger scale dataset.
yes, I'll try
it works! but the output seems not good
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If you trained the color net following the Readme guidence without adding norm_color option, it will use batch normalization rather than group normalization. So when you test it, you need to delete '--norm_color group' in test.sh, or your test network will be not compatible with the trained model (Error(s) in loading state_dict). Simply adding strict=False may lead to a bad output!
Thank you for your great work. I trained the model with my own data. When I eval with only shape net, there is no problem. But when I eval with both net_G and net_C, errors occurred: RuntimeError: Error(s) in loading state_dict for ResBlkPIFuNet: Missing key(s) in state_dict: "image_filter.model.2.weight", "image_filter.model.2.bias", "image_filter.model.5.weight", "image_filter.model.5.bias", "image_filter.model.8.weight", "image_filter.model.8.bias", "image_filter.model.10.conv_block.2.weight", "image_filter.model.10.conv_block.2.bias", "image_filter.model.10.conv_block.6.weight", "image_filter.model.10.conv_block.6.bias", "image_filter.model.11.conv_block.2.weight", "image_filter.model.11.conv_block.2.bias", "image_filter.model.11.conv_block.6.weight", "image_filter.model.11.conv_block.6.bias", "image_filter.model.12.conv_block.2.weight", "image_filter.model.12.conv_block.2.bias", "image_filter.model.12.conv_block.6.weight", "image_filter.model.12.conv_block.6.bias", "image_filter.model.13.conv_block.2.weight", "image_filter.model.13.conv_block.2.bias", "image_filter.model.13.conv_block.6.weight", "image_filter.model.13.conv_block.6.bias", "image_filter.model.14.conv_block.2.weight", "image_filter.model.14.conv_block.2.bias", "image_filter.model.14.conv_block.6.weight", "image_filter.model.14.conv_block.6.bias", "image_filter.model.15.conv_block.2.weight", "image_filter.model.15.conv_block.2.bias". Unexpected key(s) in state_dict: "image_filter.model.1.bias", "image_filter.model.4.bias", "image_filter.model.7.bias", "image_filter.model.10.conv_block.1.bias", "image_filter.model.10.conv_block.5.bias", "image_filter.model.11.conv_block.1.bias", "image_filter.model.11.conv_block.5.bias", "image_filter.model.12.conv_block.1.bias", "image_filter.model.12.conv_block.5.bias", "image_filter.model.13.conv_block.1.bias", "image_filter.model.13.conv_block.5.bias", "image_filter.model.14.conv_block.1.bias", "image_filter.model.14.conv_block.5.bias", "image_filter.model.15.conv_block.1.bias", "image_filter.model.15.conv_block.5.bias".