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Cannot Load autoencoder_25_squares & Poor Performance on Pre-trained Model #89

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HanXuan-Li opened this issue Jun 27, 2023 · 1 comment

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@HanXuan-Li
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Hello, thanks a lot for sharing.
I want to use the pre-trained autoencoder model to meshing point cloud data(2048 points sampling from ShapeNet). I encountered two problems:

Poor performance on pre-trained autoencoder_1_sphere Model

When I used python train.py --demo --demo_input_path my_pcd.ply --reload_model_path ./training/trained_models/atlasnet_autoencoder_1_sphere/network.pth to generate mesh on my own data, I got this:
image

My data is just like the examples shown in your paper:
image

I also tried to use your data(2ca6df7a5377825cfee773c7de26c274.points.ply) but still got a poor result like this:
image

So I'd like to know if I did something wrong.

Cannot Load autoencoder_25_squares

I used python train.py --demo --demo_input_path my_pcd.ply --reload_model_path ./training/trained_models/atlasnet_autoencoder_25_squares/network.pth to load the autoencoder_25_squares model, but got this:

Loaded compiled 3D CUDA chamfer distance
Launching new HTTP instance in port 8891
TMUX=0 tmux new-session -d -s http_server \; send-keys "/home/lihanxuan/anaconda3/envs/atlasnet/bin/python -m http.server -p 8891 > /dev/null 2>&1" Enter
duplicate session: http_server
Setting up a new session...
/home/lihanxuan/anaconda3/envs/atlasnet/lib/python3.6/site-packages/torchvision/transforms/transforms.py:258: UserWarning: Argument interpolation should be of type InterpolationMode instead of int. Please, use InterpolationMode enum.
  "Argument interpolation should be of type InterpolationMode instead of int. "
New MLP decoder : hidden size 512, num_layers 2, activation relu
Network weights loaded from  ./training/trained_models/atlasnet_autoencoder_25_squares/network.pth!
Traceback (most recent call last):
  File "train.py", line 20, in <module>
    trainer.build_network()
  File "/home/lihanxuan/Project/_AtlasNet/model/trainer_model.py", line 31, in build_network
    self.reload_network()
  File "/home/lihanxuan/Project/_AtlasNet/model/trainer_model.py", line 42, in reload_network
    self.network.module.load_state_dict(torch.load(self.opt.reload_model_path, map_location='cuda:0'))
  File "/home/lihanxuan/anaconda3/envs/atlasnet/lib/python3.6/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 EncoderDecoder:
        Unexpected key(s) in state_dict: "decoder.decoder.1.conv1.weight", "decoder.decoder.1.conv1.bias", "decoder.decoder.1.conv2.weight", "decoder.decoder.1.conv2.bias", "decoder.decoder.1.conv_list.0.weight", "decoder.decoder.1.conv_list.0.bias", "decoder.decoder.1.conv_list.1.weight", "decoder.decoder.1.conv_list.1.bias", "decoder.decoder.1.last_conv.weight", "decoder.decoder.1.last_conv.bias", "decoder.decoder.1.bn1.weight", "decoder.decoder.1.bn1.bias", "decoder.decoder.1.bn1.running_mean", "decoder.decoder.1.bn1.running_var", "decoder.decoder.1.bn1.num_batches_tracked", "decoder.decoder.1.bn2.weight", "decoder.decoder.1.bn2.bias", "decoder.decoder.1.bn2.running_mean", "decoder.decoder.1.bn2.running_var", "decoder.decoder.1.bn2.num_batches_tracked", "decoder.decoder.1.bn_list.0.weight", "decoder.decoder.1.bn_list.0.bias", "decoder.decoder.1.bn_list.0.running_mean", "decoder.decoder.1.bn_list.0.running_var", "decoder.decoder.1.bn_list.0.num_batches_tracked", "decoder.decoder.1.bn_list.1.weight", "decoder.decoder.1.bn_list.1.bias", "decoder.decoder.1.bn_list.1.running_mean", "decoder.decoder.1.bn_list.1.running_var", "decoder.decoder.1.bn_list.1.num_batches_tracked", "decoder.decoder.2.conv1.weight", "decoder.decoder.2.conv1.bias", "decoder.decoder.2.conv2.weight", "decoder.decoder.2.conv2.bias", "decoder.decoder.2.conv_list.0.weight", "decoder.decoder.2.conv_list.0.bias", "decoder.decoder.2.conv_list.1.weight", "decoder.decoder.2.conv_list.1.bias", "decoder.decoder.2.last_conv.weight", "decoder.decoder.2.last_conv.bias", "decoder.decoder.2.bn1.weight", "decoder.decoder.2.bn1.bias", "decoder.decoder.2.bn1.running_mean", "decoder.decoder.2.bn1.running_var", "decoder.decoder.2.bn1.num_batches_tracked", "decoder.decoder.2.bn2.weight", "decoder.decoder.2.bn2.bias", "decoder.decoder.2.bn2.running_mean", "decoder.decoder.2.bn2.running_var", "decoder.decoder.2.bn2.num_batches_tracked", "decoder.decoder.2.bn_list.0.weight", 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        size mismatch for decoder.decoder.0.conv1.weight: copying a param with shape torch.Size([1024, 2, 1]) from checkpoint, the shape in current model is torch.Size([1024, 3, 1]).
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kuwan2e commented Jul 17, 2023

Hello . I met the same problem. And I found how to solve it.
For autoencoder_25_squares, you need to use --dir_name {PATH_TO_autoencoder_25_squares}

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