albanie / pytorch-mcn Goto Github PK

When I imports the trained MatConvNet model https://pan.baidu.com/s/1kWpxAtT into Pytorch, which is trained with code https://github.com/layumi/Pedestrian_Alignment , it get the error as follow: can you import it, verify and public it on your web?
importing net-epoch-23
flattening at
Exporting MatConvNet model to PyTorch (may take some time)...
File "/home/chengzi/pytorch-mcn/python/importer.py", line 277
arch = sg.build_header_str(self.name, **self.meta, debug_mode=self.debug_mode)
^
SyntaxError: invalid syntax

Dear Professor,

I could not download the pre-trianed models now.
Could you update the links?
I need the model named vgg_face_dag.pth.

Thanks,
Chawdoe

I am trying to load the ICLabel model in PyTorch, named netICL.mat. Opening the model in Matlab, I can see that the argument meta is empty.

Thus, the converter is failing in build_network on line 537:

normalization = mcn_net['meta']['normalization']

How can I solve this?

*** SyntaxError: invalid syntax
> /home/gece/Workspace/pytorch-mcn/python/importer.py(239)extract_dag()
    238         else: import ipdb ; ipdb.set_trace()
--> 239         for output, out_ch in zip(node['outputs'], out_chs):
    240             in_ch_store[output] = out_ch

ipdb>

I got the above error when trying to convert imagenet-vgg-f and imagenet-vgg-m-1024. I have already converted them to dags using ensure_dags.m.
( I use python3.5, and I can convert imagenet-vgg-verydeep-16 successfully )

I am new in DeepLearning and trying to convert a pre-trained net from matconvnet to pytorch.
The matconvnet version is 1.0-beta13, i re-saved it in matlab with -v7.
When i run the script it says:
"for key in ['meta','params','layers']: assert key in mcn.keys()" in "...../pytorch-mcn/python/importer.py", line 49, in load_mcn_net

Can anyone teach how to use the lib?
The list of example net is a list of complicated models like "vgg,Alex..." ,but i only need to convert a simple net with only conv and relu and concat.
I download the pre-trained model here
https://github.com/Yijunmaverick/DeepJointFilter/tree/master/examples/Test/Upsampling_8x.mat

It seems that, the magenet_mcn_vgg_m in your pre-convert model is the vgg-m with BN. Now, the pytorch supply the LRN, could you please supply the pre-convert model of vgg-m-2048 without BatchNorm but with LRN?

Steps for Convert models from MatConvNet to PyTorch with pytorch-mcn
(1)run pytorch-mcn/compare/ensure_dags.m in matlab to convert models to dagnn...
(2)edit and run shell script importer.sh to Convert models from MatConvNet to PyTorch with pytorch-mcn
(3)the results
Saving imported model definition to ./models/resnext_50_32x4d_pt_mcn.py
Saving imported weights to ./models/resnext_50_32x4d_pt_mcn.pth

Bugs?
(1)Due to the default Python is 2.7 on the most Linux OS, and Python3 means Python3.5 on the the most Linux OS. Thus, I suggest change the python/ipython to python3/ipython3 for using Python3.5 obviously in importer.sh.
(2) The waning "skipping conv bias term"
skipping conv bias term
skipping conv bias term
skipping conv bias term
skipping conv bias term
skipping conv bias term
(3) Errors
> /home/chengzi/Downloads/pytorch-mcn/python/ptmcn_utils.py(66)conv2d_mod()
65 if not valid_conv_groups: import ipdb ; ipdb.set_trace()
---> 66 assert valid_conv_groups, msg
67 num_groups = int(in_ch / fsize[2])

I have download the "imagenet_mcn_vgg_m (weights)", how can I use it in pytorch? And, what the mean and var is of the input image?