Dimension Mismatch Issue in running on local pc

[ujjawalcse]

Hey @YuliangXiu ,
I tried to setup the complete dependency on my Ubuntu 18.04 PC (pytorch 1.6,Cuda 10.1) with all the dependencies in the requirements.txt one by one.
Actually faced a lot of issues in the above procedure.
After that I was getting issue in loading model in rembg module. So I manually downloaded the model file
and modified the rembg accordingly. It takes corrected the process_image function in lib/pymaf/utils/imutils.py.

This produces hps_img having shape [3,224,224] in my case, that is being further fed to pymaf_net.py in line 282
to extract features using the defined backbone (res50).
But this backbone expects input size as [64, 3, 7, 7].
And that's why i'm getting dimension mismatch runtime error.

Note:- I have modified the image_to_pymaf_tensor in get_transformer() from lib/pymaf/utils/imutils.py as per my pytorch version .

image_to_pymaf_tensor = transforms.Compose([
        transforms.ToPILImage(),                   #Added by us
        transforms.Resize(224),
        transforms.ToTensor(),                     #Added by us
        transforms.Normalize(mean=constants.IMG_NORM_MEAN,
                             std=constants.IMG_NORM_STD)
    ])

ICON:
[w/ Global Image Encoder]: True
[Image Features used by MLP]: ['normal_F', 'normal_B']
[Geometry Features used by MLP]: ['sdf', 'norm', 'vis', 'cmap']
[Dim of Image Features (local)]: 6
[Dim of Geometry Features (ICON)]: 7
[Dim of MLP's first layer]: 13

initialize network with xavier
initialize network with xavier
Resume MLP weights from ../data/ckpt/icon-filter.ckpt
Resume normal model from ../data/ckpt/normal.ckpt
Using cache found in /home/ujjawal/.cache/torch/hub/NVIDIA_DeepLearningExamples_torchhub
Using cache found in /home/ujjawal/.cache/torch/hub/NVIDIA_DeepLearningExamples_torchhub
Dataset Size: 2
  0%|                                                                                                                                             | 0/2 [00:00<?, ?it/s]*********************************
img_np shape: (512, 512, 3)
img_hps shape: torch.Size([3, 224, 224])
input shape x in pymaf_net : torch.Size([3, 224, 224])
input shape x in hmr : torch.Size([3, 224, 224])
  0%|                                                                                                                                             | 0/2 [00:01<?, ?it/s]
Traceback (most recent call last):
  File "infer.py", line 97, in <module>
    for data in pbar:
  File "/home/ujjawal/miniconda2/envs/caffe2/lib/python3.7/site-packages/tqdm/std.py", line 1130, in __iter__
    for obj in iterable:
  File "../lib/dataset/TestDataset.py", line 166, in __getitem__
    preds_dict = self.hps(img_hps.to(self.device))
  File "/home/ujjawal/miniconda2/envs/caffe2/lib/python3.7/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
    result = self.forward(*input, **kwargs)
  File "../lib/pymaf/models/pymaf_net.py", line 285, in forward
    s_feat, g_feat = self.feature_extractor(x)
  File "/home/ujjawal/miniconda2/envs/caffe2/lib/python3.7/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
    result = self.forward(*input, **kwargs)
  File "../lib/pymaf/models/hmr.py", line 159, in forward
    x = self.conv1(x)
  File "/home/ujjawal/miniconda2/envs/caffe2/lib/python3.7/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/ujjawal/miniconda2/envs/caffe2/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 419, in forward
    return self._conv_forward(input, self.weight)
  File "/home/ujjawal/miniconda2/envs/caffe2/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 416, in _conv_forward
    self.padding, self.dilation, self.groups)
RuntimeError: Expected 4-dimensional input for 4-dimensional weight [64, 3, 7, 7], but got 3-dimensional input of size [3, 224, 224] instead

Please suggest your view on the same.

[YuliangXiu]

I just updated the installation scripts and specified the versions in requirements.txt, colab can work well for now.

You could do git pull and try again.

[ujjawalcse]

Thanks @YuliangXiu
Now working fine on colab. Will try it on local also.
Can you tell how to get the animated clothed model that is mentioned in the readme?

[YuliangXiu]

Please see #17

[ujjawalcse]

Thanks for your suggestion.
Closing the issue.