liudakai2 / UnsupDIS-pytorch

A pytorch implementation of UnsupervisedDeepImageStitching
GNU General Public License v3.0
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Issue of generating coarse aligned results on UDIS testing data #46

Open tlliao opened 6 months ago

tlliao commented 6 months ago

Hi there! Thanks for the great work!

Trying to run on UDIS testing data to generate coarse aligned results, but failing with the following error, what I'm doing wrong?


Namespace(device='0', exist_ok=False, half=False, img_size=512, name='exp', project='runs/infer', rmse=False, source='data/udis.yaml', task='test', visualize=False, weights=['weights/align/udis_align_variant.pt'])
CUDA:0 (NVIDIA GeForce RTX 3090, 24259.6875MB)

Fusing layers... 
No module named 'thop'
Model Summary: 100 layers, 10181056 parameters, 0 gradients
0it [00:00, ?it/s]
Traceback (most recent call last):
  File "inference_align.py", line 176, in <module>
    infer()
  File "/home/x/anaconda3/envs/udis2/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 26, in decorate_context
    return func(*args, **kwargs)
  File "inference_align.py", line 100, in infer
    vertices_offsets, warped_imgs, warped_ones = model(imgs)
  File "/home/x/anaconda3/envs/udis2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/mnt/cv_liao_DL/UnsupDIS-pytorch/models/yolo.py", line 329, in forward
    return self.model[-1](feature1, feature2, x2, m2)
  File "/home/x/anaconda3/envs/udis2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/mnt/cv_liao_DL/UnsupDIS-pytorch/models/yolo.py", line 141, in forward
    off = self.m[i](x).unsqueeze(-1)  # [bs, 8, 1], for matrix multiplication
  File "/home/x/anaconda3/envs/udis2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/x/anaconda3/envs/udis2/lib/python3.8/site-packages/torch/nn/modules/container.py", line 117, in forward
    input = module(input)
  File "/home/x/anaconda3/envs/udis2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 727, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/x/anaconda3/envs/udis2/lib/python3.8/site-packages/torch/nn/modules/linear.py", line 93, in forward
    return F.linear(input, self.weight, self.bias)
  File "/home/x/anaconda3/envs/udis2/lib/python3.8/site-packages/torch/nn/functional.py", line 1690, in linear
    ret = torch.addmm(bias, input, weight.t())
**RuntimeError: mat1 dim 1 must match mat2 dim 0**```