no images are printed。。

[stoneshi-1999]

Thank u so much in advance❤❤❤After I set the dataset as u say , then I run the demo , no error but no images are printed...

Here's the warnings, I tried to change align_corners=False to align_corners=True in .\torch\nn\functional.py , but it's useless...

C:\Users\75643\miniconda3\envs\gfla\lib\site-packages\torch\nn\functional.py:3636: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
  "See the documentation of nn.Upsample for details.".format(mode)
C:\Users\75643\miniconda3\envs\gfla\lib\site-packages\torch\nn\functional.py:4007: UserWarning: Default grid_sample and affine_grid behavior has changed to align_corners=False since 1.3.0. Please specify align_corners=True if the old behavior is desired. See the documentation of grid_sample for details.
  "Default grid_sample and affine_grid behavior has changed "
C:\Users\75643\Desktop\0postgraduate\1paper\0_DiOr_repo\dressing-in-order-main\utils\pose_utils.py:91: FutureWarning: circle is deprecated in favor of disk.circle will be removed in version 0.19
  yy, xx = circle(joint[0], joint[1], radius=radius, shape=img_size)
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).

[stoneshi-1999]

And after I run 'pose transfer' block , when I run 'try-on' , I will met this error.

Run time error: CUDA out of memory. Tried to allocate 20.00 MiB (GPU 0: 6.00 GiB total capacity: 3.62 GiB already allocated: 0 bytes free: 3.72 GiB reserved in total by Pytorch )If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF

Here's my Chip, maybe the memory is not enough for the Demo? (T_T)

Chip type: NVIDIA geforce rtx3060 laptop GPU DAC type: integrated RAMDAC Device off type: complete display device Total memory: about 22278mb Display memory (VRAM): 6023mb Shared memory: 16255mb

[cuiaiyu]

for Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers)., check if you have image array in right type and range. As the error indicated, the image array should have [0..1] for floats or [0..255] for integers).

For memory, it should be fine for 256x176. Please check Nvidia-smi to see if there is anything else occupying the memory. Thanks.

[dubbie12]

Thank u so much in advance❤❤❤After I set the dataset as u say , then I run the demo , no error but no images are printed...

Here's the warnings, I tried to change align_corners=False to align_corners=True in .\torch\nn\functional.py , but it's useless...

C:\Users\75643\miniconda3\envs\gfla\lib\site-packages\torch\nn\functional.py:3636: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
  "See the documentation of nn.Upsample for details.".format(mode)
C:\Users\75643\miniconda3\envs\gfla\lib\site-packages\torch\nn\functional.py:4007: UserWarning: Default grid_sample and affine_grid behavior has changed to align_corners=False since 1.3.0. Please specify align_corners=True if the old behavior is desired. See the documentation of grid_sample for details.
  "Default grid_sample and affine_grid behavior has changed "
C:\Users\75643\Desktop\0postgraduate\1paper\0_DiOr_repo\dressing-in-order-main\utils\pose_utils.py:91: FutureWarning: circle is deprecated in favor of disk.circle will be removed in version 0.19
  yy, xx = circle(joint[0], joint[1], radius=radius, shape=img_size)
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).

I have the same problem. How did you resolve it?

[netsalesbg-ltd]

Must use scikit-image<=1.18. They removed old deprecation, and renamed some functions one of which circle was renamed to disk. Or if you need the newer version of scikit-image, you should refactor the code to change all circle function calls to disk.