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/content/photo_restoration
Running Stage 1: Overall restoration
initializing the dataloader
model weights loaded
directory of testing image: /content/photo_restoration/test_images/old
processing .ipynb_checkpoints
Skipping non-file .ipynb_checkpoints
processing a.png
Traceback (most recent call last):
File "/content/photo_restoration/Global/detection.py", line 178, in
main(config)
File "/content/photo_restoration/Global/detection.py", line 132, in main
scratch_image = Image.open(scratch_file).convert("RGB")
File "/usr/local/lib/python3.9/dist-packages/PIL/Image.py", line 3030, in open
raise UnidentifiedImageError(
PIL.UnidentifiedImageError: cannot identify image file '/content/photo_restoration/test_images/old/a.png'
You are using NL + Res
Finish Stage 1 ...
Running Stage 2: Face Detection
Finish Stage 2 ...
Running Stage 3: Face Enhancement
The main GPU is
0
dataset [FaceTestDataset] of size 0 was created
The size of the latent vector size is [8,8]
Network [SPADEGenerator] was created. Total number of parameters: 92.1 million. To see the architecture, do print(network).
hi :)
Finish Stage 3 ...
Running Stage 4: Blending
Finish Stage 4 ...
All the processing is done. Please check the results.
The text was updated successfully, but these errors were encountered:
/content/photo_restoration
Running Stage 1: Overall restoration
initializing the dataloader
model weights loaded
directory of testing image: /content/photo_restoration/test_images/old
processing .ipynb_checkpoints
Skipping non-file .ipynb_checkpoints
processing a.png
Traceback (most recent call last):
File "/content/photo_restoration/Global/detection.py", line 178, in
main(config)
File "/content/photo_restoration/Global/detection.py", line 132, in main
scratch_image = Image.open(scratch_file).convert("RGB")
File "/usr/local/lib/python3.9/dist-packages/PIL/Image.py", line 3030, in open
raise UnidentifiedImageError(
PIL.UnidentifiedImageError: cannot identify image file '/content/photo_restoration/test_images/old/a.png'
You are using NL + Res
Finish Stage 1 ...
Running Stage 2: Face Detection
Finish Stage 2 ...
Running Stage 3: Face Enhancement
The main GPU is
0
dataset [FaceTestDataset] of size 0 was created
The size of the latent vector size is [8,8]
Network [SPADEGenerator] was created. Total number of parameters: 92.1 million. To see the architecture, do print(network).
hi :)
Finish Stage 3 ...
Running Stage 4: Blending
Finish Stage 4 ...
All the processing is done. Please check the results.
The text was updated successfully, but these errors were encountered: