TencentARC/GFPGAN
1
0
Fork 0
mirror of https://github.com/TencentARC/GFPGAN.git synced 2026-02-14 13:24:36 +00:00
Code Issues 476 Packages Projects Releases 8 Wiki Activity

I can't use GFPGANv1.pth #46

New Issue
Closed
opened 2026-01-29 21:39:31 +00:00 by claunia · 2 comments
claunia commented 2026-01-29 21:39:31 +00:00
Owner
Copy Link

Originally created by @paconaranjo on GitHub (Aug 12, 2021).

I already use GFPGANCleanv1-NoCE-C2.pth and is working great. Please help me with this problem...

Thanks.

python inference_gfpgan.py --upscale 2 --model_path experiments/pretrained_models/GFPGANv1.pth --test_path inputs/whole_imgs --save_root results

inference_gfpgan.py:37: UserWarning: The unoptimized RealESRGAN is very slow on CPU. We do not use it. If you really want to use it, please modify the corresponding codes.
  warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. '
Traceback (most recent call last):
  File "inference_gfpgan.py", line 98, in <module>
    main()
  File "inference_gfpgan.py", line 52, in main
    restorer = GFPGANer(
  File "C:\Users\Zeus\Downloads\GFPGAN\gfpgan\utils.py", line 65, in __init__
    self.gfpgan.load_state_dict(loadnet[keyname], strict=True)
  File "C:\Users\Zeus\anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1406, in load_state_dict
    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for GFPGANv1Clean:
        Missing key(s) in state_dict: "conv_body_first.weight", "conv_body_first.bias", "conv_body_down.0.conv1.weight", "conv_body_down.0.conv1.bias", "conv_body_down.0.conv2.weight", "conv_body_down.0.conv2.bias", "conv_body_down.0.skip.weight", "conv_body_down.1.conv1.weight", "conv_body_down.1.conv1.bias", "conv_body_down.1.conv2.weight", "conv_body_down.1.conv2.bias", "conv_body_down.1.skip.weight", "conv_body_down.2.conv1.weight", "conv_body_down.2.conv1.bias", "conv_body_down.2.conv2.weight", "conv_body_down.2.conv2.bias", "conv_body_down.2.skip.weight", "conv_body_down.3.conv1.weight", "conv_body_down.3.conv1.bias", "conv_body_down.3.conv2.weight", "conv_body_down.3.conv2.bias", "conv_body_down.3.skip.weight", "conv_body_down.4.conv1.weight", "conv_body_down.4.conv1.bias", "conv_body_down.4.conv2.weight", "conv_body_down.4.conv2.bias", "conv_body_down.4.skip.weight", "conv_body_down.5.conv1.weight", "conv_body_down.5.conv1.bias", "conv_body_down.5.conv2.weight", "conv_body_down.5.conv2.bias", "conv_body_down.5.skip.weight", "conv_body_down.6.conv1.weight", "conv_body_down.6.conv1.bias", "conv_body_down.6.conv2.weight", "conv_body_down.6.conv2.bias", "conv_body_down.6.skip.weight", "final_conv.weight", "final_conv.bias", "conv_body_up.0.conv1.weight", "conv_body_up.0.conv1.bias", "conv_body_up.0.conv2.bias", "conv_body_up.1.conv1.weight", "conv_body_up.1.conv1.bias", "conv_body_up.1.conv2.bias", "conv_body_up.2.conv1.weight", "conv_body_up.2.conv1.bias", "conv_body_up.2.conv2.bias", "conv_body_up.3.conv1.weight", "conv_body_up.3.conv1.bias", "conv_body_up.3.conv2.bias", "conv_body_up.4.conv1.weight", "conv_body_up.4.conv1.bias", "conv_body_up.4.conv2.bias", "conv_body_up.5.conv1.weight", "conv_body_up.5.conv1.bias", "conv_body_up.5.conv2.bias", "conv_body_up.6.conv1.weight", "conv_body_up.6.conv1.bias", "conv_body_up.6.conv2.bias", "stylegan_decoder.style_mlp.9.weight", "stylegan_decoder.style_mlp.9.bias", "stylegan_decoder.style_mlp.11.weight", "stylegan_decoder.style_mlp.11.bias", "stylegan_decoder.style_mlp.13.weight", "stylegan_decoder.style_mlp.13.bias", "stylegan_decoder.style_mlp.15.weight", "stylegan_decoder.style_mlp.15.bias", "stylegan_decoder.style_conv1.bias", "stylegan_decoder.style_convs.0.bias", "stylegan_decoder.style_convs.1.bias", "stylegan_decoder.style_convs.2.bias", "stylegan_decoder.style_convs.3.bias", "stylegan_decoder.style_convs.4.bias", "stylegan_decoder.style_convs.5.bias", "stylegan_decoder.style_convs.6.bias", "stylegan_decoder.style_convs.7.bias", "stylegan_decoder.style_convs.8.bias", "stylegan_decoder.style_convs.9.bias", "stylegan_decoder.style_convs.10.bias", "stylegan_decoder.style_convs.11.bias", "stylegan_decoder.style_convs.12.bias", "stylegan_decoder.style_convs.13.bias".
        Unexpected key(s) in state_dict: "conv_body_first.0.weight", "conv_body_first.1.bias", "conv_body_down.0.conv1.0.weight", "conv_body_down.0.conv1.1.bias", "conv_body_down.0.conv2.1.weight", "conv_body_down.0.conv2.2.bias", "conv_body_down.0.skip.1.weight", "conv_body_down.1.conv1.0.weight", "conv_body_down.1.conv1.1.bias", "conv_body_down.1.conv2.1.weight", "conv_body_down.1.conv2.2.bias", "conv_body_down.1.skip.1.weight", "conv_body_down.2.conv1.0.weight", "conv_body_down.2.conv1.1.bias", "conv_body_down.2.conv2.1.weight", "conv_body_down.2.conv2.2.bias", "conv_body_down.2.skip.1.weight", "conv_body_down.3.conv1.0.weight", "conv_body_down.3.conv1.1.bias", "conv_body_down.3.conv2.1.weight", "conv_body_down.3.conv2.2.bias", "conv_body_down.3.skip.1.weight", "conv_body_down.4.conv1.0.weight", "conv_body_down.4.conv1.1.bias", "conv_body_down.4.conv2.1.weight", "conv_body_down.4.conv2.2.bias", "conv_body_down.4.skip.1.weight", "conv_body_down.5.conv1.0.weight", "conv_body_down.5.conv1.1.bias", "conv_body_down.5.conv2.1.weight", "conv_body_down.5.conv2.2.bias", "conv_body_down.5.skip.1.weight", "conv_body_down.6.conv1.0.weight", "conv_body_down.6.conv1.1.bias", "conv_body_down.6.conv2.1.weight", "conv_body_down.6.conv2.2.bias", "conv_body_down.6.skip.1.weight", "final_conv.0.weight", "final_conv.1.bias", "conv_body_up.0.conv1.0.weight", "conv_body_up.0.conv1.1.bias", "conv_body_up.0.conv2.activation.bias", "conv_body_up.1.conv1.0.weight", "conv_body_up.1.conv1.1.bias", "conv_body_up.1.conv2.activation.bias", "conv_body_up.2.conv1.0.weight", "conv_body_up.2.conv1.1.bias", "conv_body_up.2.conv2.activation.bias", "conv_body_up.3.conv1.0.weight", "conv_body_up.3.conv1.1.bias", "conv_body_up.3.conv2.activation.bias", "conv_body_up.4.conv1.0.weight", "conv_body_up.4.conv1.1.bias", "conv_body_up.4.conv2.activation.bias", "conv_body_up.5.conv1.0.weight", "conv_body_up.5.conv1.1.bias", "conv_body_up.5.conv2.activation.bias", "conv_body_up.6.conv1.0.weight", "conv_body_up.6.conv1.1.bias", "conv_body_up.6.conv2.activation.bias", "stylegan_decoder.style_mlp.2.weight", "stylegan_decoder.style_mlp.2.bias", "stylegan_decoder.style_mlp.4.weight", "stylegan_decoder.style_mlp.4.bias", "stylegan_decoder.style_mlp.6.weight", "stylegan_decoder.style_mlp.6.bias", "stylegan_decoder.style_mlp.8.weight", "stylegan_decoder.style_mlp.8.bias", "stylegan_decoder.style_conv1.activate.bias", "stylegan_decoder.style_convs.0.activate.bias", "stylegan_decoder.style_convs.1.activate.bias", "stylegan_decoder.style_convs.2.activate.bias", "stylegan_decoder.style_convs.3.activate.bias", "stylegan_decoder.style_convs.4.activate.bias", "stylegan_decoder.style_convs.5.activate.bias", "stylegan_decoder.style_convs.6.activate.bias", "stylegan_decoder.style_convs.7.activate.bias", "stylegan_decoder.style_convs.8.activate.bias", "stylegan_decoder.style_convs.9.activate.bias", "stylegan_decoder.style_convs.10.activate.bias", "stylegan_decoder.style_convs.11.activate.bias", "stylegan_decoder.style_convs.12.activate.bias", "stylegan_decoder.style_convs.13.activate.bias".
        size mismatch for conv_body_up.3.conv2.weight: copying a param with shape torch.Size([128, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for conv_body_up.3.skip.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 256, 1, 1]).
        size mismatch for conv_body_up.4.conv2.weight: copying a param with shape torch.Size([64, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 256, 3, 3]).
        size mismatch for conv_body_up.4.skip.weight: copying a param with shape torch.Size([64, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 256, 1, 1]).
        size mismatch for conv_body_up.5.conv2.weight: copying a param with shape torch.Size([32, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 128, 3, 3]).
        size mismatch for conv_body_up.5.skip.weight: copying a param with shape torch.Size([32, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 128, 1, 1]).
        size mismatch for conv_body_up.6.conv2.weight: copying a param with shape torch.Size([16, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 64, 3, 3]).
        size mismatch for conv_body_up.6.skip.weight: copying a param with shape torch.Size([16, 32, 1, 1]) from checkpoint, the shape in current model is torch.Size([32, 64, 1, 1]).
        size mismatch for toRGB.3.weight: copying a param with shape torch.Size([3, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 256, 1, 1]).
        size mismatch for toRGB.4.weight: copying a param with shape torch.Size([3, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 128, 1, 1]).
        size mismatch for toRGB.5.weight: copying a param with shape torch.Size([3, 32, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 64, 1, 1]).
        size mismatch for toRGB.6.weight: copying a param with shape torch.Size([3, 16, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 32, 1, 1]).
        size mismatch for stylegan_decoder.style_convs.6.modulated_conv.weight: copying a param with shape torch.Size([1, 256, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 512, 512, 3, 3]).
        size mismatch for stylegan_decoder.style_convs.7.modulated_conv.weight: copying a param with shape torch.Size([1, 256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 512, 512, 3, 3]).
        size mismatch for stylegan_decoder.style_convs.7.modulated_conv.modulation.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]).
        size mismatch for stylegan_decoder.style_convs.7.modulated_conv.modulation.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for stylegan_decoder.style_convs.8.modulated_conv.weight: copying a param with shape torch.Size([1, 128, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 256, 512, 3, 3]).
        size mismatch for stylegan_decoder.style_convs.8.modulated_conv.modulation.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]).
        size mismatch for stylegan_decoder.style_convs.8.modulated_conv.modulation.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for stylegan_decoder.style_convs.9.modulated_conv.weight: copying a param with shape torch.Size([1, 128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 256, 256, 3, 3]).
        size mismatch for stylegan_decoder.style_convs.9.modulated_conv.modulation.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
        size mismatch for stylegan_decoder.style_convs.9.modulated_conv.modulation.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for stylegan_decoder.style_convs.10.modulated_conv.weight: copying a param with shape torch.Size([1, 64, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 128, 256, 3, 3]).
        size mismatch for stylegan_decoder.style_convs.10.modulated_conv.modulation.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
        size mismatch for stylegan_decoder.style_convs.10.modulated_conv.modulation.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for stylegan_decoder.style_convs.11.modulated_conv.weight: copying a param with shape torch.Size([1, 64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 128, 128, 3, 3]).
        size mismatch for stylegan_decoder.style_convs.11.modulated_conv.modulation.weight: copying a param with shape torch.Size([64, 512]) from checkpoint, the shape in current model is torch.Size([128, 512]).
        size mismatch for stylegan_decoder.style_convs.11.modulated_conv.modulation.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
        size mismatch for stylegan_decoder.style_convs.12.modulated_conv.weight: copying a param with shape torch.Size([1, 32, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 64, 128, 3, 3]).
        size mismatch for stylegan_decoder.style_convs.12.modulated_conv.modulation.weight: copying a param with shape torch.Size([64, 512]) from checkpoint, the shape in current model is torch.Size([128, 512]).
        size mismatch for stylegan_decoder.style_convs.12.modulated_conv.modulation.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
        size mismatch for stylegan_decoder.style_convs.13.modulated_conv.weight: copying a param with shape torch.Size([1, 32, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 64, 64, 3, 3]).
        size mismatch for stylegan_decoder.style_convs.13.modulated_conv.modulation.weight: copying a param with shape torch.Size([32, 512]) from checkpoint, the shape in current model is torch.Size([64, 512]).
        size mismatch for stylegan_decoder.style_convs.13.modulated_conv.modulation.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
        size mismatch for stylegan_decoder.to_rgbs.3.modulated_conv.weight: copying a param with shape torch.Size([1, 3, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 3, 512, 1, 1]).
        size mismatch for stylegan_decoder.to_rgbs.3.modulated_conv.modulation.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]).
        size mismatch for stylegan_decoder.to_rgbs.3.modulated_conv.modulation.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]).
        size mismatch for stylegan_decoder.to_rgbs.4.modulated_conv.weight: copying a param with shape torch.Size([1, 3, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 3, 256, 1, 1]).
        size mismatch for stylegan_decoder.to_rgbs.4.modulated_conv.modulation.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]).
        size mismatch for stylegan_decoder.to_rgbs.4.modulated_conv.modulation.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for stylegan_decoder.to_rgbs.5.modulated_conv.weight: copying a param with shape torch.Size([1, 3, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 3, 128, 1, 1]).
        size mismatch for stylegan_decoder.to_rgbs.5.modulated_conv.modulation.weight: copying a param with shape torch.Size([64, 512]) from checkpoint, the shape in current model is torch.Size([128, 512]).
        size mismatch for stylegan_decoder.to_rgbs.5.modulated_conv.modulation.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
        size mismatch for stylegan_decoder.to_rgbs.6.modulated_conv.weight: copying a param with shape torch.Size([1, 3, 32, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 3, 64, 1, 1]).
        size mismatch for stylegan_decoder.to_rgbs.6.modulated_conv.modulation.weight: copying a param with shape torch.Size([32, 512]) from checkpoint, the shape in current model is torch.Size([64, 512]).
        size mismatch for stylegan_decoder.to_rgbs.6.modulated_conv.modulation.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
        size mismatch for condition_scale.3.0.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for condition_scale.3.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for condition_scale.3.2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for condition_scale.3.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for condition_scale.4.0.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
        size mismatch for condition_scale.4.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
        size mismatch for condition_scale.4.2.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
        size mismatch for condition_scale.4.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
        size mismatch for condition_scale.5.0.weight: copying a param with shape torch.Size([32, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
        size mismatch for condition_scale.5.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
        size mismatch for condition_scale.5.2.weight: copying a param with shape torch.Size([32, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
        size mismatch for condition_scale.5.2.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
        size mismatch for condition_scale.6.0.weight: copying a param with shape torch.Size([16, 16, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]).
        size mismatch for condition_scale.6.0.bias: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([32]).
        size mismatch for condition_scale.6.2.weight: copying a param with shape torch.Size([16, 16, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]).
        size mismatch for condition_scale.6.2.bias: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([32]).
        size mismatch for condition_shift.3.0.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for condition_shift.3.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for condition_shift.3.2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]).
        size mismatch for condition_shift.3.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]).
        size mismatch for condition_shift.4.0.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
        size mismatch for condition_shift.4.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
        size mismatch for condition_shift.4.2.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]).
        size mismatch for condition_shift.4.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]).
        size mismatch for condition_shift.5.0.weight: copying a param with shape torch.Size([32, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
        size mismatch for condition_shift.5.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
        size mismatch for condition_shift.5.2.weight: copying a param with shape torch.Size([32, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]).
        size mismatch for condition_shift.5.2.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]).
        size mismatch for condition_shift.6.0.weight: copying a param with shape torch.Size([16, 16, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]).
        size mismatch for condition_shift.6.0.bias: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([32]).
        size mismatch for condition_shift.6.2.weight: copying a param with shape torch.Size([16, 16, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]).
        size mismatch for condition_shift.6.2.bias: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([32]).
Originally created by @paconaranjo on GitHub (Aug 12, 2021). I already use GFPGANCleanv1-NoCE-C2.pth and is working great. Please help me with this problem... Thanks. python inference_gfpgan.py --upscale 2 --model_path experiments/pretrained_models/GFPGANv1.pth --test_path inputs/whole_imgs --save_root results ``` inference_gfpgan.py:37: UserWarning: The unoptimized RealESRGAN is very slow on CPU. We do not use it. If you really want to use it, please modify the corresponding codes. warnings.warn('The unoptimized RealESRGAN is very slow on CPU. We do not use it. ' Traceback (most recent call last): File "inference_gfpgan.py", line 98, in <module> main() File "inference_gfpgan.py", line 52, in main restorer = GFPGANer( File "C:\Users\Zeus\Downloads\GFPGAN\gfpgan\utils.py", line 65, in __init__ self.gfpgan.load_state_dict(loadnet[keyname], strict=True) File "C:\Users\Zeus\anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1406, in load_state_dict raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for GFPGANv1Clean: Missing key(s) in state_dict: "conv_body_first.weight", "conv_body_first.bias", "conv_body_down.0.conv1.weight", "conv_body_down.0.conv1.bias", "conv_body_down.0.conv2.weight", "conv_body_down.0.conv2.bias", "conv_body_down.0.skip.weight", "conv_body_down.1.conv1.weight", "conv_body_down.1.conv1.bias", "conv_body_down.1.conv2.weight", "conv_body_down.1.conv2.bias", "conv_body_down.1.skip.weight", "conv_body_down.2.conv1.weight", "conv_body_down.2.conv1.bias", "conv_body_down.2.conv2.weight", "conv_body_down.2.conv2.bias", "conv_body_down.2.skip.weight", "conv_body_down.3.conv1.weight", "conv_body_down.3.conv1.bias", "conv_body_down.3.conv2.weight", "conv_body_down.3.conv2.bias", "conv_body_down.3.skip.weight", "conv_body_down.4.conv1.weight", "conv_body_down.4.conv1.bias", "conv_body_down.4.conv2.weight", "conv_body_down.4.conv2.bias", "conv_body_down.4.skip.weight", "conv_body_down.5.conv1.weight", "conv_body_down.5.conv1.bias", "conv_body_down.5.conv2.weight", "conv_body_down.5.conv2.bias", "conv_body_down.5.skip.weight", "conv_body_down.6.conv1.weight", "conv_body_down.6.conv1.bias", "conv_body_down.6.conv2.weight", "conv_body_down.6.conv2.bias", "conv_body_down.6.skip.weight", "final_conv.weight", "final_conv.bias", "conv_body_up.0.conv1.weight", "conv_body_up.0.conv1.bias", "conv_body_up.0.conv2.bias", "conv_body_up.1.conv1.weight", "conv_body_up.1.conv1.bias", "conv_body_up.1.conv2.bias", "conv_body_up.2.conv1.weight", "conv_body_up.2.conv1.bias", "conv_body_up.2.conv2.bias", "conv_body_up.3.conv1.weight", "conv_body_up.3.conv1.bias", "conv_body_up.3.conv2.bias", "conv_body_up.4.conv1.weight", "conv_body_up.4.conv1.bias", "conv_body_up.4.conv2.bias", "conv_body_up.5.conv1.weight", "conv_body_up.5.conv1.bias", "conv_body_up.5.conv2.bias", "conv_body_up.6.conv1.weight", "conv_body_up.6.conv1.bias", "conv_body_up.6.conv2.bias", "stylegan_decoder.style_mlp.9.weight", "stylegan_decoder.style_mlp.9.bias", "stylegan_decoder.style_mlp.11.weight", "stylegan_decoder.style_mlp.11.bias", "stylegan_decoder.style_mlp.13.weight", "stylegan_decoder.style_mlp.13.bias", "stylegan_decoder.style_mlp.15.weight", "stylegan_decoder.style_mlp.15.bias", "stylegan_decoder.style_conv1.bias", "stylegan_decoder.style_convs.0.bias", "stylegan_decoder.style_convs.1.bias", "stylegan_decoder.style_convs.2.bias", "stylegan_decoder.style_convs.3.bias", "stylegan_decoder.style_convs.4.bias", "stylegan_decoder.style_convs.5.bias", "stylegan_decoder.style_convs.6.bias", "stylegan_decoder.style_convs.7.bias", "stylegan_decoder.style_convs.8.bias", "stylegan_decoder.style_convs.9.bias", "stylegan_decoder.style_convs.10.bias", "stylegan_decoder.style_convs.11.bias", "stylegan_decoder.style_convs.12.bias", "stylegan_decoder.style_convs.13.bias". Unexpected key(s) in state_dict: "conv_body_first.0.weight", "conv_body_first.1.bias", "conv_body_down.0.conv1.0.weight", "conv_body_down.0.conv1.1.bias", "conv_body_down.0.conv2.1.weight", "conv_body_down.0.conv2.2.bias", "conv_body_down.0.skip.1.weight", "conv_body_down.1.conv1.0.weight", "conv_body_down.1.conv1.1.bias", "conv_body_down.1.conv2.1.weight", "conv_body_down.1.conv2.2.bias", "conv_body_down.1.skip.1.weight", "conv_body_down.2.conv1.0.weight", "conv_body_down.2.conv1.1.bias", "conv_body_down.2.conv2.1.weight", "conv_body_down.2.conv2.2.bias", "conv_body_down.2.skip.1.weight", "conv_body_down.3.conv1.0.weight", "conv_body_down.3.conv1.1.bias", "conv_body_down.3.conv2.1.weight", "conv_body_down.3.conv2.2.bias", "conv_body_down.3.skip.1.weight", "conv_body_down.4.conv1.0.weight", "conv_body_down.4.conv1.1.bias", "conv_body_down.4.conv2.1.weight", "conv_body_down.4.conv2.2.bias", "conv_body_down.4.skip.1.weight", "conv_body_down.5.conv1.0.weight", "conv_body_down.5.conv1.1.bias", "conv_body_down.5.conv2.1.weight", "conv_body_down.5.conv2.2.bias", "conv_body_down.5.skip.1.weight", "conv_body_down.6.conv1.0.weight", "conv_body_down.6.conv1.1.bias", "conv_body_down.6.conv2.1.weight", "conv_body_down.6.conv2.2.bias", "conv_body_down.6.skip.1.weight", "final_conv.0.weight", "final_conv.1.bias", "conv_body_up.0.conv1.0.weight", "conv_body_up.0.conv1.1.bias", "conv_body_up.0.conv2.activation.bias", "conv_body_up.1.conv1.0.weight", "conv_body_up.1.conv1.1.bias", "conv_body_up.1.conv2.activation.bias", "conv_body_up.2.conv1.0.weight", "conv_body_up.2.conv1.1.bias", "conv_body_up.2.conv2.activation.bias", "conv_body_up.3.conv1.0.weight", "conv_body_up.3.conv1.1.bias", "conv_body_up.3.conv2.activation.bias", "conv_body_up.4.conv1.0.weight", "conv_body_up.4.conv1.1.bias", "conv_body_up.4.conv2.activation.bias", "conv_body_up.5.conv1.0.weight", "conv_body_up.5.conv1.1.bias", "conv_body_up.5.conv2.activation.bias", "conv_body_up.6.conv1.0.weight", "conv_body_up.6.conv1.1.bias", "conv_body_up.6.conv2.activation.bias", "stylegan_decoder.style_mlp.2.weight", "stylegan_decoder.style_mlp.2.bias", "stylegan_decoder.style_mlp.4.weight", "stylegan_decoder.style_mlp.4.bias", "stylegan_decoder.style_mlp.6.weight", "stylegan_decoder.style_mlp.6.bias", "stylegan_decoder.style_mlp.8.weight", "stylegan_decoder.style_mlp.8.bias", "stylegan_decoder.style_conv1.activate.bias", "stylegan_decoder.style_convs.0.activate.bias", "stylegan_decoder.style_convs.1.activate.bias", "stylegan_decoder.style_convs.2.activate.bias", "stylegan_decoder.style_convs.3.activate.bias", "stylegan_decoder.style_convs.4.activate.bias", "stylegan_decoder.style_convs.5.activate.bias", "stylegan_decoder.style_convs.6.activate.bias", "stylegan_decoder.style_convs.7.activate.bias", "stylegan_decoder.style_convs.8.activate.bias", "stylegan_decoder.style_convs.9.activate.bias", "stylegan_decoder.style_convs.10.activate.bias", "stylegan_decoder.style_convs.11.activate.bias", "stylegan_decoder.style_convs.12.activate.bias", "stylegan_decoder.style_convs.13.activate.bias". size mismatch for conv_body_up.3.conv2.weight: copying a param with shape torch.Size([128, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). size mismatch for conv_body_up.3.skip.weight: copying a param with shape torch.Size([128, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 256, 1, 1]). size mismatch for conv_body_up.4.conv2.weight: copying a param with shape torch.Size([64, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 256, 3, 3]). size mismatch for conv_body_up.4.skip.weight: copying a param with shape torch.Size([64, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([128, 256, 1, 1]). size mismatch for conv_body_up.5.conv2.weight: copying a param with shape torch.Size([32, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 128, 3, 3]). size mismatch for conv_body_up.5.skip.weight: copying a param with shape torch.Size([32, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([64, 128, 1, 1]). size mismatch for conv_body_up.6.conv2.weight: copying a param with shape torch.Size([16, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 64, 3, 3]). size mismatch for conv_body_up.6.skip.weight: copying a param with shape torch.Size([16, 32, 1, 1]) from checkpoint, the shape in current model is torch.Size([32, 64, 1, 1]). size mismatch for toRGB.3.weight: copying a param with shape torch.Size([3, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 256, 1, 1]). size mismatch for toRGB.4.weight: copying a param with shape torch.Size([3, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 128, 1, 1]). size mismatch for toRGB.5.weight: copying a param with shape torch.Size([3, 32, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 64, 1, 1]). size mismatch for toRGB.6.weight: copying a param with shape torch.Size([3, 16, 1, 1]) from checkpoint, the shape in current model is torch.Size([3, 32, 1, 1]). size mismatch for stylegan_decoder.style_convs.6.modulated_conv.weight: copying a param with shape torch.Size([1, 256, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 512, 512, 3, 3]). size mismatch for stylegan_decoder.style_convs.7.modulated_conv.weight: copying a param with shape torch.Size([1, 256, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 512, 512, 3, 3]). size mismatch for stylegan_decoder.style_convs.7.modulated_conv.modulation.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]). size mismatch for stylegan_decoder.style_convs.7.modulated_conv.modulation.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]). size mismatch for stylegan_decoder.style_convs.8.modulated_conv.weight: copying a param with shape torch.Size([1, 128, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 256, 512, 3, 3]). size mismatch for stylegan_decoder.style_convs.8.modulated_conv.modulation.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]). size mismatch for stylegan_decoder.style_convs.8.modulated_conv.modulation.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]). size mismatch for stylegan_decoder.style_convs.9.modulated_conv.weight: copying a param with shape torch.Size([1, 128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 256, 256, 3, 3]). size mismatch for stylegan_decoder.style_convs.9.modulated_conv.modulation.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]). size mismatch for stylegan_decoder.style_convs.9.modulated_conv.modulation.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for stylegan_decoder.style_convs.10.modulated_conv.weight: copying a param with shape torch.Size([1, 64, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 128, 256, 3, 3]). size mismatch for stylegan_decoder.style_convs.10.modulated_conv.modulation.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]). size mismatch for stylegan_decoder.style_convs.10.modulated_conv.modulation.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for stylegan_decoder.style_convs.11.modulated_conv.weight: copying a param with shape torch.Size([1, 64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 128, 128, 3, 3]). size mismatch for stylegan_decoder.style_convs.11.modulated_conv.modulation.weight: copying a param with shape torch.Size([64, 512]) from checkpoint, the shape in current model is torch.Size([128, 512]). size mismatch for stylegan_decoder.style_convs.11.modulated_conv.modulation.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for stylegan_decoder.style_convs.12.modulated_conv.weight: copying a param with shape torch.Size([1, 32, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 64, 128, 3, 3]). size mismatch for stylegan_decoder.style_convs.12.modulated_conv.modulation.weight: copying a param with shape torch.Size([64, 512]) from checkpoint, the shape in current model is torch.Size([128, 512]). size mismatch for stylegan_decoder.style_convs.12.modulated_conv.modulation.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for stylegan_decoder.style_convs.13.modulated_conv.weight: copying a param with shape torch.Size([1, 32, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([1, 64, 64, 3, 3]). size mismatch for stylegan_decoder.style_convs.13.modulated_conv.modulation.weight: copying a param with shape torch.Size([32, 512]) from checkpoint, the shape in current model is torch.Size([64, 512]). size mismatch for stylegan_decoder.style_convs.13.modulated_conv.modulation.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for stylegan_decoder.to_rgbs.3.modulated_conv.weight: copying a param with shape torch.Size([1, 3, 256, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 3, 512, 1, 1]). size mismatch for stylegan_decoder.to_rgbs.3.modulated_conv.modulation.weight: copying a param with shape torch.Size([256, 512]) from checkpoint, the shape in current model is torch.Size([512, 512]). size mismatch for stylegan_decoder.to_rgbs.3.modulated_conv.modulation.bias: copying a param with shape torch.Size([256]) from checkpoint, the shape in current model is torch.Size([512]). size mismatch for stylegan_decoder.to_rgbs.4.modulated_conv.weight: copying a param with shape torch.Size([1, 3, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 3, 256, 1, 1]). size mismatch for stylegan_decoder.to_rgbs.4.modulated_conv.modulation.weight: copying a param with shape torch.Size([128, 512]) from checkpoint, the shape in current model is torch.Size([256, 512]). size mismatch for stylegan_decoder.to_rgbs.4.modulated_conv.modulation.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for stylegan_decoder.to_rgbs.5.modulated_conv.weight: copying a param with shape torch.Size([1, 3, 64, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 3, 128, 1, 1]). size mismatch for stylegan_decoder.to_rgbs.5.modulated_conv.modulation.weight: copying a param with shape torch.Size([64, 512]) from checkpoint, the shape in current model is torch.Size([128, 512]). size mismatch for stylegan_decoder.to_rgbs.5.modulated_conv.modulation.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for stylegan_decoder.to_rgbs.6.modulated_conv.weight: copying a param with shape torch.Size([1, 3, 32, 1, 1]) from checkpoint, the shape in current model is torch.Size([1, 3, 64, 1, 1]). size mismatch for stylegan_decoder.to_rgbs.6.modulated_conv.modulation.weight: copying a param with shape torch.Size([32, 512]) from checkpoint, the shape in current model is torch.Size([64, 512]). size mismatch for stylegan_decoder.to_rgbs.6.modulated_conv.modulation.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for condition_scale.3.0.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). size mismatch for condition_scale.3.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for condition_scale.3.2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). size mismatch for condition_scale.3.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for condition_scale.4.0.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]). size mismatch for condition_scale.4.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for condition_scale.4.2.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]). size mismatch for condition_scale.4.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for condition_scale.5.0.weight: copying a param with shape torch.Size([32, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]). size mismatch for condition_scale.5.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for condition_scale.5.2.weight: copying a param with shape torch.Size([32, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]). size mismatch for condition_scale.5.2.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for condition_scale.6.0.weight: copying a param with shape torch.Size([16, 16, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]). size mismatch for condition_scale.6.0.bias: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([32]). size mismatch for condition_scale.6.2.weight: copying a param with shape torch.Size([16, 16, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]). size mismatch for condition_scale.6.2.bias: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([32]). size mismatch for condition_shift.3.0.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). size mismatch for condition_shift.3.0.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for condition_shift.3.2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). size mismatch for condition_shift.3.2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). size mismatch for condition_shift.4.0.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]). size mismatch for condition_shift.4.0.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for condition_shift.4.2.weight: copying a param with shape torch.Size([64, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 128, 3, 3]). size mismatch for condition_shift.4.2.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]). size mismatch for condition_shift.5.0.weight: copying a param with shape torch.Size([32, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]). size mismatch for condition_shift.5.0.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for condition_shift.5.2.weight: copying a param with shape torch.Size([32, 32, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 64, 3, 3]). size mismatch for condition_shift.5.2.bias: copying a param with shape torch.Size([32]) from checkpoint, the shape in current model is torch.Size([64]). size mismatch for condition_shift.6.0.weight: copying a param with shape torch.Size([16, 16, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]). size mismatch for condition_shift.6.0.bias: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([32]). size mismatch for condition_shift.6.2.weight: copying a param with shape torch.Size([16, 16, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 32, 3, 3]). size mismatch for condition_shift.6.2.bias: copying a param with shape torch.Size([16]) from checkpoint, the shape in current model is torch.Size([32]). ```
claunia commented 2026-01-29 21:39:33 +00:00
Author
Owner
Copy Link

@tachikoma777 commented on GitHub (Aug 12, 2021):

https://github.com/TencentARC/GFPGAN/blob/master/PaperModel.md
Maybe you should try this if you are using GFPGANv1.pth

@tachikoma777 commented on GitHub (Aug 12, 2021): https://github.com/TencentARC/GFPGAN/blob/master/PaperModel.md Maybe you should try this if you are using GFPGANv1.pth
claunia commented 2026-01-29 21:39:36 +00:00
Author
Owner
Copy Link

@xinntao commented on GitHub (Aug 13, 2021):

@tachikoma777 Thanks 😄

@xinntao commented on GitHub (Aug 13, 2021): @tachikoma777 Thanks 😄
Sign in to join this conversation.
No Branch/Tag Specified
Branches Tags
Labels
Clear labels
pull-request
Mirrored from GitHub Pull Request
No Label
Milestone
No items
No Milestone
Projects
Clear projects
No project
Assignees
Clear assignees
claunia
No Assignees
1 Participants
Notifications
Due Date
No due date set.
Dependencies

No dependencies set.

Reference: TencentARC/GFPGAN#46
Delete Branch "%!s()"

Deleting a branch is permanent. Although the deleted branch may continue to exist for a short time before it actually gets removed, it CANNOT be undone in most cases. Continue?