Real-ESRGAN
Real-ESRGAN copied to clipboard
Published
20 hours ago •
xinntao
xinntao
Fine-Tuned model not working
Hello guys, Amazing work you have done here, I am fine-tuning this for Mammography images, and when I follow these steps Training I don't know where is the output of my new fine-tuned model.
I get two models, I now generator and Discriminator:
./experiments/finetune_RealESRGANx4plus_400k/models/net_d_latest.pth
./experiments/finetune_RealESRGANx4plus_400k/models/net_g_latest.pth
But when I try to import any of these files, I continue to get an error like this:
esrgan image processing failed
internal_model.load_state_dict(torch.load(model_path), strict=True)
File "/path/to/venv/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1406, in load_state_dict
esrgan image processing failed
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for RRDBNet:
Missing key(s) in state_dict: "conv_first.weight", "conv_first.bias", "RRDB_trunk.0.RDB1.conv1.weight", "RRDB_trunk.0.RDB1.conv1.bias", "RRDB_trunk.0.RDB1.conv2.weight", "RRDB_trunk.0.RDB1.conv2.bias", "RRDB_trunk.0.RDB1.conv3.weight", "RRDB_trunk.0.RDB1.conv3.bias", "RRDB_trunk.0.RDB1.conv4.weight", "RRDB_trunk.0.RDB1.conv4.bias", "RRDB_trunk.0.RDB1.conv5.weight", "RRDB_trunk.0.RDB1.conv5.bias", "RRDB_trunk.0.RDB2.conv1.weight", "RRDB_trunk.0.RDB2.conv1.bias", "RRDB_trunk.0.RDB2.conv2.weight", "RRDB_trunk.0.RDB2.conv2.bias", "RRDB_trunk.0.RDB2.conv3.weight", "RRDB_trunk.0.RDB2.conv3.bias", "RRDB_trunk.0.RDB2.conv4.weight", "RRDB_trunk.0.RDB2.conv4.bias", "RRDB_trunk.0.RDB2.conv5.weight", "RRDB_trunk.0.RDB2.conv5.bias", "RRDB_trunk.0.RDB3.conv1.weight", "RRDB_trunk.0.RDB3.conv1.bias", "RRDB_trunk.0.RDB3.conv2.weight", "RRDB_trunk.0.RDB3.conv2.bias", "RRDB_trunk.0.RDB3.conv3.weight", "RRDB_trunk.0.RDB3.conv3.bias", "RRDB_trunk.0.RDB3.conv4.weight", "RRDB_trunk.0.RDB3.conv4.bias", 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Unexpected key(s) in state_dict: "params".
Can you give any idea what I need to do next? or what is the model that I should use?
This a base code I use to call the model:
def get_model(working_dir):
model_path = os.path.join(working_dir, 'models/net_d_latest.pth')
internal_device = torch.device('cpu')
internal_model = arch.RRDBNet(3, 3, 64, 23, gc=32)
print(model_path)
internal_model.load_state_dict(torch.load(model_path), strict=True)
internal_model.train()
internal_model.eval()
return internal_model.to(internal_device), internal_device
Thanks in advance!
Rename "net_g_latest.pth" in ./experiments/finetune_RealESRGANx4plus_400k/models/ to RealESRNet_x4plus.pth. Then use this RealESRNet_x4plus.pth as finetuned weights.
2022/5/26 wget https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.1/RealESRNet_x4plus.pth -P experiments/pretrained_models you can find what you want in the link https://github.com/xinntao/Real-ESRGAN/releases/download, xindao maybe forgot that line in his training.md
2022/4/30 I also think this statement is reasonable. You can even see some details at the beginning in this link https://github.com/xinntao/Real-ESRGAN/issues/82
Rename "net_g_latest.pth" in ./experiments/finetune_RealESRGANx4plus_400k/models/ to RealESRNet_x4plus.pth. Then use this RealESRNet_x4plus.pth as finetuned weights.
Yeah, I'm still lost on this issue.
Clearly there is a small bit of obviousness in how to use your trained model in Stable Diffusion, but I haven't discovered it yet.
I successfully trained my model and it loads fine in chaiNNer and works as well. It's not great because it's my first model but it's still a milestone.
However, I'm really trying to figure out the workflow after I've trained my model. For example, my model is still named net_g_latest.pth and when I drop it into the Stable Diffusion models folder it simply does not appear in the upscaler menus.
Are we supposed to convert our pth?
As for alixeee's response above I'm still trying to decode what they are trying to say (again, I'm a newbie so what's obvious to others is not obvious to me).
Ok so I got extra info....
The confusion on my part is that I used the ReaESRGAN yml template to fork as my own yml. That yml ran fine and I got a pth model within 30hrs. Perfect. Also works in chaiNNer just fine. However, what threw me off was that I had not realized the output model was defined as ESRGAN even though my yml file states "RealESRGAN" — so I kept trying to place it into the RealESRGAN folder within Automatic1111.
I moved it to ESRGAN and it now loads fine. But I still have no idea where the model identified itself as an ESRGAN when I clearly typed RealESRGAN into the yml — obviously it's some other parameter to which I'm unaware.