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View Code? Open in Web Editor NEWPyTorch implements `Designing a Practical Degradation Model for Deep Blind Image Super-Resolution` paper.
License: Apache License 2.0
PyTorch implements `Designing a Practical Degradation Model for Deep Blind Image Super-Resolution` paper.
License: Apache License 2.0
我在resume时出现了2个错误,一个是checkpoints路径问题,一个resume_d时多了个ema_lsrresnet_model
😂😂😂
应该要改成这样吧
if bsrgan_config.resume_d:
lsrresnet_model, start_epoch, est_psnr, best_ssim, optimizer, scheduler = load_state_dict(
d_model,
bsrgan_config.resume_d,
optimizer=d_optimizer,
scheduler=d_scheduler,
load_mode="resume")
print("Loaded pretrained model weights.")
else:
print("Resume training d model not found. Start training from scratch.")
print("Check whether the pretrained g model is restored...")
if bsrgan_config.resume_g:
lsrresnet_model, ema_lsrresnet_model, start_epoch, est_psnr, best_ssim, optimizer, scheduler = load_state_dict(
g_model,
bsrgan_config.resume_g,
ema_model=ema_g_model,
optimizer=g_optimizer,
scheduler=g_scheduler,
load_mode="resume")
print("Loaded pretrained model weights.")
Traceback (most recent call last):
File "/home/drfarooq/numan/BSRGAN-PyTorch-main/test.py", line 90, in
main()
File "/home/drfarooq/numan/BSRGAN-PyTorch-main/test.py", line 33, in main
bsrgan_model = model.dict[bsrgan_config.g_arch_name](in_channels=bsrgan_config.in_channels,
AttributeError: module 'bsrgan_config' has no attribute 'g_arch_name'
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