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author | AUTOMATIC1111 <16777216c@gmail.com> | 2022-10-15 07:47:26 +0000 |
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committer | GitHub <noreply@github.com> | 2022-10-15 07:47:26 +0000 |
commit | f42e0aae6de6b9a7f8da4eaf13594a13502b4fa9 (patch) | |
tree | 472025101577ff5cbd45a3bcb524e6e4accb75ec /modules/bsrgan_model.py | |
parent | 0e77ee24b0b651d6a564245243850e4fb9831e31 (diff) | |
parent | d13ce89e203d76ab2b54a3406a93a5e4304f529e (diff) | |
download | stable-diffusion-webui-gfx803-f42e0aae6de6b9a7f8da4eaf13594a13502b4fa9.tar.gz stable-diffusion-webui-gfx803-f42e0aae6de6b9a7f8da4eaf13594a13502b4fa9.tar.bz2 stable-diffusion-webui-gfx803-f42e0aae6de6b9a7f8da4eaf13594a13502b4fa9.zip |
Merge branch 'master' into master
Diffstat (limited to 'modules/bsrgan_model.py')
-rw-r--r-- | modules/bsrgan_model.py | 8 |
1 files changed, 3 insertions, 5 deletions
diff --git a/modules/bsrgan_model.py b/modules/bsrgan_model.py index e62c6657..737e1a76 100644 --- a/modules/bsrgan_model.py +++ b/modules/bsrgan_model.py @@ -8,15 +8,13 @@ import torch from basicsr.utils.download_util import load_file_from_url import modules.upscaler -from modules import shared, modelloader +from modules import devices, modelloader from modules.bsrgan_model_arch import RRDBNet -from modules.paths import models_path class UpscalerBSRGAN(modules.upscaler.Upscaler): def __init__(self, dirname): self.name = "BSRGAN" - self.model_path = os.path.join(models_path, self.name) self.model_name = "BSRGAN 4x" self.model_url = "https://github.com/cszn/KAIR/releases/download/v1.0/BSRGAN.pth" self.user_path = dirname @@ -44,13 +42,13 @@ class UpscalerBSRGAN(modules.upscaler.Upscaler): model = self.load_model(selected_file) if model is None: return img - model.to(shared.device) + model.to(devices.device_bsrgan) torch.cuda.empty_cache() img = np.array(img) img = img[:, :, ::-1] img = np.moveaxis(img, 2, 0) / 255 img = torch.from_numpy(img).float() - img = img.unsqueeze(0).to(shared.device) + img = img.unsqueeze(0).to(devices.device_bsrgan) with torch.no_grad(): output = model(img) output = output.squeeze().float().cpu().clamp_(0, 1).numpy() |