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| author | AUTOMATIC <16777216c@gmail.com> | 2022-09-12 20:24:54 +0000 |
|---|---|---|
| committer | AUTOMATIC <16777216c@gmail.com> | 2022-09-12 20:24:54 +0000 |
| commit | 0de109c21098a7469d18a40957b57f2030ab4edf (patch) | |
| tree | d4d9bcb3fc391e5c0b0768f807f3c67e906d4904 /modules | |
| parent | c249bbb4d41ecfb43cf4ba43f23a4c8b08d8c56e (diff) | |
| download | stable-diffusion-webui-gfx803-0de109c21098a7469d18a40957b57f2030ab4edf.tar.gz stable-diffusion-webui-gfx803-0de109c21098a7469d18a40957b57f2030ab4edf.tar.bz2 stable-diffusion-webui-gfx803-0de109c21098a7469d18a40957b57f2030ab4edf.zip | |
Codeformer face restoration not working: AttributeError: module 'modules.shared' has no attribute 'device_codeformer' #348
Diffstat (limited to 'modules')
| -rw-r--r-- | modules/codeformer_model.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py index 6cd29c83..21c704f7 100644 --- a/modules/codeformer_model.py +++ b/modules/codeformer_model.py @@ -56,13 +56,13 @@ def setup_codeformer(): self.net.to(shared.device)
return self.net, self.face_helper
- net = net_class(dim_embd=512, codebook_size=1024, n_head=8, n_layers=9, connect_list=['32', '64', '128', '256']).to(shared.device_codeformer)
+ net = net_class(dim_embd=512, codebook_size=1024, n_head=8, n_layers=9, connect_list=['32', '64', '128', '256']).to(devices.device_codeformer)
ckpt_path = load_file_from_url(url=pretrain_model_url, model_dir=os.path.join(path, 'weights/CodeFormer'), progress=True)
checkpoint = torch.load(ckpt_path)['params_ema']
net.load_state_dict(checkpoint)
net.eval()
- face_helper = FaceRestoreHelper(1, face_size=512, crop_ratio=(1, 1), det_model='retinaface_resnet50', save_ext='png', use_parse=True, device=shared.device_codeformer)
+ face_helper = FaceRestoreHelper(1, face_size=512, crop_ratio=(1, 1), det_model='retinaface_resnet50', save_ext='png', use_parse=True, device=devices.device_codeformer)
self.net = net
self.face_helper = face_helper
@@ -84,7 +84,7 @@ def setup_codeformer(): for idx, cropped_face in enumerate(self.face_helper.cropped_faces):
cropped_face_t = img2tensor(cropped_face / 255., bgr2rgb=True, float32=True)
normalize(cropped_face_t, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True)
- cropped_face_t = cropped_face_t.unsqueeze(0).to(shared.device_codeformer)
+ cropped_face_t = cropped_face_t.unsqueeze(0).to(devices.device_codeformer)
try:
with torch.no_grad():
|