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| author | AUTOMATIC1111 <16777216c@gmail.com> | 2023-01-04 14:40:19 +0000 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2023-01-04 14:40:19 +0000 |
| commit | da5c1e8a732c173ed8ccda9fa32f9a194ff91ab6 (patch) | |
| tree | a2eec9c47e820e7ab351337f73c99d874b4b904f /modules/esrgan_model.py | |
| parent | cffc240a7327ae60671ff533469fc4ed4bf605de (diff) | |
| parent | 47df0849019abac6722c49512f4dd2285bff5b7d (diff) | |
| download | stable-diffusion-webui-gfx803-da5c1e8a732c173ed8ccda9fa32f9a194ff91ab6.tar.gz stable-diffusion-webui-gfx803-da5c1e8a732c173ed8ccda9fa32f9a194ff91ab6.tar.bz2 stable-diffusion-webui-gfx803-da5c1e8a732c173ed8ccda9fa32f9a194ff91ab6.zip | |
Merge branch 'master' into inpaint_textual_inversion
Diffstat (limited to 'modules/esrgan_model.py')
| -rw-r--r-- | modules/esrgan_model.py | 19 |
1 files changed, 14 insertions, 5 deletions
diff --git a/modules/esrgan_model.py b/modules/esrgan_model.py index a13cf6ac..9a9c38f1 100644 --- a/modules/esrgan_model.py +++ b/modules/esrgan_model.py @@ -50,6 +50,7 @@ def mod2normal(state_dict): def resrgan2normal(state_dict, nb=23):
# this code is copied from https://github.com/victorca25/iNNfer
if "conv_first.weight" in state_dict and "body.0.rdb1.conv1.weight" in state_dict:
+ re8x = 0
crt_net = {}
items = []
for k, v in state_dict.items():
@@ -75,10 +76,18 @@ def resrgan2normal(state_dict, nb=23): crt_net['model.3.bias'] = state_dict['conv_up1.bias']
crt_net['model.6.weight'] = state_dict['conv_up2.weight']
crt_net['model.6.bias'] = state_dict['conv_up2.bias']
- crt_net['model.8.weight'] = state_dict['conv_hr.weight']
- crt_net['model.8.bias'] = state_dict['conv_hr.bias']
- crt_net['model.10.weight'] = state_dict['conv_last.weight']
- crt_net['model.10.bias'] = state_dict['conv_last.bias']
+
+ if 'conv_up3.weight' in state_dict:
+ # modification supporting: https://github.com/ai-forever/Real-ESRGAN/blob/main/RealESRGAN/rrdbnet_arch.py
+ re8x = 3
+ crt_net['model.9.weight'] = state_dict['conv_up3.weight']
+ crt_net['model.9.bias'] = state_dict['conv_up3.bias']
+
+ crt_net[f'model.{8+re8x}.weight'] = state_dict['conv_hr.weight']
+ crt_net[f'model.{8+re8x}.bias'] = state_dict['conv_hr.bias']
+ crt_net[f'model.{10+re8x}.weight'] = state_dict['conv_last.weight']
+ crt_net[f'model.{10+re8x}.bias'] = state_dict['conv_last.bias']
+
state_dict = crt_net
return state_dict
@@ -190,7 +199,7 @@ def upscale_without_tiling(model, img): img = img[:, :, ::-1]
img = np.ascontiguousarray(np.transpose(img, (2, 0, 1))) / 255
img = torch.from_numpy(img).float()
- img = devices.mps_contiguous_to(img.unsqueeze(0), devices.device_esrgan)
+ img = img.unsqueeze(0).to(devices.device_esrgan)
with torch.no_grad():
output = model(img)
output = output.squeeze().float().cpu().clamp_(0, 1).numpy()
|