diff options
Diffstat (limited to 'modules/extras.py')
| -rw-r--r-- | modules/extras.py | 11 |
1 files changed, 8 insertions, 3 deletions
diff --git a/modules/extras.py b/modules/extras.py index 38b86167..1d9e64e5 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -40,6 +40,8 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v outputs = []
for image, image_name in zip(imageArr, imageNameArr):
+ if image is None:
+ return outputs, "Please select an input image.", ''
existing_pnginfo = image.info or {}
image = image.convert("RGB")
@@ -74,7 +76,7 @@ def run_extras(extras_mode, image, image_folder, gfpgan_visibility, codeformer_v c = cached_images.get(key)
if c is None:
upscaler = shared.sd_upscalers[scaler_index]
- c = upscaler.upscale(image, image.width * resize, image.height * resize)
+ c = upscaler.scaler.upscale(image, resize, upscaler.data_path)
cached_images[key] = c
return c
@@ -143,7 +145,7 @@ def run_pnginfo(image): return '', geninfo, info
-def run_modelmerger(primary_model_name, secondary_model_name, interp_method, interp_amount, save_as_half):
+def run_modelmerger(primary_model_name, secondary_model_name, interp_method, interp_amount, save_as_half, custom_name):
# Linear interpolation (https://en.wikipedia.org/wiki/Linear_interpolation)
def weighted_sum(theta0, theta1, alpha):
return ((1 - alpha) * theta0) + (alpha * theta1)
@@ -191,8 +193,11 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int if save_as_half:
theta_0[key] = theta_0[key].half()
+ ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
+
filename = primary_model_info.model_name + '_' + str(round(interp_amount, 2)) + '-' + secondary_model_info.model_name + '_' + str(round((float(1.0) - interp_amount), 2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt'
- output_modelname = os.path.join(shared.cmd_opts.ckpt_dir, filename)
+ filename = filename if custom_name == '' else (custom_name + '.ckpt')
+ output_modelname = os.path.join(ckpt_dir, filename)
print(f"Saving to {output_modelname}...")
torch.save(primary_model, output_modelname)
|