mrq/stable-diffusion-webui
1
1
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Fix model paths, ensure we have the right files.

Browse Source 
Also, clean up logging in the ldsr arch file.
This commit is contained in:
d8ahazard 2022-09-30 08:55:04 -05:00
parent 64c6b13312
commit 8d60645106
2 changed files with 8 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

9
modules/ldsr_model.py
View File

@ -24,13 +24,18 @@ class UpscalerLDSR(Upscaler):
def load_model(self, path: str):
# Remove incorrect project.yaml file if too big
yaml_path = os.path.join(self.model_path, "project.yaml")
old_model_path = os.path.join(self.model_path, "model.pth")
new_model_path = os.path.join(self.model_path, "model.ckpt")
if os.path.exists(yaml_path):
statinfo = os.stat(yaml_path)
if statinfo.st_size <= 10485760:
if statinfo.st_size >= 10485760:
print("Removing invalid LDSR YAML file.")
os.remove(yaml_path)
if os.path.exists(old_model_path):
print("Renaming model from model.pth to model.ckpt")
os.rename(old_model_path, new_model_path)
model = load_file_from_url(url=self.model_url, model_dir=self.model_path,
file_name="model.pth", progress=True)
file_name="model.ckpt", progress=True)
yaml = load_file_from_url(url=self.yaml_url, model_dir=self.model_path,
file_name="project.yaml", progress=True)

3
modules/ldsr_model_arch.py
View File

@ -100,7 +100,6 @@ class LDSR:
# If we can adjust the max upscale size, then the 4 below should be our variable
print("Foo")
down_sample_rate = target_scale / 4
print(f"Downsample rate is {down_sample_rate}")
wd = width_og * down_sample_rate
hd = height_og * down_sample_rate
width_downsampled_pre = int(wd)
@ -111,7 +110,7 @@ class LDSR:
f'Downsampling from [{width_og}, {height_og}] to [{width_downsampled_pre}, {height_downsampled_pre}]')
im_og = im_og.resize((width_downsampled_pre, height_downsampled_pre), Image.LANCZOS)
else:
print(f"Down sample rate is 1 from {target_scale} / 4")
print(f"Down sample rate is 1 from {target_scale} / 4 (Not downsampling)")
logs = self.run(model["model"], im_og, diffusion_steps, eta)
sample = logs["sample"]