stable-diffusion-webui/modules/ldsr_model.py
d8ahazard 0dce0df1ee Holy $hit.
Yep.

Fix gfpgan_model_arch requirement(s).
Add Upscaler base class, move from images.
Add a lot of methods to Upscaler.
Re-work all the child upscalers to be proper classes.
Add BSRGAN scaler.
Add ldsr_model_arch class, removing the dependency for another repo that just uses regular latent-diffusion stuff.
Add one universal method that will always find and load new upscaler models without having to add new "setup_model" calls. Still need to add command line params, but that could probably be automated.
Add a "self.scale" property to all Upscalers so the scalers themselves can do "things" in response to the requested upscaling size.
Ensure LDSR doesn't get stuck in a longer loop of "upscale/downscale/upscale" as we try to reach the target upscale size.
Add typehints for IDE sanity.
PEP-8 improvements.
Moar.
2022-09-29 17:46:23 -05:00

45 lines
1.6 KiB
Python

import os
import sys
import traceback
from basicsr.utils.download_util import load_file_from_url
from modules.upscaler import Upscaler, UpscalerData
from modules.ldsr_model_arch import LDSR
from modules import shared
from modules.paths import models_path
class UpscalerLDSR(Upscaler):
def __init__(self, user_path):
self.name = "LDSR"
self.model_path = os.path.join(models_path, self.name)
self.user_path = user_path
self.model_url = "https://heibox.uni-heidelberg.de/f/578df07c8fc04ffbadf3/?dl=1"
self.yaml_url = "https://heibox.uni-heidelberg.de/f/31a76b13ea27482981b4/?dl=1"
super().__init__()
scaler_data = UpscalerData("LDSR", None, self)
self.scalers = [scaler_data]
def load_model(self, path: str):
model = load_file_from_url(url=self.model_url, model_dir=self.model_path,
file_name="model.pth", progress=True)
yaml = load_file_from_url(url=self.model_url, model_dir=self.model_path,
file_name="project.yaml", progress=True)
try:
return LDSR(model, yaml)
except Exception:
print("Error importing LDSR:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
return None
def do_upscale(self, img, path):
ldsr = self.load_model(path)
if ldsr is None:
print("NO LDSR!")
return img
ddim_steps = shared.opts.ldsr_steps
pre_scale = shared.opts.ldsr_pre_down
return ldsr.super_resolution(img, ddim_steps, self.scale)