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-rw-r--r--modules/modelloader.py74
1 files changed, 54 insertions, 20 deletions
diff --git a/modules/modelloader.py b/modules/modelloader.py
index 3bd1de4d..6de65c69 100644
--- a/modules/modelloader.py
+++ b/modules/modelloader.py
@@ -1,34 +1,36 @@
import os
import shutil
+import importlib
from urllib.parse import urlparse
from basicsr.utils.download_util import load_file_from_url
+from modules import shared
+from modules.upscaler import Upscaler
from modules.paths import script_path, models_path
-def load_models(model_path: str, model_url: str = None, command_path: str = None, dl_name: str = None, existing=None,
- ext_filter=None) -> list:
+def load_models(model_path: str, model_url: str = None, command_path: str = None, ext_filter=None, download_name=None) -> list:
"""
A one-and done loader to try finding the desired models in specified directories.
- @param dl_name: The file name to use for downloading a model. If not specified, it will be used from the URL.
- @param model_url: If specified, attempt to download model from the given URL.
+ @param download_name: Specify to download from model_url immediately.
+ @param model_url: If no other models are found, this will be downloaded on upscale.
@param model_path: The location to store/find models in.
@param command_path: A command-line argument to search for models in first.
- @param existing: An array of existing model paths.
@param ext_filter: An optional list of filename extensions to filter by
@return: A list of paths containing the desired model(s)
"""
+ output = []
+
if ext_filter is None:
ext_filter = []
- if existing is None:
- existing = []
try:
places = []
if command_path is not None and command_path != model_path:
pretrained_path = os.path.join(command_path, 'experiments/pretrained_models')
if os.path.exists(pretrained_path):
+ print(f"Appending path: {pretrained_path}")
places.append(pretrained_path)
elif os.path.exists(command_path):
places.append(command_path)
@@ -36,26 +38,24 @@ def load_models(model_path: str, model_url: str = None, command_path: str = None
for place in places:
if os.path.exists(place):
for file in os.listdir(place):
- if os.path.isdir(file):
+ full_path = os.path.join(place, file)
+ if os.path.isdir(full_path):
continue
if len(ext_filter) != 0:
model_name, extension = os.path.splitext(file)
if extension not in ext_filter:
continue
- if file not in existing:
- path = os.path.join(place, file)
- existing.append(path)
- if model_url is not None and len(existing) == 0:
- if dl_name is not None:
- model_file = load_file_from_url(url=model_url, model_dir=model_path, file_name=dl_name, progress=True)
+ if file not in output:
+ output.append(full_path)
+ if model_url is not None and len(output) == 0:
+ if download_name is not None:
+ dl = load_file_from_url(model_url, model_path, True, download_name)
+ output.append(dl)
else:
- model_file = load_file_from_url(url=model_url, model_dir=model_path, progress=True)
-
- if os.path.exists(model_file) and os.path.isfile(model_file) and model_file not in existing:
- existing.append(model_file)
+ output.append(model_url)
except:
pass
- return existing
+ return output
def friendly_name(file: str):
@@ -110,4 +110,38 @@ def move_files(src_path: str, dest_path: str, ext_filter: str = None):
print(f"Removing empty folder: {src_path}")
shutil.rmtree(src_path, True)
except:
- pass \ No newline at end of file
+ pass
+
+
+def load_upscalers():
+ datas = []
+ for cls in Upscaler.__subclasses__():
+ name = cls.__name__
+ module_name = cls.__module__
+ print(f"Class: {name} and {module_name}")
+ module = importlib.import_module(module_name)
+ class_ = getattr(module, name)
+ cmd_name = f"{name.lower().replace('upscaler', '')}-models-path"
+ print(f"CMD Name: {cmd_name}")
+ opt_string = None
+ try:
+ opt_string = shared.opts.__getattr__(cmd_name)
+ except:
+ pass
+ scaler = class_(opt_string)
+ for child in scaler.scalers:
+ print(f"Appending {child.name}")
+ datas.append(child)
+
+ shared.sd_upscalers = datas
+
+ # for scaler in subclasses:
+ # print(f"Found scaler: {type(scaler).__name__}")
+ # try:
+ # scaler = scaler()
+ # for child in scaler.scalers:
+ # print(f"Appending {child.name}")
+ # datas.append[child]
+ # except:
+ # pass
+ # shared.sd_upscalers = datas