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.

modules/gfpgan_model.py

@@ -1,24 +1,23 @@
 import os
 import sys
 import traceback
-from glob import glob
 
-from modules import shared, devices
-from modules.shared import cmd_opts
-from modules.paths import script_path
+import facexlib
+import gfpgan
+
 import modules.face_restoration
 from modules import shared, devices, modelloader
 from modules.paths import models_path
 
 model_dir = "GFPGAN"
-cmd_dir = None
+user_path = None
 model_path = os.path.join(models_path, model_dir)
 model_url = "https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth"
-
+have_gfpgan = False
 loaded_gfpgan_model = None
 
 
-def gfpgan():
+def gfpgann():
     global loaded_gfpgan_model
     global model_path
     if loaded_gfpgan_model is not None:
@@ -28,14 +27,16 @@ def gfpgan():
     if gfpgan_constructor is None:
         return None
 
-    models = modelloader.load_models(model_path, model_url, cmd_dir)
-    if len(models) != 0:
+    models = modelloader.load_models(model_path, model_url, user_path, ext_filter="GFPGAN")
+    if len(models) == 1 and "http" in models[0]:
+        model_file = models[0]
+    elif len(models) != 0:
         latest_file = max(models, key=os.path.getctime)
         model_file = latest_file
     else:
         print("Unable to load gfpgan model!")
         return None
-    model = gfpgan_constructor(model_path=model_file, model_dir=model_path, upscale=1, arch='clean', channel_multiplier=2,
+    model = gfpgan_constructor(model_path=model_file, upscale=1, arch='clean', channel_multiplier=2,
                                bg_upsampler=None)
     model.gfpgan.to(shared.device)
     loaded_gfpgan_model = model
@@ -44,11 +45,12 @@ def gfpgan():
 
 
 def gfpgan_fix_faces(np_image):
-    model = gfpgan()
+    model = gfpgann()
     if model is None:
         return np_image
     np_image_bgr = np_image[:, :, ::-1]
-    cropped_faces, restored_faces, gfpgan_output_bgr = model.enhance(np_image_bgr, has_aligned=False, only_center_face=False, paste_back=True)
+    cropped_faces, restored_faces, gfpgan_output_bgr = model.enhance(np_image_bgr, has_aligned=False,
+                                                                     only_center_face=False, paste_back=True)
     np_image = gfpgan_output_bgr[:, :, ::-1]
 
     if shared.opts.face_restoration_unload:
@@ -57,7 +59,6 @@ def gfpgan_fix_faces(np_image):
     return np_image
 
 
-have_gfpgan = False
 gfpgan_constructor = None
 
 
@@ -67,14 +68,33 @@ def setup_model(dirname):
         os.makedirs(model_path)
 
     try:
-        from modules.gfpgan_model_arch import GFPGANerr
-        global cmd_dir
+        from gfpgan import GFPGANer
+        from facexlib import detection, parsing
+        global user_path
         global have_gfpgan
         global gfpgan_constructor
 
-        cmd_dir = dirname
+        load_file_from_url_orig = gfpgan.utils.load_file_from_url
+        facex_load_file_from_url_orig = facexlib.detection.load_file_from_url
+        facex_load_file_from_url_orig2 = facexlib.parsing.load_file_from_url
+
+        def my_load_file_from_url(**kwargs):
+            print("Setting model_dir to " + model_path)
+            return load_file_from_url_orig(**dict(kwargs, model_dir=model_path))
+
+        def facex_load_file_from_url(**kwargs):
+            return facex_load_file_from_url_orig(**dict(kwargs, save_dir=model_path, model_dir=None))
+
+        def facex_load_file_from_url2(**kwargs):
+            return facex_load_file_from_url_orig2(**dict(kwargs, save_dir=model_path, model_dir=None))
+
+        gfpgan.utils.load_file_from_url = my_load_file_from_url
+        facexlib.detection.load_file_from_url = facex_load_file_from_url
+        facexlib.parsing.load_file_from_url = facex_load_file_from_url2
+        user_path = dirname
+        print("Have gfpgan should be true?")
         have_gfpgan = True
-        gfpgan_constructor = GFPGANerr
+        gfpgan_constructor = GFPGANer
 
         class FaceRestorerGFPGAN(modules.face_restoration.FaceRestoration):
             def name(self):
@@ -82,7 +102,9 @@ def setup_model(dirname):
 
             def restore(self, np_image):
                 np_image_bgr = np_image[:, :, ::-1]
-                cropped_faces, restored_faces, gfpgan_output_bgr = gfpgan().enhance(np_image_bgr, has_aligned=False, only_center_face=False, paste_back=True)
+                cropped_faces, restored_faces, gfpgan_output_bgr = gfpgann().enhance(np_image_bgr, has_aligned=False,
+                                                                                     only_center_face=False,
+                                                                                     paste_back=True)
                 np_image = gfpgan_output_bgr[:, :, ::-1]
 
                 return np_image