feat: pause total tqdm

scripts/!adetailer.py

@@ -5,6 +5,7 @@ import platform
 import re
 import sys
 import traceback
+from contextlib import contextmanager
 from copy import copy, deepcopy
 from pathlib import Path
 from textwrap import dedent
@@ -62,13 +63,24 @@ print(
 )
 
 
-class ChangeTorchLoad:
-    def __enter__(self):
-        self.orig = torch.load
+@contextmanager
+def change_torch_load():
+    orig = torch.load
+    try:
         torch.load = safe.unsafe_torch_load
+        yield
+    finally:
+        torch.load = orig
 
-    def __exit__(self, *args, **kwargs):
-        torch.load = self.orig
+
+@contextmanager
+def pause_total_tqdm():
+    orig = opts.data.get("multiple_tqdm", True)
+    try:
+        opts.data["multiple_tqdm"] = False
+        yield
+    finally:
+        opts.data["multiple_tqdm"] = orig
 
 
 class AfterDetailerScript(scripts.Script):
@@ -449,7 +461,7 @@ class AfterDetailerScript(scripts.Script):
             ad_model = self.get_ad_model(args.ad_model)
             kwargs["device"] = self.ultralytics_device
 
-        with ChangeTorchLoad():
+        with change_torch_load():
             pred = predictor(ad_model, pp.image, args.ad_conf, **kwargs)
 
         masks = self.pred_preprocessing(pred, args)
@@ -510,7 +522,7 @@ class AfterDetailerScript(scripts.Script):
         for n, args in enumerate(arg_list):
             if args.ad_model == "None":
                 continue
-            with CNHijackRestore():
+            with CNHijackRestore(), pause_total_tqdm():
                 is_processed |= self._postprocess_image(p, pp, args, n=n)
 
         if is_processed: