Astridkraft commited on
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56d50e6
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1 Parent(s): 91bca61

Update app.py

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Files changed (1) hide show
  1. app.py +5 -25
app.py CHANGED
@@ -1019,6 +1019,8 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
1019
  # OPTIMIERTE WERTE FÜR FOCUS_CHANGE
1020
  adj_strength = min(0.6, strength * 1.05) # Konservativer (0.65)
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  controlnet_weight = 0.85 # Stärkere ControlNet-Kontrolle
 
 
1022
  pose_ratio = 0.8 # OpenPose dominiert
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  canny_ratio = 0.2 # Canny unterstützt
1024
 
@@ -1056,7 +1058,7 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
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  nature_keywords = ["beach", "forest", "mountain", "ocean", "sky", "field", "landscape", "nature", "outdoor"]
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  interior_keywords = ["office", "room", "interior", "kitchen", "bedroom", "living room", "indoor", "wall", "furniture"]
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1059
- # Standard: Deine gewünschte 90:10 Verteilung
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  depth_ratio = 0.9
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  canny_ratio = 0.1
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@@ -1091,7 +1093,7 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
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  adj_strength = min(0.85, strength * 1.25)
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  controlnet_strength = adj_strength * 0.5
1093
 
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- # HIER FEHLEN DIE RATIOS - JETZT HINZUFÜGEN:
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  depth_ratio = 0.7 # Für Gesicht: Depth stärker
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  canny_ratio = 0.3 # Canny leichter
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@@ -1168,29 +1170,7 @@ def img_to_image(image, prompt, neg_prompt, strength, steps, guidance_scale,
1168
 
1169
  # ===== CONTROLNET-GESTEUERTES INPAINTING DURCHFÜHREN =====
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  print(f"🔄 Führe ControlNet-gesteuertes Inpainting durch...")
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-
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- # Berechne die Gewichtung der Maps für Controlnet basierend auf dem Modus
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- if keep_environment: # Depth + Canny
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- if mode == "face_only_change":
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- # Für Gesicht: Depth stärker, Canny leichter
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- depth_ratio = 0.7
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- canny_ratio = 0.3
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- else: # environment_change
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- # Für Umgebung: Ausgewogen
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- depth_ratio = 0.6
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- canny_ratio = 0.4
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-
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- conditioning_scale = [
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- controlnet_strength * depth_ratio,
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- controlnet_strength * canny_ratio
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- ]
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-
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- else: # OpenPose + Canny (nur focus_change)
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- conditioning_scale = [
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- controlnet_strength * pose_ratio,
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- controlnet_strength * canny_ratio
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- ]
1193
-
1194
 
1195
  result = pipe(
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  prompt=enhanced_prompt,
 
1019
  # OPTIMIERTE WERTE FÜR FOCUS_CHANGE
1020
  adj_strength = min(0.6, strength * 1.05) # Konservativer (0.65)
1021
  controlnet_weight = 0.85 # Stärkere ControlNet-Kontrolle
1022
+
1023
+ #Controlnet gesteuertes Inpainting
1024
  pose_ratio = 0.8 # OpenPose dominiert
1025
  canny_ratio = 0.2 # Canny unterstützt
1026
 
 
1058
  nature_keywords = ["beach", "forest", "mountain", "ocean", "sky", "field", "landscape", "nature", "outdoor"]
1059
  interior_keywords = ["office", "room", "interior", "kitchen", "bedroom", "living room", "indoor", "wall", "furniture"]
1060
 
1061
+ # Standard: Controlnet gesteuertes Inpainting wird genutzt wenn in Prompt nicht eines der folgenden keywords
1062
  depth_ratio = 0.9
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  canny_ratio = 0.1
1064
 
 
1093
  adj_strength = min(0.85, strength * 1.25)
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  controlnet_strength = adj_strength * 0.5
1095
 
1096
+ # HIER FEHLEN DIE RATIOS - Controlnet gesteuertes Inpainting:
1097
  depth_ratio = 0.7 # Für Gesicht: Depth stärker
1098
  canny_ratio = 0.3 # Canny leichter
1099
 
 
1170
 
1171
  # ===== CONTROLNET-GESTEUERTES INPAINTING DURCHFÜHREN =====
1172
  print(f"🔄 Führe ControlNet-gesteuertes Inpainting durch...")
1173
+
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1174
 
1175
  result = pipe(
1176
  prompt=enhanced_prompt,