Update controlnet_module.py

controlnet_module.py

@@ -202,6 +202,11 @@ class ControlNetProcessor:
                 controlnet_conditioning_scale = [controlnet_strength * 0.6,  # OpenPose: 60% für Person
                                                controlnet_strength * 0.4]   # Canny: 40% für Umgebung
                 
+                # Zufälliger Seed
+                seed = random.randint(0, 2**32 - 1)
+                generator = torch.Generator(device=self.device).manual_seed(seed)
+                print(f"ControlNet Seed: {seed}")
+                
             else:
                 # PERSON BEIBEHALTEN, UMGEBUNG ÄNDERN → NUR OPENPOSE
                 controlnet_type = "openpose"
@@ -209,12 +214,12 @@ class ControlNetProcessor:
                 conditioning_images = self.extract_pose(image)
                 controlnet_conditioning_scale = controlnet_strength
 
-            pipe = self.load_controlnet_pipeline(controlnet_type)
+                # Zufälliger Seed
+                seed = random.randint(0, 2**32 - 1)
+                generator = torch.Generator(device=self.device).manual_seed(seed)
+                print(f"ControlNet Seed: {seed}")
 
-            # Zufälliger Seed
-            seed = random.randint(0, 2**32 - 1)
-            generator = torch.Generator(device=self.device).manual_seed(seed)
-            print(f"ControlNet Seed: {seed}")
+            pipe = self.load_controlnet_pipeline(controlnet_type)
 
             # Fortschritt-Callback
             callback = ControlNetProgressCallback(progress, int(steps)) if progress is not None else None