Update controlnet_module.py

controlnet_module.py

@@ -113,147 +113,6 @@ class ControlNetProcessor:
             print(f"Fehler bei Depth Map Extraction: {e}")
             return image.convert("RGB").resize((512, 512))
 
-    def load_controlnet_pipeline(self, controlnet_type="openpose"):
-        """Lädt die passende ControlNet Pipeline"""
-        if controlnet_type == "openpose":
-            if self.pipe_openpose is None:
-                print("Loading OpenPose ControlNet pipeline...")
-                try:
-                    self.controlnet_openpose = ControlNetModel.from_pretrained(
-                        "lllyasviel/sd-controlnet-openpose",
-                        torch_dtype=self.torch_dtype
-                    )
-                    self.pipe_openpose = StableDiffusionControlNetPipeline.from_pretrained(
-                        "runwayml/stable-diffusion-v1-5",
-                        controlnet=self.controlnet_openpose,
-                        torch_dtype=self.torch_dtype,
-                        safety_checker=None,
-                        requires_safety_checker=False
-                    ).to(self.device)
-
-                    from diffusers import EulerAncestralDiscreteScheduler
-                    self.pipe_openpose.scheduler = EulerAncestralDiscreteScheduler.from_config(self.pipe_openpose.scheduler.config)
-                    self.pipe_openpose.enable_attention_slicing()
-                    print("✅ OpenPose ControlNet pipeline loaded successfully!")
-                except Exception as e:
-                    print(f"Fehler beim Laden von OpenPose ControlNet: {e}")
-                    raise
-            return self.pipe_openpose
-
-        elif controlnet_type == "canny":
-            if self.pipe_canny is None:
-                print("Loading Canny ControlNet pipeline...")
-                try:
-                    self.controlnet_canny = ControlNetModel.from_pretrained(
-                        "lllyasviel/sd-controlnet-canny",
-                        torch_dtype=self.torch_dtype
-                    )
-                    self.pipe_canny = StableDiffusionControlNetPipeline.from_pretrained(
-                        "runwayml/stable-diffusion-v1-5",
-                        controlnet=self.controlnet_canny,
-                        torch_dtype=self.torch_dtype,
-                        safety_checker=None,
-                        requires_safety_checker=False
-                    ).to(self.device)
-
-                    from diffusers import EulerAncestralDiscreteScheduler
-                    self.pipe_canny.scheduler = EulerAncestralDiscreteScheduler.from_config(self.pipe_canny.scheduler.config)
-                    self.pipe_canny.enable_attention_slicing()
-                    print("✅ Canny ControlNet pipeline loaded successfully!")
-                except Exception as e:
-                    print(f"Fehler beim Laden von Canny ControlNet: {e}")
-                    raise
-            return self.pipe_canny
-
-        elif controlnet_type == "depth":
-            if self.pipe_depth is None:
-                print("Loading Depth ControlNet pipeline...")
-                try:
-                    self.controlnet_depth = ControlNetModel.from_pretrained(
-                        "lllyasviel/sd-controlnet-depth",
-                        torch_dtype=self.torch_dtype
-                    )
-                    self.pipe_depth = StableDiffusionControlNetPipeline.from_pretrained(
-                        "runwayml/stable-diffusion-v1-5",
-                        controlnet=self.controlnet_depth,
-                        torch_dtype=self.torch_dtype,
-                        safety_checker=None,
-                        requires_safety_checker=False
-                    ).to(self.device)
-
-                    from diffusers import EulerAncestralDiscreteScheduler
-                    self.pipe_depth.scheduler = EulerAncestralDiscreteScheduler.from_config(self.pipe_depth.scheduler.config)
-                    self.pipe_depth.enable_attention_slicing()
-                    print("✅ Depth ControlNet pipeline loaded successfully!")
-                except Exception as e:
-                    print(f"Fehler beim Laden von Depth ControlNet: {e}")
-                    raise
-            return self.pipe_depth
-
-        elif controlnet_type == "multi_inside":  # OpenPose + Canny für Inside-Box
-            if self.pipe_multi_inside is None:
-                print("Loading Multi-ControlNet pipeline für Inside-Box...")
-                try:
-                    if self.controlnet_openpose is None:
-                        self.controlnet_openpose = ControlNetModel.from_pretrained(
-                            "lllyasviel/sd-controlnet-openpose",
-                            torch_dtype=self.torch_dtype
-                        )
-                    if self.controlnet_canny is None:
-                        self.controlnet_canny = ControlNetModel.from_pretrained(
-                            "lllyasviel/sd-controlnet-canny", 
-                            torch_dtype=self.torch_dtype
-                        )
-                    
-                    self.pipe_multi_inside = StableDiffusionControlNetPipeline.from_pretrained(
-                        "runwayml/stable-diffusion-v1-5",
-                        controlnet=[self.controlnet_openpose, self.controlnet_canny],
-                        torch_dtype=self.torch_dtype,
-                        safety_checker=None,
-                        requires_safety_checker=False
-                    ).to(self.device)
-
-                    from diffusers import EulerAncestralDiscreteScheduler
-                    self.pipe_multi_inside.scheduler = EulerAncestralDiscreteScheduler.from_config(self.pipe_multi_inside.scheduler.config)
-                    self.pipe_multi_inside.enable_attention_slicing()
-                    print("✅ Multi-ControlNet (Inside) pipeline loaded successfully!")
-                except Exception as e:
-                    print(f"Fehler beim Laden von Multi-ControlNet Inside: {e}")
-                    raise
-            return self.pipe_multi_inside
-
-        elif controlnet_type == "multi_outside":  # Depth + Canny für Outside-Box
-            if self.pipe_multi_outside is None:
-                print("Loading Multi-ControlNet pipeline für Outside-Box...")
-                try:
-                    if self.controlnet_depth is None:
-                        self.controlnet_depth = ControlNetModel.from_pretrained(
-                            "lllyasviel/sd-controlnet-depth",
-                            torch_dtype=self.torch_dtype
-                        )
-                    if self.controlnet_canny is None:
-                        self.controlnet_canny = ControlNetModel.from_pretrained(
-                            "lllyasviel/sd-controlnet-canny", 
-                            torch_dtype=self.torch_dtype
-                        )
-                    
-                    self.pipe_multi_outside = StableDiffusionControlNetPipeline.from_pretrained(
-                        "runwayml/stable-diffusion-v1-5",
-                        controlnet=[self.controlnet_depth, self.controlnet_canny],
-                        torch_dtype=self.torch_dtype,
-                        safety_checker=None,
-                        requires_safety_checker=False
-                    ).to(self.device)
-
-                    from diffusers import EulerAncestralDiscreteScheduler
-                    self.pipe_multi_outside.scheduler = EulerAncestralDiscreteScheduler.from_config(self.pipe_multi_outside.scheduler.config)
-                    self.pipe_multi_outside.enable_attention_slicing()
-                    print("✅ Multi-ControlNet (Outside) pipeline loaded successfully!")
-                except Exception as e:
-                    print(f"Fehler beim Laden von Multi-ControlNet Outside: {e}")
-                    raise
-            return self.pipe_multi_outside
-
 
     def prepare_controlnet_maps(self, image, keep_environment=False):
         """