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Runtime error
| import gradio as gr | |
| from PIL import Image | |
| from backend.lora import get_lora_models | |
| from state import get_settings | |
| from backend.models.lcmdiffusion_setting import ControlNetSetting | |
| from backend.annotators.image_control_factory import ImageControlFactory | |
| _controlnet_models_map = None | |
| _controlnet_enabled = False | |
| _adapter_path = None | |
| app_settings = get_settings() | |
| def on_user_input( | |
| enable: bool, | |
| adapter_name: str, | |
| conditioning_scale: float, | |
| control_image: Image, | |
| preprocessor: str, | |
| ): | |
| if not isinstance(adapter_name, str): | |
| gr.Warning("Please select a valid ControlNet model") | |
| return gr.Checkbox(value=False) | |
| settings = app_settings.settings.lcm_diffusion_setting | |
| if settings.controlnet is None: | |
| settings.controlnet = ControlNetSetting() | |
| if enable and (adapter_name is None or adapter_name == ""): | |
| gr.Warning("Please select a valid ControlNet adapter") | |
| return gr.Checkbox(value=False) | |
| elif enable and not control_image: | |
| gr.Warning("Please provide a ControlNet control image") | |
| return gr.Checkbox(value=False) | |
| if control_image is None: | |
| return gr.Checkbox(value=enable) | |
| if preprocessor == "None": | |
| processed_control_image = control_image | |
| else: | |
| image_control_factory = ImageControlFactory() | |
| control = image_control_factory.create_control(preprocessor) | |
| processed_control_image = control.get_control_image(control_image) | |
| if not enable: | |
| settings.controlnet.enabled = False | |
| else: | |
| settings.controlnet.enabled = True | |
| settings.controlnet.adapter_path = _controlnet_models_map[adapter_name] | |
| settings.controlnet.conditioning_scale = float(conditioning_scale) | |
| settings.controlnet._control_image = processed_control_image | |
| # This code can be improved; currently, if the user clicks the | |
| # "Enable ControlNet" checkbox or changes the currently selected | |
| # ControlNet model, it will trigger a pipeline rebuild even if, in | |
| # the end, the user leaves the same ControlNet settings | |
| global _controlnet_enabled | |
| global _adapter_path | |
| if settings.controlnet.enabled != _controlnet_enabled or ( | |
| settings.controlnet.enabled | |
| and settings.controlnet.adapter_path != _adapter_path | |
| ): | |
| settings.rebuild_pipeline = True | |
| _controlnet_enabled = settings.controlnet.enabled | |
| _adapter_path = settings.controlnet.adapter_path | |
| return gr.Checkbox(value=enable) | |
| def on_change_conditioning_scale(cond_scale): | |
| print(cond_scale) | |
| app_settings.settings.lcm_diffusion_setting.controlnet.conditioning_scale = ( | |
| cond_scale | |
| ) | |
| def get_controlnet_ui() -> None: | |
| with gr.Blocks() as ui: | |
| gr.HTML( | |
| 'Download ControlNet v1.1 model from <a href="https://huggingface.co/comfyanonymous/ControlNet-v1-1_fp16_safetensors/tree/main">ControlNet v1.1 </a> (723 MB files) and place it in <b>controlnet_models</b> folder,restart the app' | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| with gr.Row(): | |
| global _controlnet_models_map | |
| _controlnet_models_map = get_lora_models( | |
| app_settings.settings.lcm_diffusion_setting.dirs["controlnet"] | |
| ) | |
| controlnet_models = list(_controlnet_models_map.keys()) | |
| default_model = ( | |
| controlnet_models[0] if len(controlnet_models) else None | |
| ) | |
| enabled_checkbox = gr.Checkbox( | |
| label="Enable ControlNet", | |
| info="Enable ControlNet", | |
| show_label=True, | |
| ) | |
| model_dropdown = gr.Dropdown( | |
| _controlnet_models_map.keys(), | |
| label="ControlNet model", | |
| info="ControlNet model to load (.safetensors format)", | |
| value=default_model, | |
| interactive=True, | |
| ) | |
| conditioning_scale_slider = gr.Slider( | |
| 0.0, | |
| 1.0, | |
| value=0.5, | |
| step=0.05, | |
| label="ControlNet conditioning scale", | |
| interactive=True, | |
| ) | |
| control_image = gr.Image( | |
| label="Control image", | |
| type="pil", | |
| ) | |
| preprocessor_radio = gr.Radio( | |
| [ | |
| "Canny", | |
| "Depth", | |
| "LineArt", | |
| "MLSD", | |
| "NormalBAE", | |
| "Pose", | |
| "SoftEdge", | |
| "Shuffle", | |
| "None", | |
| ], | |
| label="Preprocessor", | |
| info="Select the preprocessor for the control image", | |
| value="Canny", | |
| interactive=True, | |
| ) | |
| enabled_checkbox.input( | |
| fn=on_user_input, | |
| inputs=[ | |
| enabled_checkbox, | |
| model_dropdown, | |
| conditioning_scale_slider, | |
| control_image, | |
| preprocessor_radio, | |
| ], | |
| outputs=[enabled_checkbox], | |
| ) | |
| model_dropdown.input( | |
| fn=on_user_input, | |
| inputs=[ | |
| enabled_checkbox, | |
| model_dropdown, | |
| conditioning_scale_slider, | |
| control_image, | |
| preprocessor_radio, | |
| ], | |
| outputs=[enabled_checkbox], | |
| ) | |
| conditioning_scale_slider.input( | |
| fn=on_user_input, | |
| inputs=[ | |
| enabled_checkbox, | |
| model_dropdown, | |
| conditioning_scale_slider, | |
| control_image, | |
| preprocessor_radio, | |
| ], | |
| outputs=[enabled_checkbox], | |
| ) | |
| control_image.change( | |
| fn=on_user_input, | |
| inputs=[ | |
| enabled_checkbox, | |
| model_dropdown, | |
| conditioning_scale_slider, | |
| control_image, | |
| preprocessor_radio, | |
| ], | |
| outputs=[enabled_checkbox], | |
| ) | |
| preprocessor_radio.change( | |
| fn=on_user_input, | |
| inputs=[ | |
| enabled_checkbox, | |
| model_dropdown, | |
| conditioning_scale_slider, | |
| control_image, | |
| preprocessor_radio, | |
| ], | |
| outputs=[enabled_checkbox], | |
| ) | |
| conditioning_scale_slider.change( | |
| on_change_conditioning_scale, conditioning_scale_slider | |
| ) | |