import torch import gradio as gr from diffusers import FluxInpaintPipeline MARKDOWN = """ # FLUX.1 Inpainting 🔥 Shoutout to the [Black Forest Labs](https://huggingface.co/black-forest-labs) team for creating this amazing model! """ DEVICE = torch.device("cuda") # DEVICE = torch.device("cpu") pipe = FluxInpaintPipeline.from_pretrained( "black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16) pipe.to(DEVICE) @spaces.GPU() def process(input_image_editor, input_text, progress=gr.Progress(track_tqdm=True)): if not input_text: gr.Info("Please enter a text prompt.") return None image = input_image_editor['background'] mask_image = input_image_editor['layers'][0] if not image: gr.Info("Please upload an image.") return None if not mask_image: gr.Info("Please draw a mask on the image.") return None generator = torch.Generator().manual_seed(42) return pipe( prompt=input_text, image=image, mask_image=mask_image, width=1024, height=1024, strength=0.9 ).images[0] with gr.Blocks() as demo: gr.Markdown(MARKDOWN) with gr.Row(): with gr.Column(): input_image_editor_component = gr.ImageEditor( label='Image', type='pil', sources=["upload", "webcam"], image_mode='RGB', layers=False, brush=gr.Brush(colors=["#000000"], color_mode="fixed")) input_text_component = gr.Textbox( label='Text prompt', placeholder='Cartoon cactus',) submit_button_component = gr.Button( value='Submit', variant='primary') with gr.Column(): output_image_component = gr.Image( type='pil', image_mode='RGB', label='Generated image') submit_button_component.click( fn=process, inputs=[ input_image_editor_component, input_text_component ], outputs=[ output_image_component ] ) demo.launch(debug=False, show_error=True)