import gradio as gr from diffusers import AutoPipelineForInpainting, AutoencoderKL import torch from PIL import Image, ImageOps vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16) pipeline = AutoPipelineForInpainting.from_pretrained("diffusers/stable-diffusion-xl-1.0-inpainting-0.1", vae=vae, torch_dtype=torch.float16, variant="fp16", use_safetensors=True).to("cuda") def divisible_by_8(image): width, height = image.size # Calculate the new width and height that are divisible by 8 new_width = (width // 8) * 8 new_height = (height // 8) * 8 # Resize the image resized_image = image.resize((new_width, new_height)) return resized_image def generate(image_editor, prompt, neg_prompt, strength, guidance): image = image_editor['background'].convert('RGB') image.thumbnail((1024, 1024)) image = divisible_by_8(image) layer = image_editor["layers"][0].resize(image.size) mask = Image.new("RGBA", image.size, "WHITE") mask.paste(layer, (0, 0), layer) mask = ImageOps.invert(mask.convert('L')) final_image = pipeline(prompt=prompt, image=image, mask_image=mask).images[0] #width=image.width, #height=image.height, #num_inference_steps=50, #strength=strength, #guidance_scale=guidance).images[0] return image_editor, image, mask, final_image with gr.Blocks() as demo: gr.Markdown(""" # Inpainting Sketch Pad by [Tony Assi](https://www.tonyassi.com/) """) with gr.Row(): with gr.Column(): sketch_pad = gr.ImageMask(type='pil', label='Inpaint') prompt = gr.Textbox() generate_button = gr.Button("Generate") with gr.Column(): version_gallery = gr.Gallery(label="Versions") restore_button = gr.Button("Restore Version") with gr.Accordion("Advanced Settings", open=False): neg_prompt = gr.Textbox(label='Negative Prompt', value='ugly, deformed, nsfw') strength_slider = gr.Slider(0.0, 1.0, value=1.0, label="Strength") guidance_slider = gr.Slider(1.0, 15.0, value=7.5, label="Guidance") with gr.Row(): out1 = gr.Image(format='png') out2 = gr.Image(format='png') out3 = gr.Image(format='png') generate_button.click(fn=generate, inputs=[sketch_pad,prompt, neg_prompt, strength_slider, guidance_slider], outputs=[sketch_pad, out1, out2, out3]) demo.launch()