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