barakmam commited on
Commit
6163c61
·
1 Parent(s): e4eecf5

update with cache_examples=False

Browse files
Files changed (1) hide show
  1. app.py +4 -3
app.py CHANGED
@@ -51,9 +51,9 @@ if device == "cuda":
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  # with gr.Blocks(css=css) as demo:
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  # with gr.Blocks(css="style.css") as demo:
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  with gr.Blocks(theme=gr.themes.Soft()) as demo:
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- gr.Markdown(f""" # Real Time Editing with RNRI Inversion 🍎⚡️
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- This is a demo for our [paper](https://arxiv.org/abs/2312.12540) **RNRI: Regularized Newton Raphson Inversion for Text-to-Image Diffusion Models**.
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- Image editing using RNRI for inversion demonstrates significant speed-up and improved quality compared to previous state-of-the-art methods.
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  Take a look at the [project page](https://barakmam.github.io/rnri.github.io/).
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  """)
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  inv_state = gr.State()
@@ -189,6 +189,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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  examples='examples',
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  inputs=[input_image, description_prompt, target_prompt, edit_guidance_scale, num_inference_steps,
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  inversion_max_step, rnri_iterations, rnri_alpha, rnri_lr],
 
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  )
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  gr.Markdown(f"""Disclaimer: Performance may be inferior to the reported in the paper due to hardware limitation.
 
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  # with gr.Blocks(css=css) as demo:
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  # with gr.Blocks(css="style.css") as demo:
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  with gr.Blocks(theme=gr.themes.Soft()) as demo:
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+ gr.Markdown(f""" # Real Time Editing with GNRI Inversion 🍎⚡️
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+ This is a demo for our [paper](https://arxiv.org/abs/2312.12540) **GNRI: Lightning-fast Image Inversion and Editing for Text-to-Image Diffusion Models**.
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+ Image editing using GNRI for inversion demonstrates significant speed-up and improved quality compared to previous state-of-the-art methods.
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  Take a look at the [project page](https://barakmam.github.io/rnri.github.io/).
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  """)
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  inv_state = gr.State()
 
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  examples='examples',
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  inputs=[input_image, description_prompt, target_prompt, edit_guidance_scale, num_inference_steps,
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  inversion_max_step, rnri_iterations, rnri_alpha, rnri_lr],
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+ cache_examples=False
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  )
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  gr.Markdown(f"""Disclaimer: Performance may be inferior to the reported in the paper due to hardware limitation.