barakmam commited on
Commit
1059cc6
·
1 Parent(s): 21dcae2

update markdown and disclaimer

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Files changed (1) hide show
  1. app.py +8 -4
app.py CHANGED
@@ -52,9 +52,11 @@ if device == "cuda":
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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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@@ -192,7 +194,9 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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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.""")
 
 
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  input_image.change(set_pipe, inputs=[input_image, description_prompt, edit_guidance_scale, num_inference_steps,
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  num_inference_steps, inversion_max_step, rnri_iterations, rnri_alpha, rnri_lr],
 
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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
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+ for Text-to-Image Diffusion Models. Accepted to ICLR 2025**.
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+ More details can be found in the [project page](https://barakmam.github.io/rnri.github.io/).
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+
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+ The demo is based on SDXL. Improved results can be achieved with our FLUX version (examples in project page).
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  """)
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  inv_state = gr.State()
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  cache_examples=False
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  )
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+ gr.Markdown(f"""Disclaimer: The results may vary depending on the hyper-parameters. Some typical hyper-parameters
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+ are xxxx. Errors may appear due to resource availability by HF.
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+ Performance may be inferior to the reported in the paper due to hardware limitation.""")
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  input_image.change(set_pipe, inputs=[input_image, description_prompt, edit_guidance_scale, num_inference_steps,
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  num_inference_steps, inversion_max_step, rnri_iterations, rnri_alpha, rnri_lr],