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Runtime error
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•
025dc29
1
Parent(s):
b1af849
Update app.py
Browse files
app.py
CHANGED
@@ -160,7 +160,8 @@ def edit_with_pnp(input_video,
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n_frames: int = 40,#needs to be the same as for preprocess
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n_timesteps: int = 50,
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gudiance_scale: float = 7.5,
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-
inversion_prompt: str = ""#needs to be the same as for preprocess
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):
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config = {}
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@@ -201,7 +202,7 @@ def edit_with_pnp(input_video,
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editor = TokenFlow(config=config, frames=frames.value, inverted_latents=inverted_latents.value)
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edited_frames = editor.edit_video()
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save_video(edited_frames, 'tokenflow_PnP_fps_30.mp4', fps=
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# path = export_to_video(edited_frames)
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return 'tokenflow_PnP_fps_30.mp4', frames, latents, inverted_latents, do_inversion
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@@ -268,11 +269,13 @@ with gr.Blocks(css="style.css") as demo:
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batch_size = gr.Slider(label='Batch size', minimum=1, maximum=10,
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value=8, step=1, interactive=True)
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n_frames = gr.Slider(label='Num frames', minimum=20, maximum=200,
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value=
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n_timesteps = gr.Slider(label='Diffusion steps', minimum=25, maximum=100,
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value=50, step=1, interactive=True)
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with gr.TabItem('Plug-and-
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with gr.Column(min_width=100):
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pnp_attn_t = gr.Slider(label='pnp attention threshold', minimum=0, maximum=1,
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value=0.5, step=0.5, interactive=True)
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@@ -324,7 +327,8 @@ with gr.Blocks(css="style.css") as demo:
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n_frames,
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n_timesteps,
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gudiance_scale,
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inversion_prompt
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outputs = [output_video, frames, latents, inverted_latents, do_inversion]
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)
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n_frames: int = 40,#needs to be the same as for preprocess
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n_timesteps: int = 50,
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gudiance_scale: float = 7.5,
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inversion_prompt: str = "", #needs to be the same as for preprocess
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n_fps: int = 10
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):
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config = {}
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editor = TokenFlow(config=config, frames=frames.value, inverted_latents=inverted_latents.value)
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edited_frames = editor.edit_video()
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save_video(edited_frames, 'tokenflow_PnP_fps_30.mp4', fps=n_fps)
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# path = export_to_video(edited_frames)
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return 'tokenflow_PnP_fps_30.mp4', frames, latents, inverted_latents, do_inversion
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batch_size = gr.Slider(label='Batch size', minimum=1, maximum=10,
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value=8, step=1, interactive=True)
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n_frames = gr.Slider(label='Num frames', minimum=20, maximum=200,
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value=30, step=1, interactive=True)
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n_timesteps = gr.Slider(label='Diffusion steps', minimum=25, maximum=100,
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value=50, step=1, interactive=True)
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n_fps = gr.Slider(label='Frames per second', minimum=1, maximum=60,
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value=10, step=1, interactive=True)
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with gr.TabItem('Plug-and-Play Parameters'):
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with gr.Column(min_width=100):
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pnp_attn_t = gr.Slider(label='pnp attention threshold', minimum=0, maximum=1,
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value=0.5, step=0.5, interactive=True)
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n_frames,
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n_timesteps,
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gudiance_scale,
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inversion_prompt,
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n_fps ],
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outputs = [output_video, frames, latents, inverted_latents, do_inversion]
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)
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