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https://github.com/storytold/storyteller-ml.git
synced 2026-10-17 00:23:14 +00:00
Update app.py
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@@ -32,6 +32,7 @@ unet = UNet2DConditionModel.from_pretrained(model_id, subfolder="unet", revision
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tokenflow_pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=to).to(device)
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if device == "cuda":
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tokenflow_pipe.enable_xformers_memory_efficient_attention()
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# tokenflow_pipe.enable_attention_slicing()
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def randomize_seed_fn():
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seed = random.randint(0, np.iinfo(np.int32).max)
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@@ -120,7 +121,7 @@ def preprocess_and_invert(input_video,
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steps,
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n_timesteps = 50,
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batch_size: int = 8,
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n_frames: int = 40,
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n_frames: int = 10000,
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inversion_prompt:str = '',
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):
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@@ -172,11 +173,11 @@ def edit_with_pnp(input_video,
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pnp_attn_t: float = 0.5,
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pnp_f_t: float = 0.8,
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batch_size: int = 8, #needs to be the same as for preprocess
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n_frames: int = 40,#needs to be the same as for preprocess
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n_frames: int = 10000,#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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n_fps: int = 30,
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progress=gr.Progress(track_tqdm=True)
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):
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config = {}
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@@ -281,19 +282,19 @@ with gr.Blocks(css="style.css") as demo:
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randomize_seed = gr.Checkbox(label='Randomize seed', value=False)
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gudiance_scale = gr.Slider(label='Guidance Scale', minimum=1, maximum=30,
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value=7.5, step=0.5, interactive=True)
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steps = gr.Slider(label='Inversion steps', minimum=10, maximum=500,
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value=200, step=1, interactive=True)
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steps = gr.Slider(label='Inversion steps', minimum=10, maximum=200,
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value=500, step=1, interactive=True)
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with gr.Column(min_width=100):
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inversion_prompt = gr.Textbox(lines=1, label="Inversion prompt", interactive=True, placeholder="")
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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=2, maximum=200,
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value=24, step=1, interactive=True)
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value=10, step=1, interactive=True)
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n_frames = gr.Slider(label='Num frames', minimum=2, maximum=10000,
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value=10000, step=1, interactive=True)
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n_timesteps = gr.Slider(label='Diffusion steps', minimum=25, maximum=100,
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value=25, step=25, 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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value=30, 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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@@ -378,4 +379,4 @@ with gr.Blocks(css="style.css") as demo:
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)
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demo.queue()
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demo.launch()
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demo.launch()
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