callum-canavan commited on
Commit
4a0748c
·
1 Parent(s): 25ef56f

Revert inputs

Browse files
Files changed (1) hide show
  1. app.py +3 -14
app.py CHANGED
@@ -32,9 +32,6 @@ def generate_content(
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  transformation,
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  num_inference_steps,
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  seed,
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- guidance_scale,
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- noise_level,
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- reduction,
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  ):
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  prompts = [f'{style} {p}'.strip() for p in [prompt_for_original, prompt_for_transformed]]
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  prompt_embeds = [stage_1.encode_prompt(p) for p in prompts]
@@ -53,9 +50,7 @@ def generate_content(
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  negative_prompt_embeds,
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  views,
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  num_inference_steps=num_inference_steps,
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- generator=generator,
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- guidance_scale=guidance_scale,
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- reduction=reduction)
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  print("Sample stage 2")
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  image = sample_stage_2(stage_2,
@@ -64,10 +59,7 @@ def generate_content(
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  negative_prompt_embeds,
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  views,
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  num_inference_steps=num_inference_steps,
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- generator=generator,
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- guidance_scale=guidance_scale,
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- noise_level=noise_level,
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- reduction=reduction)
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  save_illusion(image, views, Path(""))
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  output_name = f"illusion.mp4"
@@ -94,11 +86,8 @@ gradio_app = gr.Interface(
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  gr.Textbox(label="Prompt for original view", placeholder="a dress"),
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  gr.Textbox(label="Prompt for transformed view", placeholder="an old man"),
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  gr.Dropdown(label="View transformation", choices=choices, value=choices[0]),
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- gr.Number(label="Number of diffusion steps", value=75, step=1, minimum=1, maximum=300),
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  gr.Number(label="Random seed", value=0, step=1, minimum=0, maximum=100000),
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- gr.Number(label="Guidance scale", value=7, step=1, minimum=1, maximum=10, info="How strongly diffusion is guided by the prompts"),
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- gr.Number(label="Noise level", value=50, step=1, minimum=1, maximum=100, info="Noise level for stage 2 of diffusion sampling", visible=False),
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- gr.Dropdown(label="Reduction", choices=["mean", "alternate"], value="mean", info="Method for reducing predicted noise and variances", visible=False),
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  ],
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  outputs=[gr.Video(label="Illusion"), gr.Image(label="Before and After")],
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  description=description,
 
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  transformation,
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  num_inference_steps,
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  seed,
 
 
 
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  ):
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  prompts = [f'{style} {p}'.strip() for p in [prompt_for_original, prompt_for_transformed]]
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  prompt_embeds = [stage_1.encode_prompt(p) for p in prompts]
 
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  negative_prompt_embeds,
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  views,
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  num_inference_steps=num_inference_steps,
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+ generator=generator)
 
 
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  print("Sample stage 2")
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  image = sample_stage_2(stage_2,
 
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  negative_prompt_embeds,
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  views,
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  num_inference_steps=num_inference_steps,
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+ generator=generator)
 
 
 
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  save_illusion(image, views, Path(""))
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  output_name = f"illusion.mp4"
 
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  gr.Textbox(label="Prompt for original view", placeholder="a dress"),
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  gr.Textbox(label="Prompt for transformed view", placeholder="an old man"),
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  gr.Dropdown(label="View transformation", choices=choices, value=choices[0]),
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+ gr.Number(label="Number of diffusion steps", value=30, step=1, minimum=1, maximum=300),
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  gr.Number(label="Random seed", value=0, step=1, minimum=0, maximum=100000),
 
 
 
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  ],
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  outputs=[gr.Video(label="Illusion"), gr.Image(label="Before and After")],
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  description=description,