Mathdesenvnonimate commited on
Commit
2557ffa
1 Parent(s): f997da9

Update app.py

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Files changed (1) hide show
  1. app.py +9 -15
app.py CHANGED
@@ -194,13 +194,9 @@ def process(input_image, prompt, prompt_neg='', input_elevation=0, input_num_ste
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  # gradio UI
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- _TITLE = '''LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation'''
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  _DESCRIPTION = '''
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- <div>
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- <a style="display:inline-block" href="https://me.kiui.moe/lgm/"><img src='https://img.shields.io/badge/public_website-8A2BE2'></a>
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- <a style="display:inline-block; margin-left: .5em" href="https://github.com/3DTopia/LGM"><img src='https://img.shields.io/github/stars/3DTopia/LGM?style=social'/></a>
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- </div>
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  * Se você achar o resultado insatisfatório, tente mudar a barra de seeds!
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  * O video é uma representação Parcial, o Resultado sera aprimorado por tecnicas de modelagem!
@@ -216,27 +212,25 @@ with block:
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  with gr.Row(variant='panel'):
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  with gr.Column(scale=1):
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  # input image
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- input_image = gr.Image(label="image", type='pil')
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  # input prompt
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  input_text = gr.Textbox(label="prompt")
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  # negative prompt
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- input_neg_text = gr.Textbox(label="negative prompt", value='ugly, blurry, pixelated obscure, unnatural colors, poor lighting, dull, unclear, cropped, lowres, low quality, artifacts, duplicate')
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  # elevation
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- input_elevation = gr.Slider(label="elevation", minimum=-90, maximum=90, step=1, value=0)
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  # inference steps
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- input_num_steps = gr.Slider(label="inference steps", minimum=1, maximum=100, step=1, value=30)
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  # random seed
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- input_seed = gr.Slider(label="random seed", minimum=0, maximum=100000, step=1, value=0)
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  # gen button
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- button_gen = gr.Button("Generate")
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  with gr.Column(scale=1):
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  with gr.Tab("Video"):
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  # final video results
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  output_video = gr.Video(label="video")
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- # ply file
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- output_file = gr.File(label="3D Gaussians (ply format)")
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  with gr.Tab("Multi-view Image"):
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  # multi-view results
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  output_image = gr.Image(interactive=False, show_label=False)
@@ -256,7 +250,7 @@ with block:
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  outputs=[output_image, output_video, output_file],
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  fn=lambda x: process(input_image=x, prompt=''),
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  cache_examples=True,
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- label='Image-to-3D Examples'
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  )
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  gr.Examples(
@@ -273,7 +267,7 @@ with block:
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  outputs=[output_image, output_video, output_file],
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  fn=lambda x: process(input_image=None, prompt=x),
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  cache_examples=True,
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- label='Text-to-3D Examples'
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  )
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  block.launch()
 
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  # gradio UI
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+ _TITLE = '''LGM'''
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  _DESCRIPTION = '''
 
 
 
 
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  * Se você achar o resultado insatisfatório, tente mudar a barra de seeds!
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  * O video é uma representação Parcial, o Resultado sera aprimorado por tecnicas de modelagem!
 
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  with gr.Row(variant='panel'):
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  with gr.Column(scale=1):
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  # input image
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+ input_image = gr.Image(label="imagem", type='pil')
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  # input prompt
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  input_text = gr.Textbox(label="prompt")
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  # negative prompt
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+ input_neg_text = gr.Textbox(label="prompt negativo", value='ugly, blurry, pixelated obscure, unnatural colors, poor lighting, dull, unclear, cropped, lowres, low quality, artifacts, duplicate')
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  # elevation
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+ input_elevation = gr.Slider(label="elevação", minimum=-90, maximum=90, step=1, value=0)
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  # inference steps
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+ input_num_steps = gr.Slider(label="passos de inferencia", minimum=1, maximum=100, step=1, value=30)
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  # random seed
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+ input_seed = gr.Slider(label="seed aleatoria", minimum=0, maximum=100000, step=1, value=0)
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  # gen button
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+ button_gen = gr.Button("Gerar")
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  with gr.Column(scale=1):
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  with gr.Tab("Video"):
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  # final video results
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  output_video = gr.Video(label="video")
 
 
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  with gr.Tab("Multi-view Image"):
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  # multi-view results
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  output_image = gr.Image(interactive=False, show_label=False)
 
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  outputs=[output_image, output_video, output_file],
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  fn=lambda x: process(input_image=x, prompt=''),
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  cache_examples=True,
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+ label='Image-to-3D Exemplos'
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  )
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  gr.Examples(
 
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  outputs=[output_image, output_video, output_file],
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  fn=lambda x: process(input_image=None, prompt=x),
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  cache_examples=True,
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+ label='Text-to-3D Exemplos'
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  )
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  block.launch()