Mathdesenvnonimate commited on
Commit
01965bf
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1 Parent(s): a5ec7c9

Upload app.py

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Files changed (1) hide show
  1. app.py +7 -6
app.py CHANGED
@@ -45,12 +45,11 @@ rembg_session = rembg.new_session()
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  def check_input_image(input_image):
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  if input_image is None:
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- raise gr.Error("Nenhuma Imagem Carregada!")
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  def preprocess(input_image, do_remove_background, foreground_ratio):
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-
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- def fill_background(image):
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  image = np.array(image).astype(np.float32) / 255.0
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  image = image[:, :, :3] * image[:, :, 3:4] + (1 - image[:, :, 3:4]) * 0.5
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  image = Image.fromarray((image * 255.0).astype(np.uint8))
@@ -125,13 +124,13 @@ with gr.Blocks() as demo:
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  with gr.Column():
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  with gr.Tab("OBJ"):
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  output_model_obj = gr.Model3D(
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- label="Saida do Modelo (OBJ Format)",
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  interactive=False,
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  )
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- gr.Markdown("")
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  with gr.Tab("STL"):
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  output_model_glb = gr.Model3D(
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- label="Saída do Modelo (STL Format)",
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  interactive=False,
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  )
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  gr.Markdown("Nota: O modelo mostrado aqui tem uma aparência mais escura. Baixe para obter resultados corretos.")
@@ -143,6 +142,8 @@ with gr.Blocks() as demo:
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  inputs=[input_image],
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  outputs=[processed_image, output_model_obj, output_model_glb],
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  cache_examples=True,
 
 
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  examples_per_page=20
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  )
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  submit.click(fn=check_input_image, inputs=[input_image]).success(
 
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  def check_input_image(input_image):
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  if input_image is None:
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+ raise gr.Error("No image uploaded!")
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  def preprocess(input_image, do_remove_background, foreground_ratio):
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+ def fill_background(image):
 
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  image = np.array(image).astype(np.float32) / 255.0
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  image = image[:, :, :3] * image[:, :, 3:4] + (1 - image[:, :, 3:4]) * 0.5
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  image = Image.fromarray((image * 255.0).astype(np.uint8))
 
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  with gr.Column():
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  with gr.Tab("OBJ"):
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  output_model_obj = gr.Model3D(
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+ label="Output Model (OBJ Format)",
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  interactive=False,
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  )
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+ gr.Markdown(".")
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  with gr.Tab("STL"):
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  output_model_glb = gr.Model3D(
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+ label="Output Model (STL Format)",
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  interactive=False,
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  )
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  gr.Markdown("Nota: O modelo mostrado aqui tem uma aparência mais escura. Baixe para obter resultados corretos.")
 
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  inputs=[input_image],
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  outputs=[processed_image, output_model_obj, output_model_glb],
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  cache_examples=True,
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+ fn=partial(run_example),
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+ label="Examples",
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  examples_per_page=20
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  )
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  submit.click(fn=check_input_image, inputs=[input_image]).success(