fabiencasenave commited on
Commit
515b121
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1 Parent(s): 7d9d915

Update app.py

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Files changed (1) hide show
  1. app.py +32 -11
app.py CHANGED
@@ -25,6 +25,11 @@ nb_samples = 1000
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  field_names_train = ["Density", "Pressure", "Temperature"]
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  def sample_info(sample_id_str, fieldn):
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  sample_ = hf_dataset[int(sample_id_str)]["sample"]
@@ -77,10 +82,26 @@ def sample_info(sample_id_str, fieldn):
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  color, _ = r.render(scene)
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-
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  str__ = f"Training sample {sample_id_str}\n"
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  str__ += str(plaid_sample)+"\n"
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- str__ += f"number of nodes: {nodes.shape[0]}"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  return str__, color
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@@ -88,17 +109,17 @@ def sample_info(sample_id_str, fieldn):
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  if __name__ == "__main__":
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  with gr.Blocks() as demo:
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- d1 = gr.Slider(0, nb_samples-1, value=0, label="Training sample id", info="Choose between 0 and "+str(nb_samples-1))
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- d2 = gr.Dropdown(field_names_train, value=field_names_train[0], label="Field name")
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-
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-
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- output1 = gr.Text(label="Training sample info")
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- output2 = gr.Image(label="Training sample visualization")
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-
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-
 
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  d1.input(sample_info, [d1, d2], [output1, output2])
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  d2.input(sample_info, [d1, d2], [output1, output2])
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-
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  demo.launch()
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  field_names_train = ["Density", "Pressure", "Temperature"]
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+ _HEADER_ = '''
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+ <h2><b>Visualization demo of <a href='https://huggingface.co/datasets/PLAID-datasets/Rotor37' target='_blank'><b>Rotor37 dataset</b></b></h2>
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+ '''
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+
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+
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  def sample_info(sample_id_str, fieldn):
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  sample_ = hf_dataset[int(sample_id_str)]["sample"]
 
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  color, _ = r.render(scene)
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  str__ = f"Training sample {sample_id_str}\n"
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  str__ += str(plaid_sample)+"\n"
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+
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+ if len(hf_dataset.description['in_scalars_names'])>0:
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+ str__ += "\ninput scalars:\n"
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+ for sname in hf_dataset.description['in_scalars_names']:
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+ str__ += f"- {sname}: {plaid_sample.get_scalar(sname)}\n"
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+ if len(hf_dataset.description['out_scalars_names'])>0:
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+ str__ += "\noutput scalars:\n"
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+ for sname in hf_dataset.description['out_scalars_names']:
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+ str__ += f"- {sname}: {plaid_sample.get_scalar(sname)}\n"
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+ str__ += f"\n\nMesh number of nodes: {nodes.shape[0]}\n"
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+ if len(hf_dataset.description['in_fields_names'])>0:
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+ str__ += "\ninput fields:\n"
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+ for fname in hf_dataset.description['in_fields_names']:
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+ str__ += f"- {fname}\n"
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+ if len(hf_dataset.description['out_fields_names'])>0:
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+ str__ += "\noutput fields:\n"
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+ for fname in hf_dataset.description['out_fields_names']:
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+ str__ += f"- {fname}\n"
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  return str__, color
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  if __name__ == "__main__":
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  with gr.Blocks() as demo:
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+ gr.Markdown(_HEADER_)
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+ with gr.Row(variant="panel"):
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+ with gr.Column():
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+ d1 = gr.Slider(0, nb_samples-1, value=0, label="Training sample id", info="Choose between 0 and "+str(nb_samples-1))
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+ output1 = gr.Text(label="Training sample info")
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+ with gr.Column():
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+ d2 = gr.Dropdown(field_names_train, value=field_names_train[0], label="Field name")
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+ output2 = gr.Image(label="Training sample visualization")
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+
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  d1.input(sample_info, [d1, d2], [output1, output2])
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  d2.input(sample_info, [d1, d2], [output1, output2])
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  demo.launch()
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