spycoder commited on
Commit
b1c3c7c
1 Parent(s): 82be3cc

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +16 -16
app.py CHANGED
@@ -59,35 +59,34 @@ def actualpredict(file_path):
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  return predicted_class_id
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- def predict(microphone,file_upload):
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  max_length = 100000
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  warn_output = " "
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  ans = " "
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- file_path = microphone
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- if (microphone is not None) and (file_upload is not None):
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- warn_output = (
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- "WARNING: You've uploaded an audio file and used the microphone. "
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- "The recorded file from the microphone will be used and the uploaded audio will be discarded.\n"
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- )
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- elif (microphone is None) and (file_upload is None):
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- return "ERROR: You have to either use the microphone or upload an audio file"
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- if(microphone is not None):
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- file_path = microphone
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- if(file_upload is not None):
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- file_path = file_upload
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- predicted_class_id = actualpredict(file_path)
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  if(predicted_class_id==0):
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  ans = "no_parkinson"
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  else:
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  ans = "parkinson"
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- return warn_output + ans
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  gr.Interface(
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  fn=predict,
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  inputs=[
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- gr.inputs.Audio(source="microphone", type="filepath", optional=True),
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  gr.inputs.Audio(source="upload", type="filepath", optional=True),
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  ],
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  outputs="text",
@@ -95,5 +94,6 @@ gr.Interface(
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  description=description,
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  ).launch()
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  # iface = gr.Interface(fn=predict, inputs="file", outputs="text")
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  # iface.launch()
 
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  return predicted_class_id
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+ def predict(file_upload):
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  max_length = 100000
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  warn_output = " "
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  ans = " "
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+ # file_path = file_upload
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+ # if (microphone is not None) and (file_upload is not None):
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+ # warn_output = (
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+ # "WARNING: You've uploaded an audio file and used the microphone. "
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+ # "The recorded file from the microphone will be used and the uploaded audio will be discarded.\n"
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+ # )
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+ # elif (microphone is None) and (file_upload is None):
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+ # return "ERROR: You have to either use the microphone or upload an audio file"
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+ # if(microphone is not None):
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+ # file_path = microphone
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+ # if(file_upload is not None):
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+ # file_path = file_upload
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+ predicted_class_id = actualpredict(file_upload)
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  if(predicted_class_id==0):
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  ans = "no_parkinson"
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  else:
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  ans = "parkinson"
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+ return ans
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  gr.Interface(
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  fn=predict,
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  inputs=[
 
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  gr.inputs.Audio(source="upload", type="filepath", optional=True),
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  ],
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  outputs="text",
 
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  description=description,
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  ).launch()
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+ # gr.inputs.Audio(source="microphone", type="filepath", optional=True),
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  # iface = gr.Interface(fn=predict, inputs="file", outputs="text")
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  # iface.launch()