iamAI123 commited on
Commit
8a22c32
·
1 Parent(s): abf2ad0

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +7 -10
app.py CHANGED
@@ -7,7 +7,6 @@ import gradio as gr
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  model = whisper.load_model("base")
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-
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  def convert_to_text(audio_path: str) -> str:
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  # Load the model outside the function if possible, so it's only loaded once
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  model = whisper.load_model("base")
@@ -18,19 +17,17 @@ def convert_to_text(audio_path: str) -> str:
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  # Process segments in parallel using multiprocessing
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- """ctx = multiprocessing.get_context('spawn')
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- pool = ctx.Pool()
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  print("Starting the processes....")
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  results = pool.map(process_segment, audio_segments)
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  pool.close()
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- pool.join() """
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- return audio_segments[0]
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  # Combine the results
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- #text = ' '.join(results)
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- #return text
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-
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  import os
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  from pydub import AudioSegment
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@@ -69,7 +66,7 @@ def split_audio(audio_path: str, chunk_size: int) -> List[str]:
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  return audio_segments
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- def process_segment(segment_path: str, q) -> str:
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  # Load the model for each process if necessary
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  print(f"Processing segment : {segment_path}")
@@ -92,6 +89,6 @@ def get_results(path):
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  return "complete"
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  ad = gr.components.Audio(type='filepath')
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- iface = gr.Interface(fn=get_results, inputs=ad, outputs="text")
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  iface.launch()
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  model = whisper.load_model("base")
 
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  def convert_to_text(audio_path: str) -> str:
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  # Load the model outside the function if possible, so it's only loaded once
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  model = whisper.load_model("base")
 
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  # Process segments in parallel using multiprocessing
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+ pool = multiprocessing.Pool()
 
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  print("Starting the processes....")
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  results = pool.map(process_segment, audio_segments)
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  pool.close()
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+ pool.join()
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  # Combine the results
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+ text = ' '.join(results)
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+ return text
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+
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  import os
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  from pydub import AudioSegment
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  return audio_segments
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+ def process_segment(segment_path: str) -> str:
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  # Load the model for each process if necessary
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  print(f"Processing segment : {segment_path}")
 
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  return "complete"
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  ad = gr.components.Audio(type='filepath')
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+ iface = gr.Interface(fn=convert_to_text, inputs=ad, outputs="text")
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  iface.launch()
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