Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -136,7 +136,7 @@ def process_transcript(language: str, audio_path: str) -> str:
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# Transcription process
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try:
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for path in list_audio_path:
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inputs = processor.
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audio=path, model_id=model_name)
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inputs = inputs.to(device, dtype=torch.bfloat16)
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outputs = model.generate(**inputs, max_new_tokens=MAX_TOKENS)
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@@ -246,7 +246,7 @@ def voice_extract_demucs():
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]
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subprocess.run(cmd, check=True)
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voice_path = os.path.join("demucs", "htdemucs", "audio_file", "vocals.wav")
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success_message = "β
**Success!** Voice extracted."
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return voice_path, voice_path, gr.Markdown(success_message)
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except Exception as e:
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return None, None, gr.Markdown(f"β **Error:** An unexpected ERROR occurred: {e}")
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@@ -404,31 +404,13 @@ def secure_download_youtube_audio(url: str):
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return None, None, gr.Markdown(f"β **Error:** An unexpected ERROR occurred: {e}")
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###
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def voice_extract_demucs():
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"""
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Returns the path of the voice extracted file.
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"""
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try:
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cmd = [
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"demucs",
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"--two-stems=vocals",
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"--out", "demucs",
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"audio_file.wav"
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]
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subprocess.run(cmd, check=True)
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voice_path = os.path.join("demucs", "htdemucs", "audio_file", "vocals.wav")
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success_message = "β
**Success!** Voice extracted."
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return voice_path, voice_path, gr.Markdown(success_message)
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except Exception as e:
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return None, None, gr.Markdown(f"β **Error:** An unexpected ERROR occurred: {e}")
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###
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def clear_audio():
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return None, None, None, None
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###
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def get_sel_audio(audio_path: str) -> str:
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return audio_path
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###
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#### Gradio interface
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@@ -471,11 +453,11 @@ with gr.Blocks(title="Voxtral") as voxtral:
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)
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status_output1 = gr.Markdown()
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with gr.Row():
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voice_button0 = gr.Button("Process original audio")
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voice_button0.click(
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fn=get_sel_audio,
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inputs=sel_audio1,
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outputs=[sel_audio])
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voice_button1 = gr.Button("Extract voice (if noisy environment)")
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voice_button1.click(
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fn=voice_extract_demucs,
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# Transcription process
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try:
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for path in list_audio_path:
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inputs = processor.apply_transcription_request(language=id_language,
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audio=path, model_id=model_name)
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inputs = inputs.to(device, dtype=torch.bfloat16)
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outputs = model.generate(**inputs, max_new_tokens=MAX_TOKENS)
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]
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subprocess.run(cmd, check=True)
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voice_path = os.path.join("demucs", "htdemucs", "audio_file", "vocals.wav")
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success_message = "β
**Success!** Voice extracted. ("+voice_path+")"
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return voice_path, voice_path, gr.Markdown(success_message)
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except Exception as e:
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return None, None, gr.Markdown(f"β **Error:** An unexpected ERROR occurred: {e}")
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return None, None, gr.Markdown(f"β **Error:** An unexpected ERROR occurred: {e}")
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###
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def clear_audio():
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return None, None, None, None
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###
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def get_sel_audio(audio_path: str) -> str:
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return audio_path, gr.Markdown("β
**Original** audio is considered.")
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###
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#### Gradio interface
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)
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status_output1 = gr.Markdown()
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with gr.Row():
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voice_button0 = gr.Button("Process original audio", variant="primary")
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voice_button0.click(
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fn=get_sel_audio,
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inputs=sel_audio1,
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outputs=[sel_audio, status_output1])
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voice_button1 = gr.Button("Extract voice (if noisy environment)")
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voice_button1.click(
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fn=voice_extract_demucs,
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