Zw07 commited on
Commit
5f9384d
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1 Parent(s): e285ae0

Update app.py

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Files changed (1) hide show
  1. app.py +36 -33
app.py CHANGED
@@ -126,49 +126,52 @@ def main():
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  # f.write(audio_file.getbuffer())
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  # st.audio(tmp_input_audio_file, format="mp3/wav")
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-
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- # Save file to local storage
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- tmp_input_audio_file = os.path.join("/tmp/", audio_file.name)
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- file_extension = os.path.splitext(tmp_input_audio_file)[1].lower()
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- st.markdown(file_extension)
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- if file_extension in [".wav", ".flac"]:
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- with open("test.wav", "wb") as f:
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- f.write(audio_file.getbuffer())
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- st.audio("test.wav", format="audio/wav")
 
 
 
 
 
 
 
 
 
 
 
 
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- elif file_extension == ".mp3":
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- with open("test.mp3", "wb") as f:
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- f.write(audio_file.getbuffer())
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- st.audio("test.mp3", format="audio/mpeg")
 
 
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- # # Convert MP3 to WAV using pydub
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- # mp3_audio = AudioSegment.from_mp3(tmp_input_audio_file)
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- # wav_output_file = tmp_input_audio_file.replace(".mp3", ".wav")
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- # mp3_audio.export(wav_output_file, format="wav")
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  # Load the WAV file using torchaudio
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- if file_extension in [".wav", ".flac"]:
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- wav, sample_rate = torchaudio.load("test.wav")
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- st.markdown("Before unsquueze wav")
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- st.markdown(wav)
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- #Unsqueeze for line 176
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- wav= wav.unsqueeze(0)
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- elif file_extension == ".mp3":
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- wav3, sample_rate = librosa.load("test.mp3")
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- st.markdown(wav3)
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- #RuntimeError: Could not infer dtype of numpy.float32
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- #wav = torch.tensor(wav3).float() / 32768.0
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- #RuntimeError: Numpy is not available
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- wav = torch.from_numpy(wav3) #/32768.0
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- wav = wav.unsqueeze(0).unsqueeze(0)
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- st.markdown("Before unsqueeze mp3")
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- st.markdown(wav)
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  # #Unsqueeze for line 176
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  # wav= wav.unsqueeze(0)
 
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  # f.write(audio_file.getbuffer())
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  # st.audio(tmp_input_audio_file, format="mp3/wav")
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+ #1st attempt
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+ audio_path = "C:\Users\Zw\Downloads\example.mp3"
 
 
 
 
 
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+ audio, sr = torchaudio.load(audio_path)
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+ st.audio(audio_path, format="audio/mpeg")
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+ audio= audio.unsqueeze(0)
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+
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+
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+ #2nd attempt
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+ # Save file to local storage
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+ # tmp_input_audio_file = os.path.join("/tmp/", audio_file.name)
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+ # file_extension = os.path.splitext(tmp_input_audio_file)[1].lower()
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+ # st.markdown(file_extension)
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+ # if file_extension in [".wav", ".flac"]:
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+ # with open("test.wav", "wb") as f:
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+ # f.write(audio_file.getbuffer())
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+ # st.audio("test.wav", format="audio/wav")
 
 
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+ # elif file_extension == ".mp3":
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+ # with open("test.mp3", "wb") as f:
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+ # f.write(audio_file.getbuffer())
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+ # st.audio("test.mp3", format="audio/mpeg")
 
 
 
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  # Load the WAV file using torchaudio
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+ # if file_extension in [".wav", ".flac"]:
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+ # wav, sample_rate = torchaudio.load("test.wav")
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+ # st.markdown("Before unsquueze wav")
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+ # st.markdown(wav)
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+ # #Unsqueeze for line 176
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+ # wav= wav.unsqueeze(0)
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+ # elif file_extension == ".mp3":
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+ # wav3, sample_rate = librosa.load("test.mp3")
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+ # st.markdown(wav3)
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+ # #RuntimeError: Could not infer dtype of numpy.float32
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+ # #wav = torch.tensor(wav3).float() / 32768.0
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+ # #RuntimeError: Numpy is not available
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+ # wav = torch.from_numpy(wav3) #/32768.0
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+ # wav = wav.unsqueeze(0).unsqueeze(0)
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+ # st.markdown("Before unsqueeze mp3")
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+ # st.markdown(wav)
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  # #Unsqueeze for line 176
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  # wav= wav.unsqueeze(0)