Spaces:
Runtime error
Runtime error
Cleanup results for many uploads
Browse files
app.py
CHANGED
@@ -21,7 +21,7 @@ def get_supported_codes():
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return supported_codes
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def get_path_to_wav_format(uploaded_file):
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# st.write(dir(uploaded_file))
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# st.write(type(uploaded_file))
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# st.write(uploaded_file)
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@@ -36,9 +36,10 @@ def get_path_to_wav_format(uploaded_file):
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new_desired_path = actual_file_path.with_suffix(".wav")
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encoding="PCM_S" # Prevent encoding errors. https://stackoverflow.com/questions/60352850/wave-error-unknown-format-3-arises-when-trying-to-convert-a-wav-file-into-text
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bits_per_sample=16
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st.info(f"Allosaurus requires .wav files. Converting with torchaudio, encoding={encoding}, bits_per_sample={bits_per_sample}")
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waveform, sample_rate = torchaudio.load(actual_file_path)
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torchaudio.save(new_desired_path, waveform, sample_rate,
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encoding=encoding,
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bits_per_sample=bits_per_sample,
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@@ -99,18 +100,14 @@ if __name__ == "__main__":
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)
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results = {} # for better download/display
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for uploaded_file in uploaded_files:
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if uploaded_file is not None:
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st.audio(uploaded_file, format='audio/wav')
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wav_file = get_path_to_wav_format(uploaded_file)
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# st.write(wav_file)
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result = model.recognize(wav_file, langcode)
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results[uploaded_file.name] = result
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# st.write(result)
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st.write(results)
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return supported_codes
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def get_path_to_wav_format(uploaded_file, suppress_outputs=False):
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# st.write(dir(uploaded_file))
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# st.write(type(uploaded_file))
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# st.write(uploaded_file)
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new_desired_path = actual_file_path.with_suffix(".wav")
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encoding="PCM_S" # Prevent encoding errors. https://stackoverflow.com/questions/60352850/wave-error-unknown-format-3-arises-when-trying-to-convert-a-wav-file-into-text
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bits_per_sample=16
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waveform, sample_rate = torchaudio.load(actual_file_path)
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if not suppress_outputs:
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st.info(f"Allosaurus requires .wav files. Converting with torchaudio, encoding={encoding}, bits_per_sample={bits_per_sample}")
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st.info(f"Uploaded file sample_rate: {sample_rate}")
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torchaudio.save(new_desired_path, waveform, sample_rate,
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encoding=encoding,
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bits_per_sample=bits_per_sample,
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)
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results = {} # for better download/display
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uploaded_files_count = len(uploaded_files)
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suppress_output_threshold = 2
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for uploaded_file in uploaded_files:
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if uploaded_file is not None:
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wav_file = get_path_to_wav_format(uploaded_file, uploaded_files_count>suppress_output_threshold)
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result = model.recognize(wav_file, langcode)
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results[uploaded_file.name] = result
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st.write(results)
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