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Update app.py
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app.py
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@@ -1,5 +1,5 @@
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import os
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from flask import Flask, request, jsonify, send_file
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import torch
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import torchaudio
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import librosa
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@@ -13,6 +13,7 @@ from modules.bigvgan import bigvgan
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from transformers import AutoFeatureExtractor, WhisperModel
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from modules.audio import mel_spectrogram
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from modules.rmvpe import RMVPE
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# Initialize Flask app
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app = Flask(__name__)
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@@ -134,13 +135,14 @@ def voice_conversion_api():
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output_wave = (output_wave * 32768.0).astype(np.int16)
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# Convert to MP3 and send the response
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output_wave.tobytes(), frame_rate=sr,
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sample_width=output_wave.dtype.itemsize, channels=1
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).export(format="mp3", bitrate="320k")
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return send_file(mp3_bytes, mimetype="audio/mpeg", as_attachment=True, download_name="converted_audio.mp3")
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if __name__ == "__main__":
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# Run the Flask app
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import os
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from flask import Flask, request, jsonify, send_file, Response
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import torch
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import torchaudio
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import librosa
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from transformers import AutoFeatureExtractor, WhisperModel
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from modules.audio import mel_spectrogram
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from modules.rmvpe import RMVPE
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from io import BytesIO
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# Initialize Flask app
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app = Flask(__name__)
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output_wave = (output_wave * 32768.0).astype(np.int16)
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# Convert to MP3 and send the response
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mp3_file = BytesIO()
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AudioSegment(
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output_wave.tobytes(), frame_rate=sr,
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sample_width=output_wave.dtype.itemsize, channels=1
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).export(mp3_file, format="mp3", bitrate="320k")
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mp3_file.seek(0) # Ensure the stream is at the beginning
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return send_file(mp3_file, mimetype="audio/mpeg", as_attachment=True, download_name="converted_audio.mp3")
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if __name__ == "__main__":
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# Run the Flask app
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