56 lines
2.1 KiB
Python
56 lines
2.1 KiB
Python
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import io
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import numpy as np
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import soundfile
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from flask import Flask, request, send_file
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from inference import infer_tool
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from inference import slicer
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app = Flask(__name__)
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@app.route("/wav2wav", methods=["POST"])
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def wav2wav():
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request_form = request.form
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audio_path = request_form.get("audio_path", None) # wav文件地址
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tran = int(float(request_form.get("tran", 0))) # 音调
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spk = request_form.get("spk", 0) # 说话人(id或者name都可以,具体看你的config)
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wav_format = request_form.get("wav_format", 'wav') # 范围文件格式
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infer_tool.format_wav(audio_path)
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chunks = slicer.cut(audio_path, db_thresh=-40)
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audio_data, audio_sr = slicer.chunks2audio(audio_path, chunks)
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audio = []
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for (slice_tag, data) in audio_data:
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print(f'#=====segment start, {round(len(data) / audio_sr, 3)}s======')
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length = int(np.ceil(len(data) / audio_sr * svc_model.target_sample))
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if slice_tag:
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print('jump empty segment')
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_audio = np.zeros(length)
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else:
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# padd
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pad_len = int(audio_sr * 0.5)
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data = np.concatenate([np.zeros([pad_len]), data, np.zeros([pad_len])])
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raw_path = io.BytesIO()
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soundfile.write(raw_path, data, audio_sr, format="wav")
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raw_path.seek(0)
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out_audio, out_sr = svc_model.infer(spk, tran, raw_path)
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svc_model.clear_empty()
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_audio = out_audio.cpu().numpy()
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pad_len = int(svc_model.target_sample * 0.5)
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_audio = _audio[pad_len:-pad_len]
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audio.extend(list(infer_tool.pad_array(_audio, length)))
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out_wav_path = io.BytesIO()
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soundfile.write(out_wav_path, audio, svc_model.target_sample, format=wav_format)
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out_wav_path.seek(0)
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return send_file(out_wav_path, download_name=f"temp.{wav_format}", as_attachment=True)
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if __name__ == '__main__':
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model_name = "logs/44k/G_60000.pth" # 模型地址
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config_name = "configs/config.json" # config地址
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svc_model = infer_tool.Svc(model_name, config_name)
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app.run(port=1145, host="0.0.0.0", debug=False, threaded=False)
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