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