infer_record.py

import argparse
import functools

from macls.predict import PPAClsPredictor
from macls.utils.record import RecordAudio
from macls.utils.utils import add_arguments, print_arguments

parser = argparse.ArgumentParser(description=__doc__)
add_arg = functools.partial(add_arguments, argparser=parser)
add_arg('configs',          str,    'configs/ecapa_tdnn.yml',   '配置文件')
add_arg('use_gpu',          bool,   True,                       '是否使用GPU预测')
add_arg('record_seconds',   int,    3,                          '录音长度')
add_arg('model_path',       str,    'models/ecapa_tdnn_MelSpectrogram/best_model/', '导出的预测模型文件路径')
args = parser.parse_args()
print_arguments(args=args)

# 获取识别器
predictor = PPAClsPredictor(configs=args.configs,
                            model_path=args.model_path,
                            use_gpu=args.use_gpu)

record_audio = RecordAudio()

if __name__ == '__main__':
    try:
        while True:
            # 加载数据
            audio_path = record_audio.record(record_seconds=args.record_seconds)
            # 获取预测结果
            label, s = predictor.predict(audio_path)
            print(f'预测的标签为：{label}，得分：{s}')
    except Exception as e:
        print(e)
        record_audio.close()