#!/usr/bin/env python3 import argparse import logging from distutils.util import strtobool from paddlespeech.audio.transform.transformation import Transformation from paddlespeech.s2t.utils.cli_readers import file_reader_helper from paddlespeech.s2t.utils.cli_utils import get_commandline_args from paddlespeech.s2t.utils.cli_utils import is_scipy_wav_style from paddlespeech.s2t.utils.cli_writers import file_writer_helper def get_parser(): parser = argparse.ArgumentParser( description="copy feature with preprocessing", formatter_class=argparse.ArgumentDefaultsHelpFormatter, ) parser.add_argument( "--verbose", "-V", default=0, type=int, help="Verbose option") parser.add_argument( "--in-filetype", type=str, default="mat", choices=["mat", "hdf5", "sound.hdf5", "sound"], help="Specify the file format for the rspecifier. " '"mat" is the matrix format in kaldi', ) parser.add_argument( "--out-filetype", type=str, default="mat", choices=["mat", "hdf5", "sound.hdf5", "sound"], help="Specify the file format for the wspecifier. " '"mat" is the matrix format in kaldi', ) parser.add_argument( "--write-num-frames", type=str, help="Specify wspecifer for utt2num_frames") parser.add_argument( "--compress", type=strtobool, default=False, help="Save in compressed format") parser.add_argument( "--compression-method", type=int, default=2, help="Specify the method(if mat) or " "gzip-level(if hdf5)", ) parser.add_argument( "--preprocess-conf", type=str, default=None, help="The configuration file for the pre-processing", ) parser.add_argument( "rspecifier", type=str, help="Read specifier for feats. e.g. ark:some.ark") parser.add_argument( "wspecifier", type=str, help="Write specifier. e.g. ark:some.ark") return parser def main(): parser = get_parser() args = parser.parse_args() # logging info logfmt = "%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s" if args.verbose > 0: logging.basicConfig(level=logging.INFO, format=logfmt) else: logging.basicConfig(level=logging.WARN, format=logfmt) logging.info(get_commandline_args()) if args.preprocess_conf is not None: preprocessing = Transformation(args.preprocess_conf) logging.info("Apply preprocessing: {}".format(preprocessing)) else: preprocessing = None with file_writer_helper( args.wspecifier, filetype=args.out_filetype, write_num_frames=args.write_num_frames, compress=args.compress, compression_method=args.compression_method, ) as writer: for utt, mat in file_reader_helper(args.rspecifier, args.in_filetype): if is_scipy_wav_style(mat): # If data is sound file, then got as Tuple[int, ndarray] rate, mat = mat if preprocessing is not None: mat = preprocessing(mat, uttid_list=utt) # shape = (Time, Channel) if args.out_filetype in ["sound.hdf5", "sound"]: # Write Tuple[int, numpy.ndarray] (scipy style) writer[utt] = (rate, mat) else: writer[utt] = mat if __name__ == "__main__": main()