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429 lines
14 KiB
429 lines
14 KiB
#!/usr/bin/env python
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# encoding: utf-8
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"""
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`auditok` -- An Audio Activity Detection tool
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`auditok` is a program that can be used for Audio/Acoustic
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activity detection. It can read audio data from audio files as well
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as from the microphone or standard input.
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@author: Mohamed El Amine SEHILI
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@copyright: 2015-2021 Mohamed El Amine SEHILI
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@license: MIT
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@contact: amine.sehili@gmail.com
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@deffield updated: 01 Mar 2021
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"""
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import sys
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import os
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from argparse import ArgumentParser
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import time
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import threading
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from auditok import __version__, AudioRegion
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from .util import AudioDataSource
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from .exceptions import EndOfProcessing, AudioEncodingWarning
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from .io import player_for
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from .cmdline_util import make_logger, make_kwargs, initialize_workers
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from . import workers
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__all__ = []
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__date__ = "2015-11-23"
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__updated__ = "2021-03-01"
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def main(argv=None):
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program_name = os.path.basename(sys.argv[0])
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if argv is None:
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argv = sys.argv[1:]
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try:
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parser = ArgumentParser(
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prog=program_name, description="An Audio Tokenization tool"
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)
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parser.add_argument(
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"--version", "-v", action="version", version=__version__
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)
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group = parser.add_argument_group("Input-Output options")
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group.add_argument(
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dest="input",
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help="Input audio or video file. Use '-' for stdin "
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"[default: read from microphone using pyaudio]",
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metavar="input",
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nargs="?",
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default=None,
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)
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group.add_argument(
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"-I",
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"--input-device-index",
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dest="input_device_index",
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help="Audio device index [default: %(default)s]. "
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"Optional and only effective when using PyAudio",
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type=int,
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default=None,
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metavar="INT",
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)
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group.add_argument(
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"-F",
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"--audio-frame-per-buffer",
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dest="frame_per_buffer",
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help="Audio frame per buffer [default: %(default)s]. "
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"Optional and only effective when using PyAudio",
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type=int,
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default=1024,
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metavar="INT",
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)
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group.add_argument(
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"-f",
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"--input-format",
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dest="input_format",
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type=str,
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default=None,
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help="Input audio file format. If not given, guess format from "
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"extension. If output file name has no extension, guess format "
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"from file header (requires pydub). If none of the previous is "
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"true, raise an error",
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metavar="STRING",
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)
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group.add_argument(
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"-M",
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"--max-read",
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dest="max_read",
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type=float,
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default=None,
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help="Maximum data (in seconds) to read from microphone or file "
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"[default: read until the end of file/stream]",
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metavar="FLOAT",
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)
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group.add_argument(
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"-L",
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"--large-file",
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dest="large_file",
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action="store_true",
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default=False,
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help="Whether input file should be treated as a large file. "
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"If True, data will be read from file on demand, otherwise all "
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"audio data is loaded to memory before tokenization.",
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)
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group.add_argument(
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"-O",
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"--save-stream",
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dest="save_stream",
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type=str,
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default=None,
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help="Save acquired audio data (from file or microphone) to disk."
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" If omitted no data will be saved. [default: omitted]",
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metavar="FILE",
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)
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group.add_argument(
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"-o",
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"--save-detections-as",
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dest="save_detections_as",
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type=str,
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default=None,
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help="File name format for detections."
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"The following placeholders can be used to build output file name "
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"for each detection: {id} (sequential, starts from 1), {start}, "
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"{end} and {duration}. Time placeholders are in seconds. "
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"Example: 'Event_{id}_{start}-{end}_{duration:.3f}.wav'",
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metavar="STRING",
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)
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group.add_argument(
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"-T",
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"--output-format",
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dest="output_format",
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type=str,
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default=None,
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help="Audio format used to save detections and/or main stream. "
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"If not supplied, then it will: (1. be guessed from extension or "
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"(2. use raw format",
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metavar="STRING",
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)
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group.add_argument(
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"-u",
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"--use-channel",
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dest="use_channel",
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type=str,
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default=None,
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help="Which channel to use for tokenization when input stream is "
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"multi-channel (0 is the first channel). Default is None, meaning "
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"that all channels will be considered for tokenization (i.e., get "
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"any valid audio event regardless of the channel it occurs in). "
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"This value can also be 'mix' (alias 'avg' or 'average') and "
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"means mix down all audio channels into one channel (i.e. compute "
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"average channel) and use the resulting channel for tokenization. "
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"Whatever option is used, saved audio events will contain the same"
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" number of channels as input stream. "
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"[Default: None, use all channels]",
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metavar="INT/STRING",
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)
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group = parser.add_argument_group(
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"Tokenization options", "Set tokenizer options."
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)
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group.add_argument(
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"-a",
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"--analysis-window",
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dest="analysis_window",
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default=0.01,
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type=float,
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help="Size of analysis window in seconds [default: %(default)s "
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"(10ms)]",
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metavar="FLOAT",
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)
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group.add_argument(
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"-n",
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"--min-duration",
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dest="min_duration",
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type=float,
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default=0.2,
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help="Min duration of a valid audio event in seconds "
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"[default: %(default)s]",
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metavar="FLOAT",
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)
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group.add_argument(
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"-m",
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"--max-duration",
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dest="max_duration",
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type=float,
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default=5,
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help="Max duration of a valid audio event in seconds "
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"[default: %(default)s]",
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metavar="FLOAT",
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)
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group.add_argument(
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"-s",
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"--max-silence",
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dest="max_silence",
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type=float,
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default=0.3,
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help="Max duration of a consecutive silence within a valid audio "
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"event in seconds [default: %(default)s]",
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metavar="FLOAT",
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)
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group.add_argument(
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"-d",
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"--drop-trailing-silence",
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dest="drop_trailing_silence",
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action="store_true",
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default=False,
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help="Drop trailing silence from a detection [default: keep "
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"trailing silence]",
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)
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group.add_argument(
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"-R",
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"--strict-min-duration",
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dest="strict_min_duration",
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action="store_true",
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default=False,
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help="Reject an event shorter than --min-duration even if it's "
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"adjacent to the latest valid event that reached max-duration "
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"[default: keep such events]",
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)
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group.add_argument(
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"-e",
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"--energy-threshold",
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dest="energy_threshold",
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type=float,
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default=50,
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help="Log energy threshold for detection [default: %(default)s]",
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metavar="FLOAT",
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)
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group = parser.add_argument_group(
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"Audio parameters",
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"Define audio parameters if data is read from a "
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"headerless file (raw or stdin) or you want to use "
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"different microphone parameters.",
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)
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group.add_argument(
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"-r",
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"--rate",
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dest="sampling_rate",
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type=int,
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default=16000,
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help="Sampling rate of audio data [default: %(default)s]",
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metavar="INT",
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)
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group.add_argument(
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"-c",
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"--channels",
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dest="channels",
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type=int,
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default=1,
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help="Number of channels of audio data [default: %(default)s]",
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metavar="INT",
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)
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group.add_argument(
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"-w",
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"--width",
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dest="sample_width",
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type=int,
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default=2,
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help="Number of bytes per audio sample [default: %(default)s]",
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metavar="INT",
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)
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group = parser.add_argument_group(
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"Do something with audio events",
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"Use these options to print, play back or plot detections.",
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)
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group.add_argument(
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"-C",
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"--command",
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dest="command",
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type=str,
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help="Command to call when an audio detection occurs. Use '{file}' "
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"as a placeholder for the temporary wav file that will contain "
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"event's data (e.g., \"-C 'du -h {file}'\" to print out file size "
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" or \"-C 'play -q {file}'\" to play audio with sox)",
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metavar="STRING",
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)
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group.add_argument(
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"-E",
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"--echo",
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dest="echo",
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action="store_true",
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default=False,
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help="Play back each detection immediately using pyaudio",
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)
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group.add_argument(
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"-B",
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"--progress-bar",
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dest="progress_bar",
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action="store_true",
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default=False,
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help="Show a progress bar when playing audio",
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)
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group.add_argument(
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"-p",
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"--plot",
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dest="plot",
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action="store_true",
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default=False,
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help="Plot and show audio signal and detections (requires "
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"matplotlib)",
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)
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group.add_argument(
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"--save-image",
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dest="save_image",
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type=str,
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help="Save plotted audio signal and detections as a picture or a "
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"PDF file (requires matplotlib)",
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metavar="FILE",
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)
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group.add_argument(
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"--printf",
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dest="printf",
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type=str,
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default="{id} {start} {end}",
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help="Print audio events information, one per line, using this "
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"format. Format can contain text with the following placeholders: "
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"{id} (sequential, starts from 1), {start}, {end}, {duration} and "
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"{timestamp}. The first 3 time placeholders are in seconds and "
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"their format can be set using --time-format argument. "
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"{timestamp} is the system timestamp (date and time) of the event "
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"and can be set using --timestamp-format argument.\n"
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"Example: '[{id}]: {start} -> {end} -- {timestamp}'",
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metavar="STRING",
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)
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group.add_argument(
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"--time-format",
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dest="time_format",
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type=str,
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default="%S",
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help="Format used to print {start}, {end} and {duration} "
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"placeholders used with --printf [default= %(default)s]. The "
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"following formats are accepted:\n"
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"%%S: absolute time in seconds. %%I: absolute time in ms. If at "
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"least one of (%%h, %%m, %%s, %%i) is used, convert time into "
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"hours, minutes, seconds and millis (e.g. %%h:%%m:%%s.%%i). Only "
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"supplied fields are printed. Note that %%S and %%I can only be "
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"used alone",
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metavar="STRING",
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)
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group.add_argument(
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"--timestamp-format",
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dest="timestamp_format",
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type=str,
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default="%Y/%m/%d %H:%M:%S",
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help="Format used to print {timestamp}. Should be a format "
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"accepted by 'datetime' standard module. Default: "
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"'%%Y/%%m/%%d %%H:%%M:%%S'",
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)
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parser.add_argument(
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"-q",
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"--quiet",
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dest="quiet",
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action="store_true",
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default=False,
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help="Do not print any information about detections [default: "
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"print 'id', 'start' and 'end' of each detection]",
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)
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parser.add_argument(
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"-D",
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"--debug",
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dest="debug",
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action="store_true",
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default=False,
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help="Print processing operations to STDOUT",
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)
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parser.add_argument(
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"--debug-file",
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dest="debug_file",
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type=str,
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default=None,
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help="Print processing operations to FILE",
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metavar="FILE",
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)
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args = parser.parse_args(argv)
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logger = make_logger(args.debug, args.debug_file)
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kwargs = make_kwargs(args)
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reader, observers = initialize_workers(
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logger=logger, **kwargs.io, **kwargs.miscellaneous
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)
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tokenizer_worker = workers.TokenizerWorker(
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reader, observers, logger=logger, **kwargs.split
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)
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tokenizer_worker.start_all()
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while True:
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time.sleep(1)
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if len(threading.enumerate()) == 1:
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raise EndOfProcessing
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except (KeyboardInterrupt, EndOfProcessing):
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if tokenizer_worker is not None:
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tokenizer_worker.stop_all()
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if isinstance(reader, workers.StreamSaverWorker):
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reader.join()
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try:
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reader.save_stream()
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except AudioEncodingWarning as ae_warn:
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print(str(ae_warn), file=sys.stderr)
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if args.plot or args.save_image is not None:
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from .plotting import plot
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reader.rewind()
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record = AudioRegion(
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reader.data, reader.sr, reader.sw, reader.ch
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)
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detections = (
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(det.start, det.end) for det in tokenizer_worker.detections
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)
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plot(
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record,
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detections=detections,
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energy_threshold=args.energy_threshold,
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show=True,
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save_as=args.save_image,
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)
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return 0
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if __name__ == "__main__":
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sys.exit(main(None))
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