#!/usr/bin/env python3 # Copyright 2018 Mycroft AI Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import sys from prettyparse import create_parser from precise import __version__ from precise.network_runner import Listener usage = ''' stdin should be a stream of raw int16 audio, written in groups of CHUNK_SIZE samples. If no CHUNK_SIZE is given it will read until EOF. For every chunk, an inference will be given via stdout as a float string, one per line :model_name str Keras or TensorFlow model to read from ... ''' def main(): os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' stdout = sys.stdout sys.stdout = sys.stderr parser = create_parser(usage) parser.add_argument('-v', '--version', action='version', version=__version__) parser.add_argument('chunk_size', type=int, nargs='?', default=-1, help='Number of bytes to read before making a prediction.' 'Higher values are less computationally expensive') parser.usage = parser.format_usage().strip().replace('usage: ', '') + ' < audio.wav' args = parser.parse_args() if sys.stdin.isatty(): parser.error('Please pipe audio via stdin using < audio.wav') listener = Listener(args.model_name, args.chunk_size) try: while True: conf = listener.update(sys.stdin.buffer) stdout.buffer.write((str(conf) + '\n').encode('ascii')) stdout.buffer.flush() except (EOFError, KeyboardInterrupt): pass if __name__ == '__main__': main()