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