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# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# 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.
# =============================================================================
"""Tests for third_party.tensorflow.contrib.ffmpeg.decode_audio_op."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os.path
import six
from tensorflow.contrib import ffmpeg
from tensorflow.python.framework import dtypes
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import resource_loader
from tensorflow.python.platform import test
class DecodeAudioOpTest(test.TestCase):
def _loadFileAndTest(self, filename, file_format, duration_sec,
samples_per_second, channel_count,
samples_per_second_tensor=None, feed_dict=None,
stream=None):
"""Loads an audio file and validates the output tensor.
Args:
filename: The filename of the input file.
file_format: The format of the input file.
duration_sec: The duration of the audio contained in the file in seconds.
samples_per_second: The desired sample rate in the output tensor.
channel_count: The desired channel count in the output tensor.
samples_per_second_tensor: The value to pass to the corresponding
parameter in the instantiated `decode_audio` op. If not
provided, will default to a constant value of
`samples_per_second`. Useful for providing a placeholder.
feed_dict: Used when evaluating the `decode_audio` op. If not
provided, will be empty. Useful when providing a placeholder for
`samples_per_second_tensor`.
stream: A string specifying which stream from the content file
should be decoded. The default value is '' which leaves the
decision to ffmpeg.
"""
if samples_per_second_tensor is None:
samples_per_second_tensor = samples_per_second
with self.cached_session():
path = os.path.join(resource_loader.get_data_files_path(), 'testdata',
filename)
with open(path, 'rb') as f:
contents = f.read()
audio_op = ffmpeg.decode_audio(
contents,
file_format=file_format,
samples_per_second=samples_per_second_tensor,
channel_count=channel_count, stream=stream)
audio = audio_op.eval(feed_dict=feed_dict or {})
self.assertEqual(len(audio.shape), 2)
self.assertNear(
duration_sec * samples_per_second,
audio.shape[0],
# Duration should be specified within 10%:
0.1 * audio.shape[0])
self.assertEqual(audio.shape[1], channel_count)
def testStreamIdentifier(self):
# mono_16khz_mp3_32khz_aac.mp4 was generated from:
# ffmpeg -i tensorflow/contrib/ffmpeg/testdata/mono_16khz_mp3.mp4 \
# -i tensorflow/contrib/ffmpeg/testdata/mono_32khz_aac.mp4 \
# -strict -2 -map 0:a -map 1:a \
# tensorflow/contrib/ffmpeg/testdata/mono_16khz_mp3_32khz_aac.mp4
self._loadFileAndTest('mono_16khz_mp3_32khz_aac.mp4', 'mp4', 2.77, 20000,
1, stream='0')
self._loadFileAndTest('mono_16khz_mp3_32khz_aac.mp4', 'mp4', 2.77, 20000,
1, stream='1')
def testMonoMp3(self):
self._loadFileAndTest('mono_16khz.mp3', 'mp3', 0.57, 20000, 1)
self._loadFileAndTest('mono_16khz.mp3', 'mp3', 0.57, 20000, 2)
def testMonoMp4Mp3Codec(self):
# mp3 compressed audio streams in mp4 container.
self._loadFileAndTest('mono_16khz_mp3.mp4', 'mp4', 2.77, 20000, 1)
self._loadFileAndTest('mono_16khz_mp3.mp4', 'mp4', 2.77, 20000, 2)
def testMonoMp4AacCodec(self):
# aac compressed audio streams in mp4 container.
self._loadFileAndTest('mono_32khz_aac.mp4', 'mp4', 2.77, 20000, 1)
self._loadFileAndTest('mono_32khz_aac.mp4', 'mp4', 2.77, 20000, 2)
def testStereoMp3(self):
self._loadFileAndTest('stereo_48khz.mp3', 'mp3', 0.79, 50000, 1)
self._loadFileAndTest('stereo_48khz.mp3', 'mp3', 0.79, 20000, 2)
def testStereoMp4Mp3Codec(self):
# mp3 compressed audio streams in mp4 container.
self._loadFileAndTest('stereo_48khz_mp3.mp4', 'mp4', 0.79, 50000, 1)
self._loadFileAndTest('stereo_48khz_mp3.mp4', 'mp4', 0.79, 20000, 2)
def testStereoMp4AacCodec(self):
# aac compressed audio streams in mp4 container.
self._loadFileAndTest('stereo_48khz_aac.mp4', 'mp4', 0.79, 50000, 1)
self._loadFileAndTest('stereo_48khz_aac.mp4', 'mp4', 0.79, 20000, 2)
def testMonoWav(self):
self._loadFileAndTest('mono_10khz.wav', 'wav', 0.57, 5000, 1)
self._loadFileAndTest('mono_10khz.wav', 'wav', 0.57, 10000, 4)
def testOgg(self):
self._loadFileAndTest('mono_10khz.ogg', 'ogg', 0.57, 10000, 1)
def testInvalidFile(self):
with self.cached_session():
contents = 'invalid file'
audio_op = ffmpeg.decode_audio(
contents,
file_format='wav',
samples_per_second=10000,
channel_count=2)
audio = audio_op.eval()
self.assertEqual(audio.shape, (0, 0))
def testSampleRatePlaceholder(self):
placeholder = array_ops.placeholder(dtypes.int32)
self._loadFileAndTest('mono_16khz.mp3', 'mp3', 0.57, 20000, 1,
samples_per_second_tensor=placeholder,
feed_dict={placeholder: 20000})
def testSampleRateBadType(self):
placeholder = array_ops.placeholder(dtypes.float32)
with self.assertRaises(TypeError):
self._loadFileAndTest('mono_16khz.mp3', 'mp3', 0.57, 20000.0, 1,
samples_per_second_tensor=placeholder,
feed_dict={placeholder: 20000.0})
def testSampleRateBadValue_Zero(self):
placeholder = array_ops.placeholder(dtypes.int32)
with six.assertRaisesRegex(self, Exception,
r'samples_per_second must be positive'):
self._loadFileAndTest('mono_16khz.mp3', 'mp3', 0.57, 20000.0, 1,
samples_per_second_tensor=placeholder,
feed_dict={placeholder: 0})
def testSampleRateBadValue_Negative(self):
placeholder = array_ops.placeholder(dtypes.int32)
with six.assertRaisesRegex(self, Exception,
r'samples_per_second must be positive'):
self._loadFileAndTest('mono_16khz.mp3', 'mp3', 0.57, 20000.0, 1,
samples_per_second_tensor=placeholder,
feed_dict={placeholder: -2})
def testInvalidFileFormat(self):
with six.assertRaisesRegex(self, Exception,
r'file_format must be one of'):
self._loadFileAndTest('mono_16khz.mp3', 'docx', 0.57, 20000, 1)
def testStaticShapeInference_ConstantChannelCount(self):
with self.cached_session():
audio_op = ffmpeg.decode_audio(b'~~~ wave ~~~',
file_format='wav',
samples_per_second=44100,
channel_count=2)
self.assertEqual([None, 2], audio_op.shape.as_list())
def testStaticShapeInference_NonConstantChannelCount(self):
with self.cached_session():
channel_count = array_ops.placeholder(dtypes.int32)
audio_op = ffmpeg.decode_audio(b'~~~ wave ~~~',
file_format='wav',
samples_per_second=44100,
channel_count=channel_count)
self.assertEqual([None, None], audio_op.shape.as_list())
def testStaticShapeInference_ZeroChannelCountInvalid(self):
with self.cached_session():
with six.assertRaisesRegex(self, Exception,
r'channel_count must be positive'):
ffmpeg.decode_audio(b'~~~ wave ~~~',
file_format='wav',
samples_per_second=44100,
channel_count=0)
def testStaticShapeInference_NegativeChannelCountInvalid(self):
with self.cached_session():
with six.assertRaisesRegex(self, Exception,
r'channel_count must be positive'):
ffmpeg.decode_audio(b'~~~ wave ~~~',
file_format='wav',
samples_per_second=44100,
channel_count=-2)
if __name__ == '__main__':
test.main()
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