# 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. # ============================================================================= """Encoding and decoding audio using FFmpeg.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function from tensorflow.contrib.ffmpeg.ops import gen_decode_audio_op_py from tensorflow.contrib.ffmpeg.ops import gen_decode_video_op_py from tensorflow.contrib.ffmpeg.ops import gen_encode_audio_op_py from tensorflow.contrib.util import loader from tensorflow.python.framework import ops from tensorflow.python.platform import resource_loader from tensorflow.python.util.deprecation import deprecated _ffmpeg_so = loader.load_op_library( resource_loader.get_path_to_datafile('ffmpeg.so')) @deprecated('2018-09-04', 'This will be deleted and should not be used.') def decode_audio(contents, file_format=None, samples_per_second=None, channel_count=None, stream=None): """Create an op that decodes the contents of an audio file. Note that ffmpeg is free to select the "best" audio track from an mp4. https://trac.ffmpeg.org/wiki/Map Args: contents: The binary contents of the audio file to decode. This is a scalar. file_format: A string or scalar string tensor specifying which format the contents will conform to. This can be mp3, mp4, ogg, or wav. samples_per_second: The number of samples per second that is assumed, as an `int` or scalar `int32` tensor. In some cases, resampling will occur to generate the correct sample rate. channel_count: The number of channels that should be created from the audio contents, as an `int` or scalar `int32` tensor. If the `contents` have more than this number, then some channels will be merged or dropped. If `contents` has fewer than this, then additional channels will be created from the existing ones. stream: A string specifying which stream from the content file should be decoded, e.g., '0' means the 0-th stream. The default value is '' which leaves the decision to ffmpeg. Returns: A rank-2 tensor that has time along dimension 0 and channels along dimension 1. Dimension 0 will be `samples_per_second * length_in_seconds` wide, and dimension 1 will be `channel_count` wide. If ffmpeg fails to decode the audio then an empty tensor will be returned. """ return gen_decode_audio_op_py.decode_audio_v2( contents, file_format=file_format, samples_per_second=samples_per_second, channel_count=channel_count, stream=stream) ops.NotDifferentiable('DecodeAudio') @deprecated('2018-09-04', 'This will be deleted and should not be used.') def encode_audio(audio, file_format=None, samples_per_second=None): """Creates an op that encodes an audio file using sampled audio from a tensor. Args: audio: A rank-2 `Tensor` that has time along dimension 0 and channels along dimension 1. Dimension 0 is `samples_per_second * length_in_seconds` long. file_format: The type of file to encode, as a string or rank-0 string tensor. "wav" is the only supported format. samples_per_second: The number of samples in the audio tensor per second of audio, as an `int` or rank-0 `int32` tensor. Returns: A scalar tensor that contains the encoded audio in the specified file format. """ return gen_encode_audio_op_py.encode_audio_v2( audio, file_format=file_format, samples_per_second=samples_per_second, bits_per_second=192000) # not used by WAV ops.NotDifferentiable('EncodeAudio') @deprecated('2018-09-04', 'This will be deleted and should not be used.') def decode_video(contents): """Create an op that decodes the contents of a video file. Args: contents: The binary contents of the video file to decode. This is a scalar. Returns: A rank-4 `Tensor` that has `[frames, height, width, 3]` RGB as output. """ return gen_decode_video_op_py.decode_video(contents) ops.NotDifferentiable('DecodeVideo')