# Copyright (c) 2022 PaddlePaddle 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. from __future__ import annotations import wave from typing import TYPE_CHECKING, BinaryIO import numpy as np import paddle from .backend import AudioInfo if TYPE_CHECKING: from pathlib import Path from paddle import Tensor def _error_message(): package = "paddleaudio" warn_msg = ( "only PCM16 WAV supported. \n" "if want support more other audio types, please " f"manually installed (usually with `pip install {package}`). \n " "and use paddle.audio.backends.set_backend('soundfile') to set audio backend" ) return warn_msg def info(filepath: str | BinaryIO) -> AudioInfo: """Get signal information of input audio file. Args: filepath: audio path or file object. Returns: AudioInfo: info of the given audio. Example: .. code-block:: python >>> import os >>> import paddle >>> sample_rate = 16000 >>> wav_duration = 0.5 >>> num_channels = 1 >>> num_frames = sample_rate * wav_duration >>> wav_data = paddle.linspace(-1.0, 1.0, int(num_frames)) * 0.1 >>> waveform = wav_data.tile([num_channels, 1]) >>> base_dir = os.getcwd() >>> filepath = os.path.join(base_dir, "test.wav") >>> paddle.audio.save(filepath, waveform, sample_rate) >>> wav_info = paddle.audio.info(filepath) """ if hasattr(filepath, 'read'): file_obj = filepath else: file_obj = open(filepath, 'rb') try: file_ = wave.open(file_obj) except wave.Error: file_obj.seek(0) file_obj.close() err_msg = _error_message() raise NotImplementedError(err_msg) channels = file_.getnchannels() sample_rate = file_.getframerate() sample_frames = file_.getnframes() # audio frame bits_per_sample = file_.getsampwidth() * 8 encoding = "PCM_S" # default WAV encoding, only support file_obj.close() return AudioInfo( sample_rate, sample_frames, channels, bits_per_sample, encoding ) def load( filepath: str | Path, frame_offset: int = 0, num_frames: int = -1, normalize: bool = True, channels_first: bool = True, ) -> tuple[Tensor, int]: """Load audio data from file. load the audio content start form frame_offset, and get num_frames. Args: frame_offset: from 0 to total frames, num_frames: from -1 (means total frames) or number frames which want to read, normalize: if True: return audio which norm to (-1, 1), dtype=float32 if False: return audio with raw data, dtype=int16 channels_first: if True: return audio with shape (channels, time) Return: Tuple[paddle.Tensor, int]: (audio_content, sample rate) Examples: .. code-block:: python >>> import os >>> import paddle >>> sample_rate = 16000 >>> wav_duration = 0.5 >>> num_channels = 1 >>> num_frames = sample_rate * wav_duration >>> wav_data = paddle.linspace(-1.0, 1.0, int(num_frames)) * 0.1 >>> waveform = wav_data.tile([num_channels, 1]) >>> base_dir = os.getcwd() >>> filepath = os.path.join(base_dir, "test.wav") >>> paddle.audio.save(filepath, waveform, sample_rate) >>> wav_data_read, sr = paddle.audio.load(filepath) """ if hasattr(filepath, 'read'): file_obj = filepath else: file_obj = open(filepath, 'rb') try: file_ = wave.open(file_obj) except wave.Error: file_obj.seek(0) file_obj.close() err_msg = _error_message() raise NotImplementedError(err_msg) channels = file_.getnchannels() sample_rate = file_.getframerate() frames = file_.getnframes() # audio frame audio_content = file_.readframes(frames) file_obj.close() # default_subtype = "PCM_16", only support PCM16 WAV audio_as_np16 = np.frombuffer(audio_content, dtype=np.int16) audio_as_np32 = audio_as_np16.astype(np.float32) if normalize: # dtype = "float32" audio_norm = audio_as_np32 / (2**15) else: # dtype = "int16" audio_norm = audio_as_np32 waveform = np.reshape(audio_norm, (frames, channels)) if num_frames != -1: waveform = waveform[frame_offset : frame_offset + num_frames, :] waveform = paddle.to_tensor(waveform) if channels_first: waveform = paddle.transpose(waveform, perm=[1, 0]) return waveform, sample_rate def save( filepath: str, src: Tensor, sample_rate: int, channels_first: bool = True, encoding: str | None = None, bits_per_sample: int | None = 16, ) -> None: """ Save audio tensor to file. Args: filepath: saved path src: the audio tensor sample_rate: the number of samples of audio per second. channels_first: src channel information if True, means input tensor is (channels, time) if False, means input tensor is (time, channels) encoding: audio encoding format, wave_backend only support PCM16 now. bits_per_sample: bits per sample, wave_backend only support 16 bits now. Returns: None Examples: .. code-block:: python >>> import paddle >>> sample_rate = 16000 >>> wav_duration = 0.5 >>> num_channels = 1 >>> num_frames = sample_rate * wav_duration >>> wav_data = paddle.linspace(-1.0, 1.0, int(num_frames)) * 0.1 >>> waveform = wav_data.tile([num_channels, 1]) >>> filepath = "./test.wav" >>> paddle.audio.save(filepath, waveform, sample_rate) """ assert src.ndim == 2, "Expected 2D tensor" audio_numpy = src.numpy() # change src shape to (time, channels) if channels_first: audio_numpy = np.transpose(audio_numpy) channels = audio_numpy.shape[1] # only support PCM16 if bits_per_sample not in (None, 16): raise ValueError("Invalid bits_per_sample, only support 16 bit") sample_width = int(bits_per_sample / 8) # 2 if src.dtype == paddle.float32: audio_numpy = (audio_numpy * (2**15)).astype("