Files
FastDeploy/fastdeploy/input/multimodal/audio.py
2025-07-19 23:19:27 +08:00

128 lines
4.4 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

"""
# Copyright (c) 2025 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.
"""
import base64
from io import BytesIO
from pathlib import Path
import numpy as np
import numpy.typing as npt
from .base import MediaIO
# TODO 多模数据处理
# try:
# import librosa
# except ImportError:
# librosa = PlaceholderModule("librosa") # type: ignore[assignment]
# try:
# import soundfile
# except ImportError:
# soundfile = PlaceholderModule("soundfile") # type: ignore[assignment]
def resample_audio(
audio: npt.NDArray[np.floating],
*,
orig_sr: float,
target_sr: float,
) -> npt.NDArray[np.floating]:
"""
将音频数据从原始采样率(`orig_sr`)重采样到目标采样率(`target_sr`)。
Args:
audio (npt.NDArray[np.floating]): 带有单通道浮点型音频数据的 numpy ndarray形状为 `(samples,)`。
orig_sr (float): 音频数据的原始采样率。
target_sr (float): 需要转换到的目标采样率。
Returns:
npt.NDArray[np.floating]: 带有单通道浮点型音频数据的 numpy ndarray形状为 `(samples,)`,已经被重采样到目标采样率。
Raises:
None.
"""
import librosa
return librosa.resample(audio, orig_sr=orig_sr, target_sr=target_sr)
class AudioMediaIO(MediaIO[tuple[npt.NDArray, float]]):
def load_bytes(self, data: bytes) -> tuple[npt.NDArray, float]:
"""
加载字节数据,返回音频信号和采样率。
参数:
data (bytes) - 字节数据,包含音频文件的内容。
返回值tuple
(array, float) - 第一个元素是一个numpy数组表示音频信号第二个元素是一个浮点数表示采样率。
如果解码失败,则返回 None。
"""
import librosa
return librosa.load(BytesIO(data), sr=None)
def load_base64(
self,
media_type: str,
data: str,
) -> tuple[npt.NDArray, float]:
"""
将 base64 编码的字符串转换为 numpy 数组和尺度。
Args:
media_type (str): 媒体类型,例如 'image/jpeg''image/png' 等。
data (str): base64 编码的字符串,表示图像或其他二进制数据。
Returns:
tuple[npt.NDArray, float]: 包含以下两个元素:
- npt.NDArray: 形状为HWC的 numpy 数组,表示图像或其他二进制数据。
- float: 图像的尺度,单位为像素。
Raises:
ValueError: 当 media_type 不是有效的媒体类型时引发。
"""
return self.load_bytes(base64.b64decode(data))
def load_file(self, filepath: Path) -> tuple[npt.NDArray, float]:
"""
加载音频文件,返回音频数据和采样率。
参数:
filepath (Path): 音频文件路径Path类型
返回值:
tuple[npt.NDArray, float]包含两个元素的元组第一个是音频数据npt.NDArray类型
第二个是采样率float类型
"""
import librosa
return librosa.load(filepath, sr=None)
def encode_base64(self, media: tuple[npt.NDArray, float]) -> str:
"""
将音频数据和采样率转换为Base64编码的字符串。
参数:
media (tuple[numpy.ndarray, float]): 包含音频数据和采样率的元组其中音频数据是一个numpy数组采样率是一个浮点数。
返回值 (str): Base64编码的字符串表示音频数据和采样率。
"""
audio, sr = media
with BytesIO() as buffer:
import soundfile
soundfile.write(buffer, audio, sr, format="WAV")
data = buffer.getvalue()
return base64.b64encode(data).decode("utf-8")