Files
auto-caption/engine/utils/audioprcs.py
himeditator 01936d5f12 feat(renderer): 添加界面主题颜色功能,添加复制最新字幕选项(#13)
- 新增界面主题颜色功能,支持自定义主题颜色
- 使用 antd 滑块替代原生 input 元素
- 添加复制字幕记录功能,可选择复制最近的字幕记录
2025-08-18 16:03:46 +08:00

109 lines
3.7 KiB
Python

import samplerate
import numpy as np
import numpy.core.multiarray # do not remove
def merge_chunk_channels(chunk: bytes, channels: int) -> bytes:
"""
将当前多通道音频数据块转换为单通道音频数据块
Args:
chunk: 多通道音频数据块
channels: 通道数
Returns:
单通道音频数据块
"""
if channels == 1: return chunk
# (length * channels,)
chunk_np = np.frombuffer(chunk, dtype=np.int16)
# (length, channels)
chunk_np = chunk_np.reshape(-1, channels)
# (length,)
chunk_mono_f = np.mean(chunk_np.astype(np.float32), axis=1)
chunk_mono = np.round(chunk_mono_f).astype(np.int16)
return chunk_mono.tobytes()
def resample_chunk_mono(chunk: bytes, channels: int, orig_sr: int, target_sr: int, mode="sinc_best") -> bytes:
"""
将当前多通道音频数据块转换成单通道音频数据块,然后进行重采样
Args:
chunk: 多通道音频数据块
channels: 通道数
orig_sr: 原始采样率
target_sr: 目标采样率
mode: 重采样模式,可选:'sinc_best' | 'sinc_medium' | 'sinc_fastest' | 'zero_order_hold' | 'linear'
Return:
单通道音频数据块
"""
if channels == 1:
chunk_mono = np.frombuffer(chunk, dtype=np.int16)
chunk_mono = chunk_mono.astype(np.float32)
else:
# (length * channels,)
chunk_np = np.frombuffer(chunk, dtype=np.int16)
# (length, channels)
chunk_np = chunk_np.reshape(-1, channels)
# (length,)
chunk_mono = np.mean(chunk_np.astype(np.float32), axis=1)
ratio = target_sr / orig_sr
chunk_mono_r = samplerate.resample(chunk_mono, ratio, converter_type=mode)
chunk_mono_r = np.round(chunk_mono_r).astype(np.int16)
return chunk_mono_r.tobytes()
def resample_chunk_mono_np(chunk: bytes, channels: int, orig_sr: int, target_sr: int, mode="sinc_best", dtype=np.float32) -> np.ndarray:
"""
将当前多通道音频数据块转换成单通道音频数据块,然后进行重采样,返回 Numpy 数组
Args:
chunk: 多通道音频数据块
channels: 通道数
orig_sr: 原始采样率
target_sr: 目标采样率
mode: 重采样模式,可选:'sinc_best' | 'sinc_medium' | 'sinc_fastest' | 'zero_order_hold' | 'linear'
dtype: 返回 Numpy 数组的数据类型
Return:
单通道音频数据块
"""
if channels == 1:
chunk_mono = np.frombuffer(chunk, dtype=np.int16)
chunk_mono = chunk_mono.astype(np.float32)
else:
# (length * channels,)
chunk_np = np.frombuffer(chunk, dtype=np.int16)
# (length, channels)
chunk_np = chunk_np.reshape(-1, channels)
# (length,)
chunk_mono = np.mean(chunk_np.astype(np.float32), axis=1)
ratio = target_sr / orig_sr
chunk_mono_r = samplerate.resample(chunk_mono, ratio, converter_type=mode)
chunk_mono_r = chunk_mono_r.astype(dtype)
return chunk_mono_r
def resample_mono_chunk(chunk: bytes, orig_sr: int, target_sr: int, mode="sinc_best") -> bytes:
"""
将当前单通道音频块进行重采样
Args:
chunk: 单通道音频数据块
orig_sr: 原始采样率
target_sr: 目标采样率
mode: 重采样模式,可选:'sinc_best' | 'sinc_medium' | 'sinc_fastest' | 'zero_order_hold' | 'linear'
Return:
单通道音频数据块
"""
chunk_np = np.frombuffer(chunk, dtype=np.int16)
chunk_np = chunk_np.astype(np.float32)
ratio = target_sr / orig_sr
chunk_r = samplerate.resample(chunk_np, ratio, converter_type=mode)
chunk_r = np.round(chunk_r).astype(np.int16)
return chunk_r.tobytes()