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65 lines
2.1 KiB
Python
65 lines
2.1 KiB
Python
import resampy
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import numpy as np
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import numpy.core.multiarray # do not remove
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def merge_chunk_channels(chunk: bytes, channels: int) -> bytes:
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"""
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将当前多通道音频数据块转换为单通道音频数据块
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Args:
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chunk: 多通道音频数据块
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channels: 通道数
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Returns:
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单通道音频数据块
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"""
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if channels == 1: return chunk
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# (length * channels,)
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chunk_np = np.frombuffer(chunk, dtype=np.int16)
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# (length, channels)
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chunk_np = chunk_np.reshape(-1, channels)
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# (length,)
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chunk_mono_f = np.mean(chunk_np.astype(np.float32), axis=1)
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chunk_mono = np.round(chunk_mono_f).astype(np.int16)
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return chunk_mono.tobytes()
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def resample_chunk_mono(chunk: bytes, channels: int, orig_sr: int, target_sr: int) -> bytes:
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"""
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将当前多通道音频数据块转换成单通道音频数据块，并进行重采样
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Args:
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chunk: 多通道音频数据块
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channels: 通道数
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orig_sr: 原始采样率
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target_sr: 目标采样率
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Return:
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单通道音频数据块
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"""
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if channels == 1:
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chunk_mono = np.frombuffer(chunk, dtype=np.int16)
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chunk_mono = chunk_mono.astype(np.float32)
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else:
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# (length * channels,)
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chunk_np = np.frombuffer(chunk, dtype=np.int16)
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# (length, channels)
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chunk_np = chunk_np.reshape(-1, channels)
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# (length,)
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chunk_mono = np.mean(chunk_np.astype(np.float32), axis=1)
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if orig_sr == target_sr:
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return chunk_mono.astype(np.int16).tobytes()
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chunk_mono_r = resampy.resample(chunk_mono, orig_sr, target_sr)
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chunk_mono_r = np.round(chunk_mono_r).astype(np.int16)
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real_len = round(chunk_mono.shape[0] * target_sr / orig_sr)
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if(chunk_mono_r.shape[0] != real_len):
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print(chunk_mono_r.shape[0], real_len)
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if(chunk_mono_r.shape[0] > real_len):
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chunk_mono_r = chunk_mono_r[:real_len]
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else:
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while chunk_mono_r.shape[0] < real_len:
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chunk_mono_r = np.append(chunk_mono_r, chunk_mono_r[-1])
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return chunk_mono_r.tobytes()
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