fumiama/Retrieval-based-Voice-Conversion-WebUI
1
0
Fork 0
mirror of https://github.com/fumiama/Retrieval-based-Voice-Conversion-WebUI.git synced 2026-06-05 17:20:25 +08:00
Code Activity

refactor(audio): store all of the audio related functions in the infer.lib.audio

Browse Source 
refactors previous commit to have singular functions for each task, all located in `infer.lib.audio`
This commit is contained in:
Alex Murkoff
2024-06-11 12:24:03 +07:00
parent 15cf2e067e
commit 6425f2091e
4 changed files with 74 additions and 74 deletions
Download Patch File Download Diff File Expand all files Collapse all files

62
infer/lib/audio.py
View File

@@ -3,6 +3,7 @@ from pathlib import Path
from typing import Dict
import numpy as np
import av
import os
from av.audio.resampler import AudioResampler
video_format_dict: Dict[str, str] = {
@@ -54,6 +55,67 @@ def load_audio(file: str, sr: int) -> np.ndarray:
return audio.flatten()
def downsample_audio(input_path: str, output_path: str, format: str) -> None:
if not os.path.exists(input_path): return
input_container = av.open(input_path)
output_container = av.open(output_path, 'w')
# Create a stream in the output container
input_stream = input_container.streams.audio[0]
output_stream = output_container.add_stream(format)
output_stream.bit_rate = 128_000 # 128kb/s (equivalent to -q:a 2)
# Copy packets from the input file to the output file
for packet in input_container.demux(input_stream):
for frame in packet.decode():
for out_packet in output_stream.encode(frame):
output_container.mux(out_packet)
for packet in output_stream.encode():
output_container.mux(packet)
# Close the containers
input_container.close()
output_container.close()
try: # Remove the original file
os.remove(input_path)
except Exception as e:
print(f"Failed to remove the original file: {e}")
def resample_audio(input_path: str, output_path: str, format: str, sr: int, layout: str) -> None:
if not os.path.exists(input_path): return
input_container = av.open(input_path)
output_container = av.open(output_path, 'w')
# Create a stream in the output container
input_stream = input_container.streams.audio[0]
output_stream = output_container.add_stream(format, rate=sr, layout=layout)
resampler = AudioResampler(format, layout, sr)
# Copy packets from the input file to the output file
for packet in input_container.demux(input_stream):
for frame in packet.decode():
frame.pts = None # Clear presentation timestamp to avoid resampling issues
resampled = resampler.resample(frame)
for out_packet in output_stream.encode(resampled):
output_container.mux(out_packet)
for packet in output_stream.encode():
output_container.mux(packet)
# Close the containers
input_container.close()
output_container.close()
try: # Remove the original file
os.remove(input_path)
except Exception as e:
print(f"Failed to remove the original file: {e}")
def clean_path(path: str) -> Path:
return Path(path.strip(' "\n')).resolve()

8
infer/modules/uvr5/mdxnet.py
View File

@@ -10,6 +10,8 @@ import torch
from tqdm import tqdm
import av
from infer.lib.audio import downsample_audio
cpu = torch.device("cpu")
@@ -219,10 +221,10 @@ class Predictor:
sf.write(path_other, opt, rate)
opt_path_vocal = path_vocal[:-4] + ".%s" % format
opt_path_other = path_other[:-4] + ".%s" % format
process_audio(path_vocal, opt_path_vocal, format)
process_audio(path_other, opt_path_other, format)
downsample_audio(path_vocal, opt_path_vocal, format)
downsample_audio(path_other, opt_path_other, format)
def process_audio(input_path: str, output_path: str, format: str) -> None:
def downsample_audio(input_path: str, output_path: str, format: str) -> None:
if not os.path.exists(input_path): return
input_container = av.open(input_path)

38
infer/modules/uvr5/modules.py
View File

@@ -5,7 +5,7 @@ import logging
logger = logging.getLogger(__name__)
import av
from av.audio.resampler import AudioResampler
from infer.lib.audio import resample_audio
import torch
from configs import Config
@@ -63,7 +63,7 @@ def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins, agg, format
os.path.join(os.environ["TEMP"]),
os.path.basename(inp_path),
)
process_audio(inp_path, tmp_path)
resample_audio(inp_path, tmp_path, 'pcm_s16le', 44100, 'stereo')
inp_path = tmp_path
try:
if done == 0:
@@ -105,37 +105,3 @@ def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins, agg, format
torch.mps.empty_cache()
logger.info("Executed torch.mps.empty_cache()")
yield "\n".join(infos)
def process_audio(input_path: str, output_path: str) -> None:
if not os.path.exists(input_path): return
input_container = av.open(input_path)
output_container = av.open(output_path, 'w')
# Create a stream in the output container
input_stream = input_container.streams.audio[0]
output_stream = output_container.add_stream('pcm_s16le', rate=44100, layout='stereo')
resampler = AudioResampler('pcm_s16le', 'stereo', 44100)
output_stream.bit_rate = 128_000 # 128kb/s (equivalent to -q:a 2)
# Copy packets from the input file to the output file
for packet in input_container.demux(input_stream):
for frame in packet.decode():
frame.pts = None # Clear presentation timestamp to avoid resampling issues
resampled = resampler.resample(frame)
for out_packet in output_stream.encode(resampled):
output_container.mux(out_packet)
for packet in output_stream.encode():
output_container.mux(packet)
# Close the containers
input_container.close()
output_container.close()
try: # Remove the original file
os.remove(input_path)
except Exception as e:
print(f"Failed to remove the original file: {e}")

40
infer/modules/uvr5/vr.py
View File

@@ -6,7 +6,7 @@ logger = logging.getLogger(__name__)
import librosa
import numpy as np
import soundfile as sf
import av
from infer.lib.audio import downsample_audio
import torch
from infer.lib.uvr5_pack.lib_v5 import nets_123821KB as Nets
@@ -147,7 +147,7 @@ class AudioPre:
)
if os.path.exists(path):
opt_format_path = path[:-4] + ".%s" % format
process_audio(path, opt_format_path, format)
downsample_audio(path, opt_format_path, format)
if vocal_root is not None:
if is_hp3 == True:
head = "instrument_"
@@ -182,37 +182,7 @@ class AudioPre:
self.mp.param["sr"],
)
opt_format_path = path[:-4] + ".%s" % format
process_audio(path, opt_format_path, format)
def process_audio(input_path: str, output_path: str, format: str) -> None:
if not os.path.exists(input_path): return
input_container = av.open(input_path)
output_container = av.open(output_path, 'w')
# Create a stream in the output container
input_stream = input_container.streams.audio[0]
output_stream = output_container.add_stream(format)
output_stream.bit_rate = 128_000 # 128kb/s (equivalent to -q:a 2)
# Copy packets from the input file to the output file
for packet in input_container.demux(input_stream):
for frame in packet.decode():
for out_packet in output_stream.encode(frame):
output_container.mux(out_packet)
for packet in output_stream.encode():
output_container.mux(packet)
# Close the containers
input_container.close()
output_container.close()
try: # Remove the original file
os.remove(input_path)
except Exception as e:
print(f"Failed to remove the original file: {e}")
downsample_audio(path, opt_format_path, format)
class AudioPreDeEcho:
def __init__(self, agg, model_path, device, is_half, tta=False):
@@ -342,7 +312,7 @@ class AudioPreDeEcho:
)
if os.path.exists(path):
opt_format_path = path[:-4] + ".%s" % format
process_audio(path, opt_format_path, format)
downsample_audio(path, opt_format_path, format)
if vocal_root is not None:
if self.data["high_end_process"].startswith("mirroring"):
input_high_end_ = spec_utils.mirroring(
@@ -374,4 +344,4 @@ class AudioPreDeEcho:
)
if os.path.exists(path):
opt_format_path = path[:-4] + ".%s" % format
process_audio(path, opt_format_path, format)
downsample_audio(path, opt_format_path, format)