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Retrieval-based-Voice-Conve…/infer/modules/uvr5/modules.py
Alex Murkoff 76ba0e20ff feat(audio): use PyAV instead of ffmpeg
replaced usage of ffmpeg in favor of PyAV (`av`)
2024-06-11 12:08:37 +07:00

141 lines
5.1 KiB
Python

import os
import traceback
import logging
logger = logging.getLogger(__name__)
import av
from av.audio.resampler import AudioResampler
import torch
from configs import Config
from infer.modules.uvr5.mdxnet import MDXNetDereverb
from infer.modules.uvr5.vr import AudioPre, AudioPreDeEcho
config = Config()
def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins, agg, format0):
infos = []
try:
inp_root = inp_root.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
save_root_vocal = (
save_root_vocal.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
)
save_root_ins = (
save_root_ins.strip(" ").strip('"').strip("\n").strip('"').strip(" ")
)
if model_name == "onnx_dereverb_By_FoxJoy":
pre_fun = MDXNetDereverb(15, config.device)
else:
func = AudioPre if "DeEcho" not in model_name else AudioPreDeEcho
pre_fun = func(
agg=int(agg),
model_path=os.path.join(
os.getenv("weight_uvr5_root"), model_name + ".pth"
),
device=config.device,
is_half=config.is_half,
)
is_hp3 = "HP3" in model_name
if inp_root != "":
paths = [os.path.join(inp_root, name) for name in os.listdir(inp_root)]
else:
paths = [path.name for path in paths]
for path in paths:
inp_path = os.path.join(inp_root, path)
need_reformat = 1
done = 0
try:
container = av.open(inp_path)
audio_stream = next(s for s in container.streams if s.type == 'audio')
# Check the audio stream's properties
if audio_stream.channels == 2 and audio_stream.rate == 44100:
pre_fun._path_audio_(inp_path, save_root_ins, save_root_vocal, format0, is_hp3=is_hp3)
need_reformat = 0
done = 1
except Exception as e:
need_reformat = 1
print(f"Exception {e} occured. Will reformat")
if need_reformat == 1:
tmp_path = "%s/%s.reformatted.wav" % (
os.path.join(os.environ["TEMP"]),
os.path.basename(inp_path),
)
process_audio(inp_path, tmp_path)
inp_path = tmp_path
try:
if done == 0:
pre_fun._path_audio_(
inp_path, save_root_ins, save_root_vocal, format0
)
infos.append("%s->Success" % (os.path.basename(inp_path)))
yield "\n".join(infos)
except:
try:
if done == 0:
pre_fun._path_audio_(
inp_path, save_root_ins, save_root_vocal, format0
)
infos.append("%s->Success" % (os.path.basename(inp_path)))
yield "\n".join(infos)
except:
infos.append(
"%s->%s" % (os.path.basename(inp_path), traceback.format_exc())
)
yield "\n".join(infos)
except:
infos.append(traceback.format_exc())
yield "\n".join(infos)
finally:
try:
if model_name == "onnx_dereverb_By_FoxJoy":
del pre_fun.pred.model
del pre_fun.pred.model_
else:
del pre_fun.model
del pre_fun
except:
traceback.print_exc()
if torch.cuda.is_available():
torch.cuda.empty_cache()
logger.info("Executed torch.cuda.empty_cache()")
elif torch.backends.mps.is_available():
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}")