WIP: eliminate ffmpeg

This commit is contained in:
wataru 2023-04-06 02:49:16 +09:00
parent 1fd0422b43
commit 689d3a4cdc

View File

@ -1,5 +1,6 @@
import sys
import os
import resampy
# avoiding parse arg error in RVC
sys.argv = ["MMVCServerSIO.py"]
@ -191,19 +192,6 @@ class RVC:
vol = max(rms, self.prevVol * 0.0)
self.prevVol = vol
import wave
filename = "testc2.wav"
if os.path.exists(filename):
print("[IORecorder] delete old analyze file.", filename)
os.remove(filename)
fo = wave.open(filename, 'wb')
fo.setnchannels(1)
fo.setsampwidth(2)
# fo.setframerate(24000)
fo.setframerate(self.tgt_sr)
fo.writeframes((self.audio_buffer * 32768.0).astype(np.int16))
fo.close()
return (self.audio_buffer, convertSize, vol)
def _onnx_inference(self, data):
@ -223,8 +211,7 @@ class RVC:
convertSize = data[1]
vol = data[2]
filename = "testc2.wav"
audio = load_audio(filename, 16000)
audio = resampy.resample(audio, self.tgt_sr, 16000)
if vol < self.settings.silentThreshold:
return np.zeros(convertSize).astype(np.int16)
@ -234,7 +221,7 @@ class RVC:
vc = VC(self.tgt_sr, dev, is_half)
sid = 0
times = [0, 0, 0]
f0_up_key = 0
f0_up_key = 10
f0_method = "pm"
file_index = ""
file_big_npy = ""
@ -245,8 +232,7 @@ class RVC:
audio_out = vc.pipeline(self.hubert_model, self.net_g, sid, audio, times, f0_up_key, f0_method,
file_index, file_big_npy, index_rate, if_f0, f0_file=f0_file)
result = audio_out
from scipy.io import wavfile
wavfile.write("testaaaaa.wav", self.tgt_sr, result)
return result
def inference(self, data):
@ -262,19 +248,3 @@ class RVC:
import ffmpeg
def load_audio(file, sr):
try:
# https://github.com/openai/whisper/blob/main/whisper/audio.py#L26
# This launches a subprocess to decode audio while down-mixing and resampling as necessary.
# Requires the ffmpeg CLI and `ffmpeg-python` package to be installed.
out, _ = (
ffmpeg.input(file, threads=0)
.output("-", format="s16le", acodec="pcm_s16le", ac=1, ar=sr)
.run(cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True)
)
except Exception as e:
raise RuntimeError(f"Failed to load audio: {e}")
return np.frombuffer(out, np.int16).flatten().astype(np.float32) / 32768.0