A streamlined Python wrapper for inference with RVC. Specifically designed for inference tasks.
pip install rvc_infer
from rvc_infer import download_online_model
output = download_online_model(
url,
dir_name
)
print(output)
from rvc_infer import infer_audio
result = infer_audio(
model_name,
audio_path,
f0_change=0,
f0_method="rmvpe+",
min_pitch="50",
max_pitch="1100",
crepe_hop_length=128,
index_rate=0.75,
filter_radius=3,
rms_mix_rate=0.25,
protect=0.33,
split_infer=False,
min_silence=500,
silence_threshold=-50,
seek_step=1,
keep_silence=100,
do_formant=False,
quefrency=0,
timbre=1,
f0_autotune=False,
audio_format="wav",
resample_sr=0,
hubert_model_path="hubert_base.pt",
rmvpe_model_path="rmvpe.pt",
fcpe_model_path="fcpe.pt"
)
the model_name It will automaticly search a folder containing the pth file and index file.