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import sys,os
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
import torch
import argparse
import numpy as np
from omegaconf import OmegaConf
from scipy.io.wavfile import write
from pitch import load_csv_pitch
from vits.models import SynthesizerInfer
from svc_inference import load_svc_model, svc_infer
def main(args):
if (args.ppg == None):
args.ppg = "svc_tmp.ppg.npy"
print(
f"Auto run : python whisper/inference.py -w {args.wave} -p {args.ppg}")
os.system(f"python whisper/inference.py -w {args.wave} -p {args.ppg}")
if (args.vec == None):
args.vec = "svc_tmp.vec.npy"
print(
f"Auto run : python hubert/inference.py -w {args.wave} -v {args.vec}")
os.system(f"python hubert/inference.py -w {args.wave} -v {args.vec}")
if (args.pit == None):
args.pit = "svc_tmp.pit.csv"
print(
f"Auto run : python pitch/inference.py -w {args.wave} -p {args.pit}")
os.system(f"python pitch/inference.py -w {args.wave} -p {args.pit}")
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
hp = OmegaConf.load(args.config)
model = SynthesizerInfer(
hp.data.filter_length // 2 + 1,
hp.data.segment_size // hp.data.hop_length,
hp)
load_svc_model(args.model, model)
model.eval()
model.to(device)
spk = np.load(args.spk)
spk = torch.FloatTensor(spk)
ppg = np.load(args.ppg)
ppg = np.repeat(ppg, 2, 0)
ppg = torch.FloatTensor(ppg)
vec = np.load(args.vec)
vec = np.repeat(vec, 2, 0)
vec = torch.FloatTensor(vec)
pit = load_csv_pitch(args.pit)
shift_l = args.shift_l
shift_r = args.shift_r
print(f"pitch shift: [{shift_l}, {shift_r}]")
for shift in range(shift_l, shift_r + 1):
print(shift)
tmp = np.array(pit)
tmp = tmp * (2 ** (shift / 12))
tmp = torch.FloatTensor(tmp)
out_audio = svc_infer(model, spk, tmp, ppg, vec, hp, device)
write(os.path.join("./_svc_out", f"svc_out_{shift}.wav"),
hp.data.sampling_rate, out_audio)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--config', type=str, required=True,
help="yaml file for config.")
parser.add_argument('--model', type=str, required=True,
help="path of model for evaluation")
parser.add_argument('--wave', type=str, required=True,
help="Path of raw audio.")
parser.add_argument('--spk', type=str, required=True,
help="Path of speaker.")
parser.add_argument('--ppg', type=str,
help="Path of content vector.")
parser.add_argument('--vec', type=str,
help="Path of hubert vector.")
parser.add_argument('--pit', type=str,
help="Path of pitch csv file.")
parser.add_argument('--shift_l', type=int, default=0,
help="Pitch shift key for [shift_l, shift_r]")
parser.add_argument('--shift_r', type=int, default=0,
help="Pitch shift key for [shift_l, shift_r]")
args = parser.parse_args()
assert args.shift_l >= -12
assert args.shift_r >= -12
assert args.shift_l <= 12
assert args.shift_r <= 12
assert args.shift_l <= args.shift_r
os.makedirs("./_svc_out", exist_ok=True)
main(args)
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