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import os
import sys
import traceback
import parselmouth
now_dir = os.getcwd()
sys.path.append(now_dir)
import logging
import numpy as np
import pyworld
from infer.lib.audio import load_audio
logging.getLogger("numba").setLevel(logging.WARNING)
from multiprocessing import Process
exp_dir = sys.argv[1]
f = open("%s/extract_f0_feature.log" % exp_dir, "a+")
def printt(strr):
print(strr)
f.write("%s\n" % strr)
f.flush()
n_p = int(sys.argv[2])
f0method = sys.argv[3]
class FeatureInput(object):
def __init__(self, samplerate=16000, hop_size=160):
self.fs = samplerate
self.hop = hop_size
self.f0_bin = 256
self.f0_max = 1100.0
self.f0_min = 50.0
self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
self.f0_mel_max = 1127 * np.log(1 + self.f0_max / 700)
def compute_f0(self, path, f0_method):
x = load_audio(path, self.fs)
p_len = x.shape[0] // self.hop
if f0_method == "pm":
time_step = 160 / 16000 * 1000
f0_min = 50
f0_max = 1100
f0 = (
parselmouth.Sound(x, self.fs)
.to_pitch_ac(
time_step=time_step / 1000,
voicing_threshold=0.6,
pitch_floor=f0_min,
pitch_ceiling=f0_max,
)
.selected_array["frequency"]
)
pad_size = (p_len - len(f0) + 1) // 2
if pad_size > 0 or p_len - len(f0) - pad_size > 0:
f0 = np.pad(
f0, [[pad_size, p_len - len(f0) - pad_size]], mode="constant"
)
elif f0_method == "harvest":
f0, t = pyworld.harvest(
x.astype(np.double),
fs=self.fs,
f0_ceil=self.f0_max,
f0_floor=self.f0_min,
frame_period=1000 * self.hop / self.fs,
)
f0 = pyworld.stonemask(x.astype(np.double), f0, t, self.fs)
elif f0_method == "dio":
f0, t = pyworld.dio(
x.astype(np.double),
fs=self.fs,
f0_ceil=self.f0_max,
f0_floor=self.f0_min,
frame_period=1000 * self.hop / self.fs,
)
f0 = pyworld.stonemask(x.astype(np.double), f0, t, self.fs)
elif f0_method == "rmvpe":
if hasattr(self, "model_rmvpe") == False:
from infer.lib.rmvpe import RMVPE
print("Loading rmvpe model")
self.model_rmvpe = RMVPE(
"assets/rmvpe/rmvpe.pt", is_half=False, device="cpu"
)
f0 = self.model_rmvpe.infer_from_audio(x, thred=0.03)
return f0
def coarse_f0(self, f0):
f0_mel = 1127 * np.log(1 + f0 / 700)
f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - self.f0_mel_min) * (
self.f0_bin - 2
) / (self.f0_mel_max - self.f0_mel_min) + 1
# use 0 or 1
f0_mel[f0_mel <= 1] = 1
f0_mel[f0_mel > self.f0_bin - 1] = self.f0_bin - 1
f0_coarse = np.rint(f0_mel).astype(int)
assert f0_coarse.max() <= 255 and f0_coarse.min() >= 1, (
f0_coarse.max(),
f0_coarse.min(),
)
return f0_coarse
def go(self, paths, f0_method):
if len(paths) == 0:
printt("no-f0-todo")
else:
printt("todo-f0-%s" % len(paths))
n = max(len(paths) // 5, 1) # 每个进程最多打印5条
for idx, (inp_path, opt_path1, opt_path2) in enumerate(paths):
try:
if idx % n == 0:
printt("f0ing,now-%s,all-%s,-%s" % (idx, len(paths), inp_path))
if (
os.path.exists(opt_path1 + ".npy") == True
and os.path.exists(opt_path2 + ".npy") == True
):
continue
featur_pit = self.compute_f0(inp_path, f0_method)
np.save(
opt_path2,
featur_pit,
allow_pickle=False,
) # nsf
coarse_pit = self.coarse_f0(featur_pit)
np.save(
opt_path1,
coarse_pit,
allow_pickle=False,
) # ori
except:
printt("f0fail-%s-%s-%s" % (idx, inp_path, traceback.format_exc()))
if __name__ == "__main__":
# exp_dir=r"E:\codes\py39\dataset\mi-test"
# n_p=16
# f = open("%s/log_extract_f0.log"%exp_dir, "w")
printt(sys.argv)
featureInput = FeatureInput()
paths = []
inp_root = "%s/1_16k_wavs" % (exp_dir)
opt_root1 = "%s/2a_f0" % (exp_dir)
opt_root2 = "%s/2b-f0nsf" % (exp_dir)
os.makedirs(opt_root1, exist_ok=True)
os.makedirs(opt_root2, exist_ok=True)
for name in sorted(list(os.listdir(inp_root))):
inp_path = "%s/%s" % (inp_root, name)
if "spec" in inp_path:
continue
opt_path1 = "%s/%s" % (opt_root1, name)
opt_path2 = "%s/%s" % (opt_root2, name)
paths.append([inp_path, opt_path1, opt_path2])
ps = []
for i in range(n_p):
p = Process(
target=featureInput.go,
args=(
paths[i::n_p],
f0method,
),
)
ps.append(p)
p.start()
for i in range(n_p):
ps[i].join()
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