File size: 4,470 Bytes
d64f270
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
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)

exp_dir = sys.argv[1]
import torch_directml

device = torch_directml.device(torch_directml.default_device())
f = open("%s/extract_f0_feature.log" % exp_dir, "a+")


def printt(strr):
    print(strr)
    f.write("%s\n" % strr)
    f.flush()


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 == "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=device
                )
            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(" ".join(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])
    try:
        featureInput.go(paths, "rmvpe")
    except:
        printt("f0_all_fail-%s" % (traceback.format_exc()))
    # 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()