import os, traceback, sys, parselmouth import librosa import pyworld from scipy.io import wavfile import numpy as np, logging 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, sr = librosa.load(path, self.fs) p_len = x.shape[0] // self.hop assert sr == self.fs if f0_method == "pm": time_step = 160 / 16000 * 1000 f0_min = 50 f0_max = 1100 f0 = ( parselmouth.Sound(x, sr) .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=sr, f0_ceil=self.f0_max, f0_floor=self.f0_min, frame_period=1000 * self.hop / sr, ) f0 = pyworld.stonemask(x.astype(np.double), f0, t, self.fs) elif f0_method == "dio": f0, t = pyworld.dio( x.astype(np.double), fs=sr, f0_ceil=self.f0_max, f0_floor=self.f0_min, frame_period=1000 * self.hop / sr, ) f0 = pyworld.stonemask(x.astype(np.double), f0, t, self.fs) 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(np.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, ), ) p.start() ps.append(p) for p in ps: p.join()