|
import argparse |
|
import concurrent.futures |
|
import sys |
|
import warnings |
|
|
|
import numpy as np |
|
import torch |
|
from tqdm import tqdm |
|
|
|
import utils |
|
from config import config |
|
|
|
warnings.filterwarnings("ignore", category=UserWarning) |
|
from pyannote.audio import Inference, Model |
|
|
|
model = Model.from_pretrained("pyannote/wespeaker-voxceleb-resnet34-LM") |
|
inference = Inference(model, window="whole") |
|
device = torch.device(config.style_gen_config.device) |
|
inference.to(device) |
|
|
|
|
|
def extract_style_vector(wav_path): |
|
return inference(wav_path) |
|
|
|
|
|
def save_style_vector(wav_path): |
|
style_vec = extract_style_vector(wav_path) |
|
|
|
np.save(f"{wav_path}.npy", style_vec) |
|
|
|
|
|
if __name__ == "__main__": |
|
parser = argparse.ArgumentParser() |
|
parser.add_argument( |
|
"-c", "--config", type=str, default=config.style_gen_config.config_path |
|
) |
|
parser.add_argument( |
|
"--num_processes", type=int, default=config.style_gen_config.num_processes |
|
) |
|
args, _ = parser.parse_known_args() |
|
config_path = args.config |
|
num_processes = args.num_processes |
|
|
|
hps = utils.get_hparams_from_file(config_path) |
|
|
|
device = config.style_gen_config.device |
|
|
|
lines = [] |
|
with open(hps.data.training_files, encoding="utf-8") as f: |
|
lines.extend(f.readlines()) |
|
|
|
with open(hps.data.validation_files, encoding="utf-8") as f: |
|
lines.extend(f.readlines()) |
|
|
|
wavnames = [line.split("|")[0] for line in lines] |
|
|
|
with concurrent.futures.ThreadPoolExecutor(max_workers=num_processes) as executor: |
|
list( |
|
tqdm( |
|
executor.map(save_style_vector, wavnames), |
|
total=len(wavnames), |
|
file=sys.stdout, |
|
) |
|
) |
|
|
|
print(f"Finished generating style vectors! total: {len(wavnames)} npy files.") |
|
|
