preprocess_flist_config.py

import os
import argparse
from tqdm import tqdm
from random import shuffle
import json


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("--train_list", type=str, default="./filelists/train.txt", help="path to train list")
    parser.add_argument("--val_list", type=str, default="./filelists/val.txt", help="path to val list")
    parser.add_argument("--test_list", type=str, default="./filelists/test.txt", help="path to test list")
    parser.add_argument("--source_dir", type=str, default="./dataset", help="path to source dir")
    args = parser.parse_args()
    
    train = []
    val = []
    test = []
    idx = 0
    spk_dict = {}
    spk_id = 0
    for speaker in tqdm([ii for ii in os.listdir(args.source_dir) if os.path.isdir(os.path.join(args.source_dir, ii))]):
        spk_dict[speaker] = spk_id
        spk_id += 1
        wavs = [os.path.join(args.source_dir, speaker, i) for i in os.listdir(os.path.join(args.source_dir, speaker))]
        wavs = [i for i in wavs if i.endswith("wav") and not i.endswith(".16k.wav")]
        shuffle(wavs)
        train += wavs[2:-10]
        val += wavs[:2]
        test += wavs[-10:]
    # n_speakers = len(spk_dict.keys())*2
    shuffle(train)
    shuffle(val)
    shuffle(test)
            
    print("Writing", args.train_list)
    with open(args.train_list, "w") as f:
        for fname in tqdm(train):
            wavpath = fname
            f.write(wavpath + "\n")
        
    print("Writing", args.val_list)
    with open(args.val_list, "w") as f:
        for fname in tqdm(val):
            wavpath = fname
            f.write(wavpath + "\n")
            
    print("Writing", args.test_list)
    with open(args.test_list, "w") as f:
        for fname in tqdm(test):
            wavpath = fname
            f.write(wavpath + "\n")

    # config_template["model"]["n_speakers"] = n_speakers
    # config_template["spk"] = spk_dict
    print("Writing dataset/speakers.json")
    with open("dataset/speakers.json", "w") as f:
        json.dump(spk_dict, f, indent=2)