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/48k", help="path to source dir") args = parser.parse_args() previous_config = json.load(open("configs/config.json", "rb")) train = [] val = [] test = [] idx = 0 spk_dict = previous_config["spk"] spk_id = max([i for i in spk_dict.values()]) + 1 for speaker in tqdm(os.listdir(args.source_dir)): if speaker not in spk_dict.keys(): 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")] shuffle(wavs) train += wavs[2:-10] val += wavs[:2] test += wavs[-10:] assert previous_config["model"]["n_speakers"] > len(spk_dict.keys()) 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") previous_config["spk"] = spk_dict print("Writing configs/config.json") with open("configs/config.json", "w") as f: json.dump(previous_config, f, indent=2)