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import os |
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import argparse |
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from tqdm import tqdm |
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from random import shuffle |
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import json |
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if __name__ == "__main__": |
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parser = argparse.ArgumentParser() |
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parser.add_argument("--train_list", type=str, default="./filelists/train.txt", help="path to train list") |
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parser.add_argument("--val_list", type=str, default="./filelists/val.txt", help="path to val list") |
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parser.add_argument("--test_list", type=str, default="./filelists/test.txt", help="path to test list") |
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parser.add_argument("--source_dir", type=str, default="./dataset/32k", help="path to source dir") |
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args = parser.parse_args() |
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previous_config = json.load(open("configs/config.json", "rb")) |
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train = [] |
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val = [] |
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test = [] |
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idx = 0 |
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spk_dict = previous_config["spk"] |
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spk_id = max([i for i in spk_dict.values()]) + 1 |
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for speaker in tqdm(os.listdir(args.source_dir)): |
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if speaker not in spk_dict.keys(): |
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spk_dict[speaker] = spk_id |
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spk_id += 1 |
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wavs = [os.path.join(args.source_dir, speaker, i)for i in os.listdir(os.path.join(args.source_dir, speaker))] |
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wavs = [i for i in wavs if i.endswith("wav")] |
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shuffle(wavs) |
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train += wavs[2:-10] |
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val += wavs[:2] |
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test += wavs[-10:] |
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assert previous_config["model"]["n_speakers"] > len(spk_dict.keys()) |
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shuffle(train) |
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shuffle(val) |
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shuffle(test) |
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print("Writing", args.train_list) |
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with open(args.train_list, "w") as f: |
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for fname in tqdm(train): |
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wavpath = fname |
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f.write(wavpath + "\n") |
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print("Writing", args.val_list) |
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with open(args.val_list, "w") as f: |
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for fname in tqdm(val): |
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wavpath = fname |
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f.write(wavpath + "\n") |
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print("Writing", args.test_list) |
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with open(args.test_list, "w") as f: |
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for fname in tqdm(test): |
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wavpath = fname |
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f.write(wavpath + "\n") |
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previous_config["spk"] = spk_dict |
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print("Writing configs/config.json") |
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with open("configs/config.json", "w") as f: |
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json.dump(previous_config, f, indent=2) |
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