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A10G
Starting
on
A10G
| # Copyright (c) 2023 Amphion. | |
| # | |
| # This source code is licensed under the MIT license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| import os | |
| import glob | |
| import librosa | |
| import json | |
| from utils.util import has_existed | |
| def main(output_path, dataset_path): | |
| print("-" * 10) | |
| print("Preparing training dataset for svcceval...") | |
| data_dir = os.path.join(dataset_path, "Data") | |
| save_dir = os.path.join(output_path, "svcceval") | |
| os.makedirs(save_dir, exist_ok=True) | |
| singer_dict_file = os.path.join(save_dir, "singers.json") | |
| utt2singer_file = os.path.join(save_dir, "utt2singer") | |
| utt2singer = open(utt2singer_file, "w") | |
| # Load utterances | |
| train = [] | |
| test = [] | |
| singers = [] | |
| for wav_file in glob.glob(os.path.join(data_dir, "*/*.wav")): | |
| singer, filename = wav_file.split("/")[-2:] | |
| uid = filename.split(".")[0] | |
| utt = { | |
| "Dataset": "svcceval", | |
| "Singer": singer, | |
| "Uid": "{}_{}".format(singer, uid), | |
| "Path": wav_file, | |
| } | |
| # Duration | |
| duration = librosa.get_duration(filename=wav_file) | |
| utt["Duration"] = duration | |
| test.append(utt) | |
| singers.append(singer) | |
| utt2singer.write("{}\t{}\n".format(utt["Uid"], utt["Singer"])) | |
| # Save singers.json | |
| unique_singers = list(set(singers)) | |
| unique_singers.sort() | |
| singer_lut = {name: i for i, name in enumerate(unique_singers)} | |
| with open(singer_dict_file, "w") as f: | |
| json.dump(singer_lut, f, indent=4, ensure_ascii=False) | |
| train_total_duration = sum([utt["Duration"] for utt in train]) | |
| test_total_duration = sum([utt["Duration"] for utt in test]) | |
| for dataset_type in ["train", "test"]: | |
| output_file = os.path.join(save_dir, "{}.json".format(dataset_type)) | |
| if has_existed(output_file): | |
| continue | |
| utterances = eval(dataset_type) | |
| utterances = sorted(utterances, key=lambda x: x["Uid"]) | |
| for i in range(len(utterances)): | |
| utterances[i]["index"] = i | |
| print("{}: Total size: {}\n".format(dataset_type, len(utterances))) | |
| # Save | |
| with open(output_file, "w") as f: | |
| json.dump(utterances, f, indent=4, ensure_ascii=False) | |
| print( | |
| "#Train hours= {}, #Test hours= {}".format( | |
| train_total_duration / 3600, test_total_duration / 3600 | |
| ) | |
| ) | |