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add backend inference and inferface output
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# 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 json
from tqdm import tqdm
import os
import librosa
from utils.util import has_existed
def get_lines(file):
with open(file, "r") as f:
lines = f.readlines()
lines = [l.strip() for l in lines]
return lines
def get_uid2utt(opencpop_path, dataset, dataset_type):
index_count = 0
total_duration = 0
file = os.path.join(opencpop_path, "segments", "{}.txt".format(dataset_type))
lines = get_lines(file)
uid2utt = []
for l in tqdm(lines):
items = l.split("|")
uid = items[0]
res = {
"Dataset": dataset,
"index": index_count,
"Singer": "female1",
"Uid": uid,
}
# Duration in wav files
audio_file = os.path.join(opencpop_path, "segments/wavs/{}.wav".format(uid))
res["Path"] = audio_file
duration = librosa.get_duration(filename=res["Path"])
res["Duration"] = duration
uid2utt.append(res)
index_count = index_count + 1
total_duration += duration
return uid2utt, total_duration / 3600
def main(dataset, output_path, dataset_path):
print("-" * 10)
print("Dataset splits for {}...\n".format(dataset))
save_dir = os.path.join(output_path, dataset)
opencpop_path = dataset_path
for dataset_type in ["train", "test"]:
output_file = os.path.join(save_dir, "{}.json".format(dataset_type))
if has_existed(output_file):
continue
res, hours = get_uid2utt(opencpop_path, dataset, dataset_type)
# Save
os.makedirs(save_dir, exist_ok=True)
with open(output_file, "w") as f:
json.dump(res, f, indent=4, ensure_ascii=False)
print("{}_{}_hours= {}".format(dataset, dataset_type, hours))