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import os
import datasets
logger = datasets.logging.get_logger(__name__)
datasets.logging.set_verbosity(20)
class ParsiGoo(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
def _info(self):
features = datasets.Features(
{
"text": datasets.Value("string"),
"audio_file": datasets.Value("string"),
"speaker_name": datasets.Value("string"),
"root_path": datasets.Value("string")
}
)
return datasets.DatasetInfo(
description="ParsiGoo dataset",
features=features,
homepage="https://example.com",
citation="",
)
def _split_generators(self, dl_manager):
logger.info("| > ")
print("4544444")
print(dl_manager.manual_dir)
# logger.info(os.path.join(os.path.dirname(os.path.abspath(__file__)), "datasets"))
data_dir = dl_manager.download_and_extract("https://huggingface.co/datasets/Kamtera/ParsiGoo/resolve/main/datasets.zip")
# data_dir="datasets"
data_dir = os.path.join(data_dir, "datasets")
print("| > data_dir =",data_dir)
meta_files = []
speaker_names = os.listdir(data_dir)
root_path = ""
print("| > listdir =",os.listdir(data_dir))
for speaker_name in os.listdir(data_dir):
# if not os.path.isdir(os.path.join(data_dir, speaker_name)):
# continue
root_path = os.path.join(data_dir, speaker_name)
meta_files.append(os.path.join(root_path, "metadata.csv"))
return [datasets.SplitGenerator(
name="train",
gen_kwargs={
"txt_files": meta_files,
"speaker_names": speaker_names,
"root_path": root_path
}
)]
def _generate_examples(self, txt_files, speaker_names, root_path):
print(txt_files)
id=-1
for ind,txt_file in enumerate(txt_files):
with open(txt_file, "r", encoding="utf-8") as ttf:
for i, line in enumerate(ttf):
cols = line.split("|")
wav_file = cols[1].strip()
text = cols[0].strip()
wav_file = os.path.join(root_path, "wavs", wav_file)
id+=1
yield id, {"text": text, "audio_file": wav_file, "speaker_name": speaker_names[ind], "root_path": root_path}
|