Datasets:
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import os
import pandas as pd
# Read CSV
df = pd.read_csv('metadata.csv', sep=',')
# if directory audio does not exist, create it
if not os.path.exists('audio'):
os.makedirs('audio')
def youtube_timer_in_seconds(time_str):
"""Converts a youtube timestamp (M:S or H:M:S) to seconds."""
parts = str(time_str).split(':')
seconds = 0
try:
if len(parts) == 2: # M:S
seconds = int(parts[0]) * 60 + int(parts[1])
elif len(parts) == 3: # H:M:S
seconds = int(parts[0]) * 3600 + int(parts[1]) * 60 + int(parts[2])
else:
raise ValueError("Unsupported time format")
except ValueError:
raise ValueError(
f"Invalid time format for '{time_str}'. Expected M:S or H:M:S."
)
return seconds
# Download audio from YouTube using yt-dlp library
for index, row in df.iterrows():
yt_url = row["url"]
start_time = youtube_timer_in_seconds(row["start_time"])
end_time = youtube_timer_in_seconds(row["end_time"])
output_template = os.path.join(
'audio', "tmp_" + str(row["identifier"]) + ".wav"
)
output_final_template = str(row["file_name"])
cmd_ytb = f'yt-dlp "{yt_url}" --extract-audio --audio-format wav --output "{output_template}"'
print(cmd_ytb)
cmd_ffmpeg = f"ffmpeg -y -i {output_template} -ss {start_time} -to {end_time} -c copy {output_final_template}"
print(cmd_ffmpeg)
cmd_rm_tmp = f"rm {output_template}"
print(cmd_rm_tmp)
print("-"*25)
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