- name
- youtube-chapter-generator
- description
- >
- Triggers
- youtube chapters", "视频章节", "youtube分段".
- version
- 1.0.0
- tags
YouTube Chapter Generator
Auto-generate YouTube video chapters from subtitles. Parses VTT/SRT files, identifies topic transitions, and produces timestamped chapter markers.
Usage
# Download subtitles first
yt-dlp --write-sub --write-auto-sub \
--sub-lang "zh-Hans,zh,en" \
--convert-subs vtt \
--skip-download \
-o "/tmp/%(id)s" \
"https://www.youtube.com/watch?v=VIDEO_ID"
# Generate chapters from subtitle file
python3 generate_chapters.py "/tmp/VIDEO_ID.zh-Hans.vtt"Chapter Generation Logic
import re
def parse_vtt_timestamps(vtt_content):
"""Extract timestamps and text from VTT file"""
timestamps = []
for match in re.finditer(r'(\d{2}:\d{2}:\d{2})\.\d{3}\s*-->\s*\d{2}:\d{2}:\d{2}\.\d{3}', vtt_content):
timestamps.append(match.group(1))
return timestamps
def generate_chapters(vtt_file, min_gap_seconds=30):
"""Generate chapters from VTT subtitle file"""
with open(vtt_file) as f:
content = f.read()
timestamps = parse_vtt_timestamps(content)
if len(timestamps) < 2:
return []
# Find natural breaks (gaps > min_gap_seconds)
chapters = []
last_ts = timestamps[0]
for ts in timestamps[1:]:
gap = parse_ts(ts) - parse_ts(last_ts)
if gap >= min_gap_seconds:
chapters.append(last_ts)
last_ts = ts
chapters.append(timestamps[-1])
return chapters
def parse_ts(ts_str):
"""Parse HH:MM:SS to seconds"""
parts = ts_str.split(":")
return int(parts[0])*3600 + int(parts[1])*60 + int(parts[2])
# Output format: "00:00 Introduction\
00:45 Main Topic\
..."YouTube Chapter Requirements
- Minimum 3 chapters for YouTube to auto-display
- First chapter must start at 0:00
- Chapters must be at least 10 seconds apart
- Maximum 12 chapters recommended
Tags
youtube chapters video timestamps subtitles automation