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Muhammad Naufal Rizqullah edited this page Jun 26, 2026 · 5 revisions

🎬 OpenSource Clipping — Wiki

Welcome to the OpenSource Clipping wiki! This is the central hub for all documentation related to the project.

OpenSource Clipping is an open-source AI-powered content factory that transforms long-form videos into cinematic short-form highlights with hook teasers, karaoke subtitles, and auto-thumbnails.

📚 Table of Contents

# Page Description
1 Home You are here — project overview and navigation
2 Getting Started Installation, prerequisites, API keys setup
3 CLI Reference Full list of all command-line arguments
4 Face Tracking & Auto-Framing How AI face detection and camera tracking works
5 Podcast Modes Split-screen & camera-switch for multi-speaker content
6 Hook V2 & Segment Trimming Multi-hook intros and AI-driven clip trimming
7 Subtitles & Typography Karaoke subtitles, font styles, kinetic text
8 BGM & Audio Background music, ducking, and audio settings
9 Video Quality & Rendering Resolution, bitrate, sharpening, encoder tuning
10 Story Clip Mode Multi-source narrative assembly for campaigns
11 YouTube Auto-Upload Automated uploading with scheduling support
12 Google Colab Guide Running the pipeline on Google Colab (free GPU)
13 Troubleshooting & FAQ Common errors, fixes, and frequently asked questions
14 Contributing How to contribute, report issues, and support the project

✨ Key Features at a Glance

  • 🤖 AI Transcriber — Word-level transcription using Faster-Whisper (large-v3)
  • 🧠 AI Content Curator — Google Gemini analyzes context and picks the most viral moments
  • 🎯 Smart Auto-Framing — Face-tracking via MediaPipe / YOLOv8 with smooth pan and anti-jitter
  • 🎬 Cinematic Teaser Hook — 3-second hook with dark overlay and TV Glitch transition
  • 📝 Karaoke Subtitles — Word-by-word highlighted .ASS subtitles (Hormozi / Veed style)
  • 🎥 B-Roll Integration — Auto-fetches contextual stock footage from Pexels
  • 🎙️ Podcast Split-Screen — Auto speaker diarization with top-bottom split layout
  • 📤 Auto YouTube Upload — Upload with scheduling and full metadata support
  • 📐 5 Aspect Ratios — 9:16, 16:9, 1:1, 3:4, 4:5

🔄 Pipeline Flow

Video URL → Download → Whisper Transcription → Gemini AI Analysis → Metadata QA → Render Loop
                                                                                      ↓
                                                            Face-Track Crop + B-Roll + BGM + Subtitles + Hook
                                                                                      ↓
                                                                              Final MP4 + Thumbnail

📊 Results

1 video 9:16 1 video split from YouTube Shorts link

(Standard 9:16 Auto-Framing)
(Split-Screen Podcast Mode)

🔗 Quick Links

🎬 OpenSource Clipping

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