Clips AI

Clips AI: An Open-Source Python Library for Intelligent Video Clipping and Aspect Ratio Conversion

I. Background and Technology

II. Function Introduction

(I) Core AI Functions (Highlight)

1. Text-Based Intelligent Clipping
   • Speech-to-Text Transcription: Utilizes the WhisperX open-source library to transcribe video audio, supporting multilingual recognition (e.g., English, Chinese, Spanish), and generates timestamped 逐字文本 (word-by-word text).
   • Key Segment Extraction: Analyzes transcriptions via NLP algorithms to identify dialogue transitions, topic shifts, or emotional peaks, automatically generating clip lists. For example, it can segment interview videos by guest speeches or podcast episodes by topic chapters.
2. Intelligent Aspect Ratio Conversion
   • Speaker Tracking: Uses Pyannote’s speaker diarization technology to identify primary speakers’ positions in videos, dynamically adjusting frame cropping to keep subjects centered.
   • Multi-Aspect Ratio Adaptation: Converts 16:9 landscape videos to 9:16 portrait (for TikTok/Douyin), 1:1 square (for Instagram), etc., by automatically filling backgrounds or scaling frames to avoid content cropping.

(II) Other Practical Functions

1. Batch Processing Support: Enables bulk video import via Python scripts, suitable for content teams handling large 素材 (e.g., news editing, course production).
2. Custom Parameter Configuration: Allows users to set minimum clip duration, keyword filtering rules, frame reframing sensitivity, etc., to meet personalized needs.

III. Usage Methods

(I) Development Environment Deployment (Desktop-Only)

1. System Requirements:
   • OS: Windows/macOS/Linux
   • Dependencies: Python 3.8+, FFmpeg (for video processing), libmagic (for file type detection)
2. Installation Steps:
   bash

   # Install Clips AI core library  
   pip install clipsai  
   # Install WhisperX dependencies (including speaker recognition)  
   pip install whisperx@git+https://github.com/m-bain/whisperx.git  
   # Install Pyannote (aspect ratio conversion requires Hugging Face Token)  
   pip install pyannote.audio  

3. Basic Code Example:
   from clipsai import ClipFinder, Transcriber, resize  
   
   # 1. Video transcription  
   transcriber = Transcriber()  
   transcription = transcriber.transcribe("input_video.mp4")  
   
   # 2. Extract clips  
   clipfinder = ClipFinder()  
   clips = clipfinder.find_clips(transcription, keywords=["technology", "case study"])  # Filter clips by keywords  
   
   # 3. Convert to 9:16 portrait video  
   resize(  
       "input_video.mp4",  
       pyannote_auth_token="your_huggingface_token",  
       aspect_ratio=(9, 16),  
       output_path="output_clips/"  
   )  

(II) Non-Programmer Users (No GUI Yet)

IV. Product Advantages

1. Open-Source, Free, and Flexible: As open-source software, it allows code modification for special scenarios without licensing fees, ideal for startups and tech enthusiasts.
2. Content-Aware Precision: Its semantic analysis-based clipping logic avoids the mechanical nature of traditional rule-based editing, preserving core information and narrative flow.
3. Efficient Multi-Platform Adaptation: Its dynamic frame reframing technology outperforms traditional stretching/cropping, keeping subjects clear and adapting to social media algorithms.

V. Use Cases

1. Social Media Operations
   • Scenario: Convert landscape interview videos to portrait clips by topic (e.g., “guest quotes”, “controversial opinions”) for mobile-friendly distribution.
   • Case: A YouTube blogger used Clips AI to auto-split a 1-hour video into 10×1-minute highlights, increasing TikTok views by 300%.
2. Online Education Content
   • Scenario: Clip course recordings by 知识点 (key concepts), such as “formula derivations” or “experiment demos”, and convert to portrait for mobile learning.
   • Case: An edtech platform processed 500 hours of courses with Clips AI, improving editing efficiency by 90% and course completion rates by 15%.
3. News and Short Video Production
   • Scenario: Rapidly extract key speeches from meeting recordings or press conferences for multi-platform distribution.

VI. Summary