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VideoClipper

An AI-powered video highlight generator that automatically extracts the most interesting segments from videos.

Features

  • Automated video highlight generation
  • Scene detection and analysis
  • Audio energy analysis for exciting moment detection
  • Speech transcription with OpenAI's Whisper model
  • Intelligent clip selection and assembly
  • YouTube video support (download and process)
  • Animated captions with speech synchronization and keyword highlighting

Installation

Prerequisites

  • Python 3.8 or higher
  • FFmpeg (required for video processing)

Setup

  1. Clone the repository:
git clone https://github.com/bugkill3r/video-clipper.git
cd video-clipper
  1. Install dependencies:

Or for development:

Usage

Command Line Interface

Processing Local Videos

Basic usage:

videoclipper process path/to/video.mp4 --output-dir highlights/

With advanced options:

videoclipper process path/to/video.mp4 \
  --output-dir highlights/ \
  --duration 60 \
  --transcribe \
  --whisper-model base \
  --min-segment 3 \
  --max-segment 15 \
  --num-clips 5 \
  --captions \
  --highlight-words "important,keywords,to,highlight"

Processing YouTube Videos

You can directly process YouTube videos by providing a URL:

videoclipper process https://www.youtube.com/watch?v=dQw4w9WgXcQ

With options:

videoclipper process https://www.youtube.com/watch?v=dQw4w9WgXcQ \
  --output-dir custom_highlights/ \
  --num-clips 3 \
  --duration 45 \
  --captions

Python API

from videoclipper import VideoProcessor

# Initialize the processor
processor = VideoProcessor("path/to/video.mp4")

# Run analysis
processor.analyze(transcribe=True, detect_scenes=True)

# Generate highlight clip
processor.create_highlight("output.mp4", max_duration=60, add_captions=True, highlight_keywords=["important", "words"])

Development

Setting up a development environment

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install development dependencies
pip install -e ".[dev]"

# Install pre-commit hooks
pre-commit install

Running tests

Or with coverage:

pytest --cov=videoclipper

License

MIT

Caption Feature

The video clipper now supports animated captions that synchronize with speech timing:

  • Captions are disabled by default and can be enabled with the --captions flag
  • Captions appear in short phrases (4-6 words) timed to match when words are spoken
  • Keywords are automatically identified and highlighted in alternating yellow/green
  • You can specify your own highlight words with the --highlight-words option
  • The style matches viral social media videos with a dark background and highlighted words
  • Word-by-word highlighting makes important terms stand out for viewers

Example usage:

videoclipper process video.mp4 --captions --highlight-words "important,keywords,to,highlight"

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.