🚀🎬 VividCut-AI

(Note: VividCut-AI is a powerful tool for automating video editing processes with AI)

⚡ Automating video editing and processing with AI ⚡

Follow the installation steps below for running VividCut-AI locally. Please read "installation-notes.md" for more details.

🛠️ Workflow

🎥 Showcase

Here's a demonstration of VividCut-AI's capabilities:

Before Processing

After Processing

These examples illustrate the transformation from a raw video segment to a fully processed clip, showcasing the power of VividCut-AI.

☕ Buy Me a Coffee

If you appreciate the work and would like to support future developments, consider buying me a coffee!

🛠️ How it works

VividCut-AI is a powerful framework for automating video editing processes. It simplifies tasks such as video clipping, content extraction, and face tracking.

• 🎞️ Automated editing framework: Streamlines the video editing process using AI-driven techniques.

• 📃 Content Extraction: Extracts relevant segments based on user queries using a Faiss index built with Alibaba-NLP/gte-large-en-v1.5 embeddings.

• 🗣️ Face Tracking and Cropping: Automatically tracks and crops faces in videos using YOLO models.

• 🔗 Video Clipping: Clips and processes video segments based on AI-identified content.

• 🌐🎥 Automation: Automates the video processing workflow, making it easier for content creators to produce high-quality videos.

🚀 Quick Start: Run VividCut-AI

To run VividCut-AI locally, follow these steps:

1. Clone the Repository:

   git clone https://github.com/Mbonea-Mjema/VividCut-AI.git
   cd VividCut-AI

2. Install the Dependencies:

   pip install -r requirements.txt
   sudo apt-get install ffmpeg

3. Run the CLI:

   python CLI.py

4. Don't forget to include your Groq API key in the CLI.py code to enable the AI functionalities.

Framework Overview

• 🎬 The AIEditor component processes video transcripts and identifies key segments.

• 🎥 The VideoProcessor component handles video clipping, face tracking, and cropping.

💡 VividCut-AI offers powerful tools for automating video editing, making it an essential tool for content creators.

Technologies Used

VividCut-AI utilizes the following technologies:

• Faiss: For fast and efficient similarity search.
• Moviepy: For video processing and editing.
• OpenAI: For AI-driven content extraction and processing.
• YOLO: For object detection and face tracking in video.

These technologies provide a robust framework for automating video editing processes.

💁 Contributing

As an open-source project, we welcome contributions, whether it's a new feature, improved infrastructure, or better documentation.