Video Summarizer Tool

This repository contains a Video Summarizer Tool that processes video files to generate concise and meaningful summaries. The tool leverages state-of-the-art AI models like Hugging Face Whisper for audio transcription and Pegasus for text summarization, combined with a user-friendly web interface for seamless interaction.

Features

• Audio Transcription: Extracts speech from video files using Hugging Face Whisper.
• Text Summarization: Summarizes the transcribed content using the Pegasus model.
• Web Interface: Provides a simple and intuitive interface for video uploads and summary generation.
• Real-Time Processing: Quickly processes video files to generate summaries efficiently.

How It Works

1. Upload a Video: The user uploads a video file through the web interface.
2. Audio Extraction: The tool extracts audio from the video.
3. Transcription: Speech in the audio is transcribed into text using Whisper.
4. Summarization: The transcribed text is summarized using Pegasus to provide concise insights.
5. Summary Display: The generated summary is displayed to the user on the interface.

Requirements

• Python 3.8+
• Libraries:
  • transformers
  • torch
  • moviepy
  • flask
  • whisper

Setup Instructions

1. Clone the repository:

   git clone https://github.com/janakiram180/Video-summarizer-tool.git  
   cd Video-summarizer-tool  

2. Install dependencies:

   pip install -r requirements.txt  

3. Run the application:

   python app.py  

4. Open the web interface in your browser:

   http://127.0.0.1:5000  
   

Usage

• Upload a video file via the web interface.
• Wait for the tool to process the video and generate the summary.
• View or download the summary from the interface.

Technologies Used

• Hugging Face Whisper: For accurate speech-to-text transcription.
• Pegasus: For state-of-the-art text summarization.
• Flask: Backend framework for building the web interface.
• MoviePy: For video and audio processing.

Future Enhancements

• Add support for multiple languages.
• Integrate with cloud storage for larger video files.
• Optimize processing time for longer videos.
• Enhance summarization with user-selectable models.

License

This project is licensed under the MIT License. See the LICENSE file for more details.