Video Content Summarizer for Social Media Optimization

Here is the updated GitHub description with the link placed at the top:

Access the Project:

1. Offline Access:
   To run the project locally, follow the setup instructions below.

2. Online Access:
   You can access the project online via the following link.

Demo Video

Here is the demo video:link.

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This repository implements a Video Content Summarizer that analyzes YouTube video content, extracts key insights, and generates optimized outputs for social media engagement. The system leverages AI-powered models to provide captions, hashtags, and tagging recommendations for increasing video virality and audience reach.

Features

• YouTube Transcript Extraction
  Extracts video transcripts using the YouTube Transcript API for further analysis.

• Video Summarization
  Generates a concise summary of video content, enabling quick comprehension of the core message.

• Caption Generator
  Creates engaging and personalized captions for social media platforms.

• Hashtag Recommendations
  Generates two types of hashtags:

  • Viral Hashtags: Optimized for audience engagement.
  • Field-Specific Tags: Suggestions of relevant famous personalities or influencers to tag based on video content.

• Streamlit User Interface
  Provides an easy-to-use interface for uploading video URLs and receiving outputs.

Workflow

1. Input Video URL
   Paste the YouTube video link into the application.

2. Transcript Extraction
   Automatically fetches the transcript of the video.

3. Content Processing
   Summarizes the transcript into clear insights.
   Generates suggested captions and optimized hashtags.

4. Tagging Recommendations
   Identifies famous personalities or relevant figures related to the video topic for tagging.

5. Output
   Summarized transcript.
   Suggested captions.
   Viral hashtags and famous people to tag.

Sample Outputs

• Caption:
  "Unlock your potential with AI-powered insights! 🚀 #ArtificialIntelligence #GrowthMindset"

• Viral Hashtags:
  #Trending #ViralVideo #AI #ContentCreator #Inspiration

• Famous Personalities to Tag:

  • In Tech: Elon Musk, Sundar Pichai, Satya Nadella
  • In Fitness: Chris Hemsworth, Michelle Lewin

Setup Instructions

To run the project locally:

1. Clone the Repository

   git clone https://github.com/<your-username>/video-content-summarizer.git  
   cd video-content-summarizer  

2. Install Dependencies
   Install required Python libraries:

   pip install -r requirements.txt  

3. Add API Keys
   Create a .env file and add the required keys:

   WATSONX_API_KEY=your_ibm_watsonx_api_key  
   PROJECT_ID=your_project_id  
   

4. Run the Application
   Start the Streamlit interface:

   streamlit run app.py  

5. Input the Video URL
   Paste the YouTube video link and let the system generate optimized outputs.

Project Structure

• app.py: Streamlit app for user interaction.
• transcript_extraction.py: Fetches YouTube video transcripts.
• summary_generation.py: Generates video summaries and key insights.
• hashtag_suggester.py: Generates viral hashtags and tagging recommendations.
• requirements.txt: Lists project dependencies.

Technologies Used

• Streamlit: Interactive User Interface.
• YouTube Transcript API: For extracting video transcripts.
• IBM Watsonx AI: To generate summaries, captions, and recommendations.
• Python Libraries: Pysbd, Pandas, and Requests for text processing.

Future Enhancements

• Integration with social media platforms for auto-posting.
• Support for other video platforms (e.g., Vimeo).
• Enhanced AI models for caption personalization.

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