🎮 Movie-to-Music Recommendation System 🎵

A Python-based web application that recommends music tracks based on the genres of movies entered by the user. This project uses Streamlit for the frontend, Pyngrok for exposing the app to the internet, and leverages movie and music datasets for genre-based recommendations.

Repository Under: AcWoC'25

Club: Android Club, VIT Bhopal University

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📚 Features

• Movie Genre Recognition: Detects genres of a given movie.
• Music Genre Mapping: Matches movie genres to related music genres.
• Music Recommendations: Recommends tracks based on movie genres.
• User-Friendly Interface: Interactive web app for easy usage.
• Link With Spotify: For Song link is given by Spotify
• Info. of Song: Model also give album,image,Link.

🚀 Getting Started

Prerequisites

• Python 3.x
• Required Libraries:
  • streamlit
  • pyngrok

Datasets

1. Movies Dataset: tmdb_5000_movies.csv
   Contains movie information, including genres and titles.

2. Music Dataset: extended_data_by_genres.csv
   Contains music genres and associated track names.

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🔧 How to Run

1. Clone the Repository:

   git clone https://github.com/YourUsername/MovieMusicRecommender.git
   cd MovieMusicRecommender
   

2. Run the Script:

   • Run all the Code Cells given in MovMusic.ipynb one by one.
   • Replace YOUR_AUTH_TOKEN in the last cell with your Ngrok Auth Token.
   • Run the last cell

3. Access the Application:

   • The app will be hosted locally, but the Pyngrok integration will provide a public URL.
   • Open the provided URL to access the app in your browser.

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🖥️ Application Workflow

1. Input:

   • Enter the movie dataset path, music dataset path, and a movie title in the Streamlit web app.

2. Processing:

   • The app identifies the movie's genres.
   • Maps the genres to related music genres using a predefined mapping.
   • Searches the music dataset for matching tracks.

3. Output:

   • Displays a list of recommended music tracks for the movie's genres.

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🧬 Key Components

GenreRecommendationSystem

A Python class that handles:

• Loading and preprocessing movie and music datasets.
• Mapping movie genres to related music genres.
• Generating music recommendations.
• Spotify link to listen the song

Streamlit Interface

• Provides a user-friendly UI for entering inputs and displaying results.

Pyngrok Integration

• Exposes the local Streamlit server to the internet, making it accessible from anywhere.

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🗃️ Example Usage

• Input:
  Movie Title: Inception

• Output:
  Recommended Tracks:

  1. Genre: Electronic - Track: Dreamscape Beats
  2. Genre: Ambient - Track: Space Journey
  3. Genre: Cinematic - Track: Epic Movie Score

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🤝 Contributing

Contributions are welcome! To contribute:

1. Fork the repository.
2. Create a feature branch (git checkout -b feature-name).
3. Commit your changes (git commit -m 'Add feature').
4. Push to the branch (git push origin feature-name).
5. Create a Pull Request.

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🙏 Acknowledgments

• Datasets:
  • TMDB Movies Dataset
  • Custom Music Dataset
• Libraries:
  • Streamlit
  • Pyngrok
  • Pandas