This project is an AI-powered music search and recommendation system developed for Calgary Hacks 2026. It leverages deep learning models to analyze and retrieve music tracks based on user queries.

• Music search using audio features
• Song recommendation system
• Deep learning model integration (CNN14)
• REST API for music retrieval
• Dockerized for easy deployment

• main.py: Entry point for running the application
• model.py: Implements image functionality
• music.py: Handles music data processing
• search.py: Implements search functionality
• songret.py: Song retrieval and recommendation logic
• requirements.txt: Python dependencies
• Dockerfile & docker-compose.yml: Containerization setup
• Cnn14_DecisionLevelMax_mAP=0.385.pth: Pre-trained model weights

1. Clone the repository
2. Install dependencies:

   pip install -r requirements.txt

3. Run the application:

   python main.py

4. (Optional) Run with Docker:

   docker-compose up --build

• Access the API endpoints as described in the code or documentation.
• Use the search and recommendation features to find music tracks.

• Python 3.8+
• See requirements.txt for Python packages
• Docker (optional, for containerized deployment)

• Sreerag
• Nik
• Mohammad
• Aarav
• Keegan