🎵 EMOBEAT - Emotion-Driven Music App

An AI-powered music recommendation system that detects real-time emotions through facial recognition and provides personalized music recommendations based on your current mood.

🎬 Demo

Experience the full workflow: emotion detection → music discovery → playlist creation

🌟 Features

• Real-Time Emotion Detection: Uses webcam feed to analyze facial expressions and detect emotions using deep learning models
• Intelligent Music Recommendation: Suggests songs aligned with detected mood, pulling music data from YouTube
• Song Download & Playback: Download recommended songs and play them with built-in music player
• Professional Interface: Clean, intuitive Streamlit-based web application
• Multiple Emotion Support: Detects 7 emotions - happy, sad, angry, fear, disgust, neutral, surprise

🛠️ Technologies Used

• Python: Core programming language
• OpenCV: Real-time webcam input and facial recognition
• TensorFlow/Keras: Deep learning emotion detection model
• YouTube API & yt-dlp: Search, fetch, and download songs from YouTube
• Streamlit: Web application framework for user interface
• Google API Client: YouTube Data API integration

📋 Prerequisites

• Python 3.7+
• Webcam/Camera access
• Internet connection for YouTube API
• YouTube Data API key

🚀 Installation

1. Clone the repository

   git clone https://github.com/Saad-Shakeel/Emotion-Driven-Music-App.git
   cd Emotion-Driven-Music-App

2. Install dependencies

   pip install uv
   uv sync

3. Install FFmpeg

   • Download FFmpeg from: https://www.gyan.dev/ffmpeg/builds/ffmpeg-release-essentials.zip
   • Extract the zip file
   • Add the bin folder path to your system environment variables

4. Set up YouTube API

   • Get YouTube Data API key from Google Cloud Console
   • Create .env file in project root
   • Add your API key:

     YOUTUBE_API_KEY=your_api_key_here
     

5. Download emotion detection model

   • Ensure emotionDetection.json and emotionDetection.h5 files are in the project directory

🎯 Usage

1. Run the application

   streamlit run main.py

2. Follow the app workflow

   • Step 1: Click "Start Webcam" to activate emotion detection
   • Step 2: Position your face in front of camera
   • Step 3: Click "Detect Mood" when ready
   • Step 4: Select mood filter and music genre
   • Step 5: Browse and download recommended songs
   • Step 6: Enjoy your personalized playlist

🎵 Music Genres

• Pop
• Rock
• Hip-Hop/Rap
• Electronic
• Classical
• Bollywood
• Punjabi
• Sufi

⚙️ Configuration

Environment Variables

Create a .env file with:

YOUTUBE_API_KEY=your_youtube_api_key

Model Files

Ensure these files are present:

• emotionDetection.json - Model architecture
• emotionDetection.h5 - Trained weights

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