MoodifyAI

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An AI-powered music recommendation system that detects emotions from facial expressions and suggests songs tailored to the user's mood.

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Features

• Detects emotions from facial expressions using a pre-trained deep learning model.
• Recommends songs based on the detected emotion by integrating with Spotify.
• Provides a user-friendly web interface for interaction.

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Technologies Used

• Backend: Python, Flask, TensorFlow/Keras
• Frontend: HTML, CSS, JavaScript
• Spotify Integration: Spotify Web API
• Model: Pre-trained emotion detection model (facial_EmotionClassifer.h5)

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How It Works

1. Emotion Detection:
   The system uses a deep learning model to analyze facial expressions and classify them into emotions such as happy, sad, angry, neutral, etc.

2. Spotify API Integration:
   Based on the detected emotion, the app queries Spotify's API for songs that match the mood and displays the results.

3. User Interface:
   Users interact with the system via a web interface where they can capture or upload images to detect emotions and get music recommendations.

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Getting Started

Prerequisites

• Python 3.x
• Spotify Developer Account
• Flask (pip install flask)
• TensorFlow/Keras
• Other dependencies listed in requirements.txt.

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Steps to Set Up the Project

1. Clone the Repository

git clone https://github.com/shivamprasad1001/MoodifyAI.git
cd MoodifyAI

2. Install Dependencies

pip install -r requirements.txt

3. Get Spotify API Credentials

• Visit Spotify Developer Dashboard.
• Log in or create an account.
• Create a new application and note down the Client ID and Client Secret.
• Add a redirect URI for authentication (e.g., http://localhost:5000/callback).

4. Set Up Environment Variables

Create a .env file in the root directory and add:

SPOTIFY_CLIENT_ID=your_client_id_here
SPOTIFY_CLIENT_SECRET=your_client_secret_here
SPOTIFY_REDIRECT_URI=http://localhost:5000/callback

5. Run the Application

python app.py

Open your browser and go to http://localhost:5000.

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How to Use the Spotify API

Query Songs Based on Emotion

The app uses the Spotify Web API to fetch songs:

import spotipy
from spotipy.oauth2 import SpotifyClientCredentials

# Authenticate with Spotify
sp = spotipy.Spotify(auth_manager=SpotifyClientCredentials(
    client_id="your_client_id",
    client_secret="your_client_secret"
))

# Fetch songs based on genre or mood
results = sp.search(q="genre:pop", type="track", limit=10)
for track in results['tracks']['items']:
    print(f"{track['name']} by {track['artists'][0]['name']}")

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Contributing

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature/your-feature-name

3. Commit your changes:

   git commit -m "Add some feature"

4. Push to the branch:

   git push origin feature/your-feature-name

5. Open a pull request.

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License

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

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Acknowledgments

• Spotify API Documentation
• TensorFlow/Keras for the emotion detection model.

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