AutoEQ is an innovative application designed to enhance the listening experience across all audio sources on your computer. It provides a customizable 10-band graphic equalizer, includes genre-specific presets, integrates with Spotify to display the currently playing track, and enables automatic genre-based equalizer adjustments.

Full Application:

Here are some images showing the different genres available in the AutoEQ:

Hip-Hop	R&B
Hip-Hop	R&B

Pop	Rock
Pop	Rock

• 10-Band Equalizer: Adjust frequencies ranging from 60 Hz to 16,000 Hz.
• Custom Presets: Create, save, and load personalized EQ settings.
• Built-in Genre Presets: Includes presets for genres like Pop, Rock, Classical, and more.
• Real-Time Adjustment: Applies equalizer settings to system-wide audio with low latency.
• Flat Mode: Reset all bands to 0 dB using the "Flat" preset.

• "Now Playing" Display: Displays the currently playing track in real time.
• Automatic Updates: Updates every second to show the latest song from your Spotify account.
• Genre Detection: Detects the genre of the currently playing track and automatically adjusts the EQ based on pre-trained machine learning models.
• Genre Assignment: Assign specific genres to artists, allowing for management of "Unknown" genres and correction of mislabeled ones.

• Python 3.8 or higher
• Required Python packages:
  • PyQt5
  • pyaudio
  • scipy
  • spotipy
  • python-dotenv
  • scikit-learn

• Virtual Audio Cable:
  • Required to route audio for processing by the application.
  • Install and configure a virtual audio cable of your choice (e.g., VB-CABLE).

1. Clone the repository:

   git clone https://github.com/yourusername/adaptive-audio-equalizer.git
   cd adaptive-audio-equalizer

2. Install dependencies:

   pip install -r requirements.txt

3. Configure Spotify API:

   • Create a Spotify app at Spotify Developer Dashboard.
   • Note the Client ID, Client Secret, and Redirect URI.
   • Create a .env file in the main/ directory with the following content:

     SPOTIFY_CLIENT_ID=your_client_id
     SPOTIFY_CLIENT_SECRET=your_client_secret
     SPOTIFY_REDIRECT_URI=http://localhost:8888/callback

4. Set up virtual audio devices:

   • Run the application to list available audio devices.
   • Note the input and output device indices from the terminal output.
   • Update input_device_index and output_device_index in start_stream() in equalizer.py.

5. Run the application:

   python main.py

Here’s the structure of the AutoEQ project:

autoeq/
│
├── archive/                     # Archived/old files
│
├── images/                      # Folder for images
│   ├── full.png                 # Full application screenshot
│   ├── hiphop.png               # Hip-Hop genre image
│   ├── pop.png                  # Pop genre image
│   ├── rnb.png                  # R&B genre image
│   └── rock.png                 # Rock genre image
│
├── main/                        # Main application directory
│   ├── __pycache__/             # Python cache files
│   ├── build                    # Build files for PyInstaller
│   ├── dist                     # Distribution files for PyInstaller
│   ├── genre/                   # Genre detection files
│   │   ├── dataset.json         # Dataset for genre detection
│   │   ├── genre_detection.py    # Genre detection logic
│   │   └── genre_model.pkl       # Pre-trained genre classification model
│   ├── presets/                 # Presets directory
│   │   ├── custom_presets.pkl    # Saved custom EQ presets
│   │   ├── genre_presets.pkl     # Pre-defined genre classification presets
│   ├── .env                     # Environment variables for Spotify API
│   ├── artist_genres.pkl        # Artist-genre mapping
│   ├── equalizer.py             # Main equalizer logic and UI
│   ├── main.py                  # Entry point of the application
│   ├── requirements.txt         # Python dependencies
│   ├── spotify_integration.py   # Spotify integration logic
│   ├── styles.qss               # Styles for the application
│   ├── icon.jpg                 # Application icon
│
├── .gitattributes               # Git attributes file
├── .gitignore                   # Ignored files for Git
├── README.md                    # Project documentation

1. Use the sliders to adjust the gain for each frequency band.
2. Select a genre preset from the dropdown to apply genre-specific settings.
3. Create custom presets:
   • Adjust the sliders as desired.
   • Enter a preset name in the text field.
   • Click "Save Custom."
4. Delete custom presets by selecting the preset and clicking "Delete Custom."

1. Enter Artist Name: In the "Assign Genre" section, enter the name of the artist you want to assign a genre to.
2. Select Genre: Choose the desired genre from the dropdown menu.
3. Assign Genre: Click the "Assign Genre" button to save the assignment.

1. Enter Artist Name: In the "Assign Genre" section, enter the name of the artist whose genre you want to reset.
2. Click Reset Genre: Click the "Reset Genre" button to remove the genre assignment for that artist.

• Update credentials in .env file. Refer to installation section.
• The "Currently streaming" section displays the current track and genre.
• If Auto EQ is enabled, the EQ will automatically adjust based on the detected genre.

1. No Sound Output/Input Detected:

   • Verify input/output device indices in start_stream() in equalizer.py.
   • Ensure PyAudio is correctly installed.

2. Spotify Integration Fails:

   • Verify .env file contains valid Spotify credentials.
   • Ensure your browser is logged into Spotify.

3. Custom Presets Not Saving:

   • Ensure the application has write permissions for custom_presets.pkl.

Contributions are welcome! Follow these steps:

1. Fork the repository.
2. Create a new branch: git checkout -b feature-name.
3. Commit your changes: git commit -m "Add feature-name".
4. Push to the branch: git push origin feature-name.
5. Submit a pull request.

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