Update README.md

README.md

@@ -1,81 +1,81 @@
----
-title: NeuroMusicLab
-emoji: 🐢
-colorFrom: indigo
-colorTo: red
-sdk: gradio
-sdk_version: 5.47.2
-app_file: app.py
-pinned: false
-short_description: A demo for EEG-based music composition and manipulation.
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
-
-# EEG Motor Imagery Music Composer
-
-A user-friendly, accessible neuro-music studio for motor rehabilitation and creative exploration. Compose and remix music using EEG motor imagery signals—no musical experience required!
-
-## Features
-
-- **Automatic Composition:** Layer musical stems (bass, drums, instruments, vocals) by imagining left/right hand or leg movements. Each correct, high-confidence prediction adds a new sound.
-- **DJ Mode:** After all four layers are added, apply real-time audio effects (Echo, Low Pass, Compressor, Fade In/Out) to remix your composition using new brain commands.
-- **Seamless Playback:** All completed layers play continuously, with smooth transitions and effect toggling.
-- **Manual Classifier:** Test the classifier on individual movements and visualize EEG data, class probabilities, and confusion matrix.
-- **Accessible UI:** Built with Gradio for easy use in browser or on Hugging Face Spaces.
-
-## How It Works
-
-1. **Compose:**
-   - Click "Start Composing" and follow the on-screen prompts.
-   - Imagine the prompted movement (left hand, right hand, left leg, right leg) to add musical layers.
-   - Each correct, confident prediction adds a new instrument to the mix.
-2. **DJ Mode:**
-   - After all four layers are added, enter DJ mode.
-   - Imagine movements in a specific order to toggle effects on each stem.
-   - Effects are sticky and only toggle every 4th repetition for smoothness.
-3. **Manual Classifier:**
-   - Switch to the Manual Classifier tab to test the model on random epochs for each movement.
-   - Visualize predictions, probabilities, and confusion matrix.
-
-## Project Structure
-
-```
-app.py                # Main Gradio app and UI logic
-sound_control.py      # Audio processing and effect logic
-classifier.py         # EEG classifier
-config.py             # Configuration and constants
-data_processor.py     # EEG data loading and preprocessing
-requirements.txt      # Python dependencies
-.gitignore            # Files/folders to ignore in git
-SoundHelix-Song-6/    # Demo audio stems (bass, drums, instruments, vocals)
-```
-
-## Quick Start
-
-1. **Install dependencies:**
-   ```bash
-   pip install -r requirements.txt
-   ```
-2. **Add required data:**
-   - Ensure the `SoundHelix-Song-1/` folder with all audio stems (`bass.wav`, `drums.wav`, `instruments.wav` or `other.wav`, `vocals.wav`) is present and tracked in your repository.
-   - Include at least one demo EEG `.mat` file (as referenced in your `DEMO_DATA_PATHS` in `config.py`) for the app to run out-of-the-box. Place it in the correct location and ensure it is tracked by git.
-3. **Run the app:**
-   ```bash
-   python app.py
-   ```
-4. **Open in browser:**
-   - Go to `http://localhost:7867` (or the port shown in the terminal)
-
-## Deployment
-
-- Ready for Hugging Face Spaces or any Gradio-compatible cloud platform.
-- Minimal `.gitignore` and clean repo for easy deployment.
-- Make sure to include all required audio stems and at least two demo `.mat` EEG file in your deployment for full functionality.
-
-## Credits
-
-- Developed by Sofia Fregni. Model training by Katarzyna Kuhlmann. Deployment by Hamed Koochaki Kelardeh.
-- Audio stems: [SoundHelix](https://www.soundhelix.com/)
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: NeuroMusicLab
+emoji: 🧠🎵
+colorFrom: indigo
+colorTo: red
+sdk: docker
+pinned: false
+license: mit
+short_description: A demo for EEG-based music composition and manipulation.
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# EEG Motor Imagery Music Composer
+
+A user-friendly, accessible neuro-music studio for motor rehabilitation and creative exploration. Compose and remix music using EEG motor imagery signals—no musical experience required!
+
+## Features
+
+- **Automatic Composition:** Layer musical stems (bass, drums, instruments, vocals) by imagining left/right hand or leg movements. Each correct, high-confidence prediction adds a new sound.
+- **DJ Mode:** After all four layers are added, apply real-time audio effects (Echo, Low Pass, Compressor, Fade In/Out) to remix your composition using new brain commands.
+- **Seamless Playback:** All completed layers play continuously, with smooth transitions and effect toggling.
+- **Manual Classifier:** Test the classifier on individual movements and visualize EEG data, class probabilities, and confusion matrix.
+- **Accessible UI:** Built with Gradio for easy use in browser or on Hugging Face Spaces.
+
+## How It Works
+
+1. **Compose:**
+   - Click "Start Composing" and follow the on-screen prompts.
+   - Imagine the prompted movement (left hand, right hand, left leg, right leg) to add musical layers.
+   - Each correct, confident prediction adds a new instrument to the mix.
+2. **DJ Mode:**
+   - After all four layers are added, enter DJ mode.
+   - Imagine movements in a specific order to toggle effects on each stem.
+   - Effects are sticky and only toggle every 4th repetition for smoothness.
+3. **Manual Classifier:**
+   - Switch to the Manual Classifier tab to test the model on random epochs for each movement.
+   - Visualize predictions, probabilities, and confusion matrix.
+
+## Project Structure
+
+```
+app.py                # Main Gradio app and UI logic
+sound_control.py      # Audio processing and effect logic
+classifier.py         # EEG classifier
+config.py             # Configuration and constants
+data_processor.py     # EEG data loading and preprocessing
+requirements.txt      # Python dependencies
+.gitignore            # Files/folders to ignore in git
+SoundHelix-Song-6/    # Demo audio stems (bass, drums, instruments, vocals)
+```
+
+## Quick Start
+
+1. **Install dependencies:**
+   ```bash
+   pip install -r requirements.txt
+   ```
+2. **Add required data:**
+   - Ensure the `SoundHelix-Song-1/` folder with all audio stems (`bass.wav`, `drums.wav`, `instruments.wav` or `other.wav`, `vocals.wav`) is present and tracked in your repository.
+   - Include at least one demo EEG `.mat` file (as referenced in your `DEMO_DATA_PATHS` in `config.py`) for the app to run out-of-the-box. Place it in the correct location and ensure it is tracked by git.
+3. **Run the app:**
+   ```bash
+   python app.py
+   ```
+4. **Open in browser:**
+   - Go to `http://localhost:7867` (or the port shown in the terminal)
+
+## Deployment
+
+- Ready for Hugging Face Spaces or any Gradio-compatible cloud platform.
+- Minimal `.gitignore` and clean repo for easy deployment.
+- Make sure to include all required audio stems and at least two demo `.mat` EEG file in your deployment for full functionality.
+
+## Credits
+
+- Developed by Sofia Fregni. Model training by Katarzyna Kuhlmann. Deployment by Hamed Koochaki Kelardeh.
+- Audio stems: [SoundHelix](https://www.soundhelix.com/)
+
+## License
+MIT License - see LICENSE file for details.