https://github.com/publishername/moodmelodynepal
MoodMelodyNepal is an application that uses facial recognition to analyze emotions and recommend Nepali songs that align with the user's mood.
https://github.com/publishername/moodmelodynepal
ai django emotion-detection music-player playlist youtube youtube-api
Last synced: about 2 months ago
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MoodMelodyNepal is an application that uses facial recognition to analyze emotions and recommend Nepali songs that align with the user's mood.
- Host: GitHub
- URL: https://github.com/publishername/moodmelodynepal
- Owner: PublisherName
- License: mit
- Created: 2024-11-18T13:04:50.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-14T16:15:12.000Z (over 1 year ago)
- Last Synced: 2025-03-15T04:22:28.535Z (over 1 year ago)
- Topics: ai, django, emotion-detection, music-player, playlist, youtube, youtube-api
- Language: Jupyter Notebook
- Homepage: https://moodmelodynepal.onrender.com/
- Size: 13.9 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Nepali Music Recommendation
An music player that suggests YouTube playlists based on your detected emotional state.
## Features
- Real-time emotion detection using webcam
- Mood-based playlist recommendations
- YouTube playlist integration
- Responsive web interface
- Support for multiple emotional states (Happy, Sad, Angry, Neutral, Surprise, Calm)
## Tech Stack
- Python/Django
- TensorFlow for emotion detection
- YouTube Data API
- Bootstrap 5
- JavaScript/AJAX
## Setup
1. Clone the repository:
```bash
git clone https://github.com/publishername/MoodMelodyNepal.git
```
2. Change the directory:
```bash
cd MoodMelodyNepal
```
3. Set up a virtual environment:
```bash
python -m venv .venv
source venv/bin/activate
```
4. Install the dependencies:
```bash
pip install -r requirements.txt
```
5. Copy the `.env.example` file to `.env` and set the environment variables:
```bash
cp .env.example .env
```
6. Load Dummy Playlist:
```bash
python manage.py loaddata seeds/music.json
```
7. Run the server:
```bash
python manage.py runserver
```
8. Open the web interface in your browser:
```bash
http://127.0.0.1:8000/
```