Emotion Detection Django Project

This Django project uses facial emotion detection to recommend songs and books based on the detected emotion.

Demo Images

The project has the following structure:

core: Core application of the Django project.
demoImages: Folder containing image files for testing the emotion detection.
emotion_detector: Django app for handling emotion detection and recommendations.
static: Static files for the project.
db.sqlite3: SQLite database file.

Follow these steps to set up and run the project:

Clone the repository:

git clone <repository_url>
cd emotion_detection_django-main
cd emotion_detection_django-main

Create a virtual environment (optional but recommended):

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

Install dependencies:
```
pip install -r requirements.txt
```
Apply migrations:
```
python manage.py migrate
```
Run the development server:
```
python manage.py runserver
```
Visit http://127.0.0.1:8000/face_detection/ in your web browser to access the face detection endpoint.

Post an image to the face_detection/ endpoint using a tool like Postman or by making a POST request to the endpoint.
The server will detect emotions, recommend songs and books based on the detected emotion, and return the results.

The project uses TensorFlow for emotion detection and Django for the web framework.
Ensure that your environment supports the required dependencies, including TensorFlow.
This project assumes proper configuration of the database and Cloudinary settings.
Additional configurations such as database settings may be needed for production deployment.