Emotion Detection Django Project

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

Demo Images

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Project Structure

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.

Installation

Follow these steps to set up and run the project:

1. Clone the repository:

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

2. Create a virtual environment (optional but recommended):

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

3. Install dependencies:

   pip install -r requirements.txt

4. Apply migrations:

   python manage.py migrate

5. Run the development server:

   python manage.py runserver

6. Visit http://127.0.0.1:8000/face_detection/ in your web browser to access the face detection endpoint.

Usage

1. Post an image to the face_detection/ endpoint using a tool like Postman or by making a POST request to the endpoint.

2. The server will detect emotions, recommend songs and books based on the detected emotion, and return the results.

Notes

• 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.