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Emotion Detection from Image

Overview

This project uses a pre-trained emotion detection model to predict the emotion of a person from an image. The emotion categories include:

  • Angry
  • Disgust
  • Fear
  • Happy
  • Sad
  • Surprise
  • Neutral

The model is based on the FER-2013 dataset and can classify emotions based on facial expressions. The goal of this project is to build a simple yet effective emotion detection system that can analyze a given image and predict the emotion in real-time.

Requirements

To run the code successfully, you need to have the following libraries installed:

  • opencv-python: OpenCV library for image and video processing.
  • keras: Keras library to work with deep learning models.
  • matplotlib: To display images and results.
  • numpy: To handle numerical operations.

You can install these libraries using pip:

pip install opencv-python opencv-python-headless keras matplotlib numpy

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