/EmotionAI

EmotionAI uses a CNN model to analyze facial expressions and accurately recognize emotions (happiness, sadness, anger, etc.)

Primary LanguagePython

EmotionAI

EmotionAI is an Emotion Detection tool powered by artificial intelligence technology. It leverages a powerful CNN model to analyze facial expressions and accurately recognize emotions such as happiness, sadness, anger, and more. final

Features

  • Real-time emotion detection from webcam feed.
  • Supports multiple emotions including Angry, Disgust, Fear, Happy, Neutral, Sad, and Surprise.
  • Simple and intuitive user interface.

Demo

Go to the website link to test the project yourself.

Installation

  1. Clone the repository:
git clone https://github.com/your-username/EmotionAI.git
cd EmotionAI
  1. Install the required dependencies:
pip install -r requirements.txt
  1. Run the EmotionAI tool:
streamlit run app.py

Technologies Used

  • Python
  • OpenCV
  • Keras
  • TensorFlow
  • Streamlit
  • Streamlit WebRTC

Model Training

If you're interested in training your own emotion detection model, follow these steps:

  • Download the images dataset from here: https://www.kaggle.com/jonathanoheix/face-expression-recognition-dataset
  • Implement and train a Convolutional Neural Network (CNN) model using a framework like Keras or TensorFlow.
  • Evaluate the model's performance and fine-tune as necessary.
  • Save the trained model weights.
  • Update the model.h5 file in the project with your own trained model.