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This project aims to develop a facial expression detection model that can recognize and classify human facial expressions such as happiness, sadness, anger, surprise, etc. The project employs image processing and deep learning techniques utilizing Convolutional Neural Networks (CNN) as the model architecture.

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Real-time Facial Expression Detection with WebRTC

Deskripsi: This project aims to develop a facial expression detection model that can recognize and classify human facial expressions such as happiness, sadness, anger, surprise, etc. The project employs image processing and deep learning techniques utilizing Convolutional Neural Networks (CNN) as the model architecture. The dataset used is sourced from kaggle which was uploaded by JONATHAN OHEIX.

Link Dataset: https://www.kaggle.com/datasets/jonathanoheix/face-expression-recognition-dataset.

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DEMO

Installation

  1. Clone this repository to your local machine.
  2. Navigate to the project directory.
cd deteksi-ekspresi-wajah
  1. Install the required dependencies using pip.
pip install -r requirements.txt
  1. Run the application.
streamlit run streamlit_app.py
  1. Access the application in your web browser at http://localhost:8501.

Made with ❤️ by 8shagrid

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This project aims to develop a facial expression detection model that can recognize and classify human facial expressions such as happiness, sadness, anger, surprise, etc. The project employs image processing and deep learning techniques utilizing Convolutional Neural Networks (CNN) as the model architecture.

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