https://github.com/andreihar/emotion-recognition

Facial emotions recognition CNN
https://github.com/andreihar/emotion-recognition

cnn emotion-recognition keras machine-learning

Last synced: 27 days ago
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Facial emotions recognition CNN

• Host: GitHub
• URL: https://github.com/andreihar/emotion-recognition
• Owner: andreihar
• Created: 2023-06-13T16:57:40.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-08-20T02:31:53.000Z (3 months ago)
• Last Synced: 2024-08-21T05:58:53.956Z (3 months ago)
• Topics: cnn, emotion-recognition, keras, machine-learning
• Language: Jupyter Notebook
• Homepage: https://github.com/andreihar/emotion-recognition
• Size: 62.5 MB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        



  

    

  

  

# Emotion Recognition


![Contributors][contributors-badge]

**CNN model for classifying facial emotions into seven categories using Keras**

A deep learning model for facial emotion classification. This Keras-based project includes a CNN architecture and pre-trained weights for quick testing on custom images.



---

  Table of Contents

  


    


      About The Project

      


        
Built With

      

    

    
Run

    
Data

    
Contributors

  


## About The Project

This is the final project created for the Spring semester of 2023 course in Introduction to Artificial Intelligence with a focus on the study of Machine Learning.

The project is a Convolutional Neural Network (CNN) model architecture that classifies human facial emotions into one of the 7 categories. During the project development iterative process, many different machine learning ideas were tested and evaluated based on the performance metrics.

The CNN was implemented using the Keras API and is described in detail in the project notebook.

### Built With

* [![Keras][keras-badge]][keras]

* [![NumPy][numpy-badge]][numpy]

* [![sklearn][sklearn-badge]][sklearn]

## Run

Open the notebook using your choice software in a terminal or command window by navigating to the top-level project directory, `emotion-recognition`. For example, if the software is Jupyter Notebook:

```bash

jupyter notebook emotion_recognition.ipynb

```

The project folder includes the weights of the trained neural network and the model can be tested on custom images without requiring to train it again.

## Data

This dataset is a modified version of the Emotion Detection dataset found on [Kaggle](https://www.kaggle.com/datasets/ananthu017/emotion-detection-fer), consisting of 35887 data entries, classified into 7 categories.

## Contributors

- Andrei Harbachov ([Github][andrei-github] · [LinkedIn][andrei-linkedin])

- Shane Eastwood ([Github][shane-github] · [LinkedIn][shane-linkedin])

[contributors-badge]: https://img.shields.io/badge/Contributors-2-44cc11?style=for-the-badge

[keras-badge]: https://img.shields.io/badge/keras-d10000?style=for-the-badge&logo=keras&logoColor=ffffff

[keras]: https://keras.io/

[numpy-badge]: https://img.shields.io/badge/numpy-013243?style=for-the-badge&logo=numpy&logoColor=ffffff

[numpy]: https://numpy.org/

[sklearn-badge]: https://img.shields.io/badge/sklearn-f89a36?style=for-the-badge&logo=scikitlearn&logoColor=ffffff

[sklearn]: https://scikit-learn.org/stable/

[andrei-linkedin]: https://www.linkedin.com/in/andreihar/

[andrei-github]: https://github.com/andreihar

[shane-linkedin]: https://www.linkedin.com/in/shane-eastwood-3549479b/

[shane-github]: https://github.com/sjeastwood