Facial Expression Recognition

This project on Colab uses the FER 2013 dataset from Kaggle (FER+ is WIP).

Getting Started

1. Open the facial_expression_recognition.ipynb file on Colab or your computer.
2. Follow the Kaggle API authentication instructions to obtain a kaggle.json file and place it in the root directory of the project.
3. Run the code to download and extract the datasets. The datasets will be stored in a local fer2013 folder.

Data Description

The FER 2013 dataset consists of images of faces and the corresponding labels indicating the facial expression in each image. The labels are integers in the range 0-6, where each integer corresponds to a specific facial expression as follows:

• (0) Angry
• (1) Disgust
• (2) Fear
• (3) Happy
• (4) Sad
• (5) Surprise
• (6) Neutral

Each image is represented in the datasets as a string of grayscale pixels (integers in the range 0-255). The size of the images is 48x48.

Acknowledgements

• The Kaggle dataset was created by the "Challenges in Representation Learning: Facial Expression Recognition Challenge" competition organizers.
• The FER+ dataset was created by Microsoft.

Further Reading

• The Kaggle competition webpage for the FER 2013 dataset: https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge
• The GitHub repository for the FER+ dataset: https://github.com/microsoft/FERPlus
• A review of existing facial expression recognition datasets: https://arxiv.org/ftp/arxiv/papers/2105/2105.03588.pdf