https://github.com/petercunha/Emotion

:smile: Recognizes human faces and their corresponding emotions from a video or webcam feed. Powered by OpenCV and Deep Learning.
https://github.com/petercunha/Emotion

deep-learning emotion-recognition facial-recognition opencv tensorflow

Last synced: 9 days ago
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:smile: Recognizes human faces and their corresponding emotions from a video or webcam feed. Powered by OpenCV and Deep Learning.

• Host: GitHub
• URL: https://github.com/petercunha/Emotion
• Owner: petercunha
• License: mit
• Created: 2017-11-13T15:11:28.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2021-12-30T19:36:09.000Z (almost 3 years ago)
• Last Synced: 2024-08-01T17:23:31.568Z (3 months ago)
• Topics: deep-learning, emotion-recognition, facial-recognition, opencv, tensorflow
• Language: Python
• Homepage:
• Size: 9.1 MB
• Stars: 445
• Watchers: 25
• Forks: 169
• Open Issues: 15
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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• awesome-affective-computing - Emotion
• awesome-affective-computing - Emotion

README

        
# Emotion

This software recognizes human faces and their corresponding emotions from a video or webcam feed. Powered by OpenCV and Deep Learning.

![Demo](https://github.com/petercunha/Emotion/blob/master/demo/demo.gif?raw=true)

## Installation

Clone the repository:

```

git clone https://github.com/petercunha/Emotion.git

cd Emotion/

```

Install these dependencies with `pip3 install `

-	tensorflow

-	numpy

-	scipy

-	opencv-python

-	pillow

-	pandas

-	matplotlib

-	h5py

-	keras

Once the dependencies are installed, you can run the project.

`python3 emotions.py`

## To train new models for emotion classification

- Download the fer2013.tar.gz file from [here](https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data)

- Move the downloaded file to the datasets directory inside this repository.

- Untar the file:

`tar -xzf fer2013.tar`

- Download train_emotion_classifier.py from orriaga's repo [here](https://github.com/oarriaga/face_classification/blob/master/src/train_emotion_classifier.py)

- Run the train_emotion_classification.py file:

`python3 train_emotion_classifier.py`

## Deep Learning Model

The model used is from this [research paper](https://github.com/oarriaga/face_classification/blob/master/report.pdf) written by Octavio Arriaga, Paul G. Plöger, and Matias Valdenegro.

![Model](https://i.imgur.com/vr9yDaF.png?1)

## Credit

* Computer vision powered by OpenCV.

* Neural network scaffolding powered by Keras with Tensorflow.

* Convolutional Neural Network (CNN) deep learning architecture is from this [research paper](https://github.com/oarriaga/face_classification/blob/master/report.pdf).

* Pretrained Keras model and much of the OpenCV code provided by GitHub user [oarriaga](https://github.com/oarriaga).