AditAg/Emotion-detection

Identify the emotion (neutral, anger, contempt, disgust, fear, happy, sadness, surprise) in a given static image

Emotion-detection

Identify the emotion (neutral, anger, contempt, disgust, fear, happy, sadness, surprise) in a given static image. This is an example of a Supervised Machine Learning problem.

Prerequisites

• CK+ AU Coded Database is available for free. It can be downloaded from here. http://www.consortium.ri.cmu.edu/ckagree/
• Install the following python libraries:
  • pandas
  • sklearn
  • numpy

Getting Started

Run read_database.py

python read_database.py

This will create a file emos.csv that can be opened and edited in Excel. This file has all features (AU Codes) and labels (Emotions).

Next run classifier_test.py

python classifier_test.py

See the ouput and compare accuracy, recall, precision, F-measure of different classifiers. Additionally, Confusion Matrix can be printed

from pandas_ml import ConfusionMatrix as cm
print cm(y_true,y_predicted)