Skip to content

The System detects the facial emotion among the seven (happy, sad, angry ,surprise, fear, neutral, disgust) using the convolutional neural network (CNN) Architecture

Notifications You must be signed in to change notification settings

RajKhanke/facial-expression-detection-using-Machine-Learning

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

facial-expression-detection-using-Machine-Learning

The System detects the facial emotion among the seven different types of emotions using the convolutional neural network (CNN) Architecture at the accuracy rate of 60 % and a loss of less than 0.20.

The seven types of expressions are :

Angry

sad

fear

neutral

surprise

disgust

Happy

The model is trained and tested over fer_2013 image dataset available on kaggle, with the total epoche count of 50.

The model is connected with the web0cam using OpenCV.

To clone the repository in your system use :

git clone https://github.com/RajKhanke/facial-expression-detection-using-Machine-Learning.git

dataset link : https://www.kaggle.com/datasets/msambare/fer2013

About

The System detects the facial emotion among the seven (happy, sad, angry ,surprise, fear, neutral, disgust) using the convolutional neural network (CNN) Architecture

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published