We will use 7 emotions namely - We have use 7 emotions namely - 'Angry'😠, 'Disgust'🤢, 'Fear'😱, 'Happy'😇, 'Neutral'😐, 'Sad'☹️, 'Surprise'😲 to train and test(validation) our algorithm using Convolution Neural Networks. You can directly use kaggle kernel notebook, so that you don't need to download the dataset. Also, you can download your code and run it in your local device directly.
Kaggle notebook - https://www.kaggle.com/mayank7900/notebook0a0917a828/edit

Tools and Libraries used -

• Install anaconda
• Jupyter notebook
• VSCode
• matplotlib
• numpy
• openCV
• keras

Given dataset of different expressions:

https://www.kaggle.com/jonathanoheix/face-expression-recognition-dataset

Screenshot of some angry expressions from the dataset on kaggle:

• source code -

  mayankchaudhary26 / Emotion_Detection_CNN_keras

  Train and test our algorithm using Convolution Neural Networks and classify emotions in real-time.

  Emotion_Detection_CNN_keras

  We will use 7 emotions namely - 'Angry'😠, 'Disgust'🤢, 'Fear'😱, 'Happy'😇, 'Neutral'😐, 'Sad'☹️, 'Surprise'😲 to train and test our algorithm using Convolution Neural Networks.
  
  

  You need a dataset with different emotions :

  
  

  Given dataset of different expressions on kaggle:

  https://www.kaggle.com/jonathanoheix/face-expression-recognition-dataset

  
  

  
  

  View on GitHub

  
  

Emotion Detection — Classifying the emotion on the face as emotion_labels = ['Angry','Disgust','Fear','Happy','Neutral', 'Sad', 'Surprise']