Ani-Moji

Ani (animation)-Moji (emoji)
Example of Happy emoji
Angry
disgusted
fearful
happy
neutral
sad
surprised

Inspiration

Emojis or avatars are ways to indicate nonverbal cues. These cues have become an essential part of online chatting, product review, brand emotion, and many more. It also lead to increasing data science research dedicated to emoji-driven storytelling.

What it does

With advancements in computer vision and deep learning, it is now possible to detect human emotions from images. In this deep learning project, we will classify human facial expressions to filter and map corresponding emojis or avatars. We will analyze the live video feeds in real-time to capture the face and find out the expression.

How we built it

In this project, will build a convolution neural network architecture and train the model on the FER2013 dataset for Emotion recognition from images. Using OpenCV’s haar cascade xml we are getting the bounding box of the faces in the webcam. Then we feed these boxes to the trained model for classification.

About the Dataset

The FER2013 dataset from Kaggle ( facial expression recognition) consists of 48*48 pixel grayscale face images. The images are centered and occupy an equal amount of space. This dataset consist of facial emotions of the following categories:

0:angry 1:disgust 2:feat 3:happy 4:sad 5:surprise 6:natural