In this tutorial, we'll see how we can create a python program that will detect emotion on a human face. This might be interesting if you want to do things like emotion detection using python, or if you're training machine learning systems to read human emotions. We're going to create a program that takes an image as an input and outputs a list of human emotions that the image invokes. To do this, we're going to use a package called Deepface. Deepface is an open-source face recognition attribute analysis framework that was created for python.
Recognition of the face as an identity is a critical aspect in today's world. Facial identification and recognition find its use in many real-life contexts, whether your identity card, passport, or any other credential of significant importance. It has become quite a popular tool these days to authenticate the identity of an individual. This technology is also being used in various sectors and industries to prevent ID fraud and identity theft. Your smartphone also has a face recognition feature to unlock it.
Whatever we feel at heart is understood by our facial expressions. Facial expressions are a vital mode of communication. It is said that any person's behaviour is controlled by his/her face. Social Media to video chat applications our emotions are tracked everywhere. Medical research has also used them widely.
Key value databases come with a high speed and performance where we mostly cannot reach in relational databases. Herein similar to Cassandra, Redis is a fast key value store solution. In this post, we are going to adopt Redis to build an overperforming face recognition application. On the other hand, this could be adapted to NLP studies or any reverse image search case such as in Google Images. The official redis distribution is available for Linux and MacOS here.