Personality Prediction and Face Emotion Detection

This is the system that is responsible for determining a user's personality when they first enter the system. It will ask fifty questions, and users need to answer them by selecting a value from one to five. The values are declared as 1=Disagree, 3=Neutral, 5=Agree to the users to mark as answers for the fifty questions. The system assesses the user characteristics based on the given answers with the help of Machine Learning. After that, based on the analytics, it will give a personality to the user from a set of 16 predefined personality types according to the MBTI personality types. Every default personality type has a unique collection of traits. Therefore the data which consists of one million responses for 50 personality questions from the Big Five Personality Test from Kaggle is selected. ([login to view URL]) Then the data is fed into k-means (unsupervised learning algorithm) to discover the personality traits within all of the personality types. After that the model normalizes the data to plot the results to the user. The output will be the personality of a particular user. And also this system will determine the user's emotion through the face images which will be inputted by the User. This is not real time emotion detection. Using Machine Learning and OpenCV, it will determine the emotion which is shown on the user's face. It could be happy, anger, sad, neutral, or surprise. To implement the part, Images with emotions are collected. And detecting the faces in the images. Training the classifier on the faces is the next step. Then easily the model can recognize the emotion in the images. The output will be the emotion of a particular user. At the same time there must be a novelty in the part to prove this is a special one than other existing face emotion detection systems. For each part(Predicting the personality, Detecting the face emotion) of the whole system, you have to tell how we can validate the results using an evaluation method. That means there must be a way to prove that the system is working fine and the outputs are correct. Have to develop the project with python using Pycharm IDE. It is not for commercial purposes. This is actually a research project to be used for academic purposes. The payment provided for completion of the project is from 40 USD to 100 USD. Have to complete the project on or before the 15th of February, 2022. References [login to view URL] [login to view URL] [login to view URL]