Generation and grading of arduous MCQs using NLP and OMR detection using OpenCV

During the 21st century pandemic, it has become difficult for students and teachers to engage physically in the aftermath of the epidemic, the process of assessing and grading students has become cumbersome. Multiple Choice Questions (MCQs) have increasingly become a more popular method of assessing a person's knowledge, but the questions which are generated directly from the chapter provided are readily available on the internet. Thus évaluer, the proposed approach solves this problem by paraphrasing the text, and thus the questions, so as to make it difficult to look it up on the internet. Usage of OMR (Optical Mark Recognition) sheets or manual correction had been prominent in the pre-pandemics situation. The évaluer automates the process of generation of MCQs which are difficult to search on the internet, and speeds up the task of grading a candidate's OMR answer sheet.