![]() They're required that if they changed their answers, they should erase the mistake completely, but some don't fully erase it, though this case should be considered as a correct answer if the black answer is correct if and only if there's a clear difference between intensity levels of the marked answers like in Q35 answers: They're required to use the same fill level all over the answer sheet, but you'll find someone who doesn't fill the circles consistently across his/her answer sheet: ![]() They're required to have only one answer per question, but some students just don't, so this should be considered a mistake even if any of the two filled answers is correct: They're required to fully fill the circle of the answer, but some students just don't: They are required to use a 2B Pen, but some students use a lighter pen: The challenges you'll face during building your automatic solution are usually due to students not following the rules: Manually correcting a huge amount of data is a very time-consuming task, also creating an intelligent system without being 100% accurate won't be a usable solution, as we can't accept that a student doesn't get what he/she deserves, that's why we're not targeting only high accuracy, but we're targeting a perfect solution. And my team's solution ranked the first with only one entry. In this competition, there were 52 teams competing. The competition is about designing an image processing pipeline to automatically correct the scanned documents for students answers. This repo contains the solution to the MCQ Corrector Kaggle Competition.
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