omr
omr is a small Python 3 optical mark recognition script. It takes as input an image of an answered answer sheet and outputs which alternatives were marked. The project is generally optimized for conciseness and teachability, and the goal is to provide a reasonable starting point for learning and hopefully building more powerful applications.
Usage
$ python omr.py --help
usage: omr.py [-h] --input INPUT [--output OUTPUT] [--show]
optional arguments:
-h, --help show this help message and exit
--input INPUT Input image filename
--output OUTPUT Output annotated image filename
--show Displays annotated imageExample
$ python omr.py --input img/answered-sheet-photo.jpg --output /tmp/results.png --show
Q1: A
Q2: C
Q3: C
Q4: E
Q5: N/A
Q6: N/A
Q7: A
Q8: N/A
Q9: N/A
Q10: N/AIn this case, we used the following image as input:
And got the following output:
Installation
Using pipenv with pyenv
Install pyenv
$ git clone https://github.com/rbaron/omr
$ cd omr/
$ pyenv install 3.7.5
$ pyenv local 3.7.5
$ pipenv --python 3.7.5
$ pipenv install
$ pipenv shell
$ py.testUsing virtualenv
$ git clone https://github.com/rbaron/omr
$ cd omr/
$ virtualenv --python=`which python3` venv
$ source venv/bin/activate
(venv) $ pip install -r requirements.txt
(venv) $ python omr.py --helpAnwer Sheet
The answer sheet is available in the sheet/ directory.
Development
Run unit tests
test_omr.py contains unit tests that can be run using:
$ py.test
=========================================================== test session starts ===========================================================
platform darwin -- Python 3.7.5, pytest-5.2.4, py-1.8.0, pluggy-0.13.0
collected 1 item
test_omr.py . [100%]
============================================================ 1 passed in 0.31s ============================================================