🎯 Features

OMR checking software that can read and evaluate OMR sheets scanned at any angle and having any color. Independent for scanner or mobile camera. Just you need image!

Specs
💯 Accurate	Currently nearly 100% accurate on good quality document scans; and about 95% accurate on mobile images.
💪🏿 Robust	Supports low resolution with Robust feature.
⏩ Fast	Current processing speed without any optimization is 220 OMRs/minute.
✅ Customizable	Easily custom OMR layouts.
📊 Visually Rich	Visually rich console using.
🎈 Lightweight	Very minimal and lightweight core code.
🏫 Large Scale	Tested with Nokta Tek Egitim Kurumlari and Cozum Yenimahalle exams.

Contributors

• duhanguler
• elffbykll
• erayerglc

You can contribute our project with TODO sections. For example

Getting started

Operating system: OSX or Linux is recommended although Windows is also supported.

1. Install global dependencies

To check if python3 and pip is already installed:

python3 --version
python3 -m pip --version

Install Python3

To install python3 follow instructions here

To install pip - follow instructions here

Install OpenCV

Any installation method is fine.

Recommended:

python3 -m pip install --user --upgrade pip
python3 -m pip install --user opencv-python
python3 -m pip install --user opencv-contrib-python

More details on pip install openCV here.

Extra steps(for Linux users only)

Installing missing libraries(if any):

On a fresh computer, some of the libraries may get missing in event after a successful pip install. Install them using following commands(ref):

sudo apt-get install -y build-essential cmake unzip pkg-config
sudo apt-get install -y libjpeg-dev libpng-dev libtiff-dev
sudo apt-get install -y libavcodec-dev libavformat-dev libswscale-dev libv4l-dev
sudo apt-get install -y libatlas-base-dev gfortran

2. Install project dependencies

Clone the repo

git clone https://github.com/duhanguler/omr
cd omr/

Install pip requirements

python3 -m pip install --user -r requirements.txt

Note: If you face a distutils error in pip, use --ignore-installed flag in above command.

3. Run the code

1. First copy and examine the sample data to know how to structure your inputs:

   cp -r ./samples/sample1 inputs/
   # Note: you may remove previous inputs (if any) with `mv inputs/* ~/.trash`
   # Change the number N in sampleN to see more examples

2. Run program:

   python3 main.py

Alternatively you can also use python3 main.py -i ./samples/sample1.

Each example in the samples folder demonstrates different ways in which OMR can be used.