Read OMR sheets fast and accurately using a scanner 🖨 or your phone 🤳.

OMR stands for Optical Mark Recognition, used to detect and interpret human-marked data on documents. OMR refers to the process of reading and evaluating OMR sheets, commonly used in exams, surveys, and other forms.

• Installation
• User Guide
• Contributor Guide
• Project Ideas List

A full-fledged OMR checking software that can read and evaluate OMR sheets scanned at any angle and having any color.

Specs
💯 Accurate	Currently nearly 100% accurate on good quality document scans; and about 90% accurate on mobile images.
💪🏿 Robust	Supports low resolution, xeroxed sheets. See Robustness for more.
⏩ Fast	Current processing speed without any optimization is 200 OMRs/minute.
✅ Customizable	Easily apply to custom OMR layouts, surveys, etc.
📊 Visually Rich	Get insights to configure and debug easily.
🎈 Lightweight	Very minimal core code size.
🏫 Large Scale	Tested on a large scale at Technothlon.
👩🏿‍💻 Dev Friendly	Pylinted and Black formatted code. Also has a developer community on discord.

Note: For solving interesting challenges, developers can check out TODOs.

See the complete guide and details at Project Wiki.

Once you configure the OMR layout, just throw images of the sheets at the software; and you'll get back the marked responses in an excel sheet!

Images can be taken from various angles as shown below-

See step-by-step processing of any OMR sheet:

*Note: This image is generated by the code itself!*

Get a CSV sheet containing the detected responses and evaluated scores:

We now support colored outputs as well. Here's a sample output on another image -

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

To check if python3 and pip is already installed:

python3 --version
python3 -m pip --version

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

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

Clone the repo

git clone https://github.com/Udayraj123/OMRChecker
cd OMRChecker/

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.

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 OMRChecker:

   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 OMRChecker can be used.

1. First, create your own template.json.
2. Configure the tuning parameters.
3. Run OMRChecker with appropriate arguments (See full usage).

python3 main.py [--setLayout] [--inputDir dir1] [--outputDir dir1]

Explanation for the arguments:

--setLayout: Set up OMR template layout - modify your json file and run again until the template is set.

--inputDir: Specify an input directory.

--outputDir: Specify an output directory.

A Huge thanks to: Adrian Rosebrock for his exemplary blog: https://pyimagesearch.com

Harrison Kinsley aka sentdex for his video tutorials and many other resources.

Satya Mallic for his resourceful blog: https://www.learnopencv.com

And to other amazing people from all over the globe who've made significant improvements in this project.

Thank you!

Here's a snapshot of the Android OMR Helper App (archived):

For more details see LICENSE.

Find OMRChecker on Product Hunt | Reddit | Discord | Linkedin | goodfirstissue.dev | codepeak.tech | fossoverflow.dev | Interview on Console by CodeSee | Open Source Hub