An open-source tool for fast and accurate Optical Mark Recognition (OMR) from scanned documents or mobile photos.
OMRChecker is an open-source Optical Mark Recognition (OMR) software that automatically reads and evaluates marked responses on OMR sheets from scanned documents or mobile photos. It solves the problem of manual OMR grading by providing fast, accurate, and customizable automation for exams, surveys, and forms.
Educators, exam administrators, survey creators, and developers who need to automate OMR-based data collection and evaluation without proprietary software.
Developers choose OMRChecker for its high accuracy, robustness with low-quality images, open-source flexibility, and cost savings compared to commercial OMR solutions, all while being backed by an active community.
Evaluate OMR sheets fast and accurately using a scanner 🖨 or your phone 🤳.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Achieves nearly 100% accuracy on good-quality document scans, as stated in the README, making it reliable for standardized exams and surveys.
Processes low-resolution, xeroxed, and rotated sheets, demonstrated in sample GIFs and the robustness wiki, reducing preprocessing needs.
Handles over 200 OMR sheets per minute, tested at large-scale events like Technothlon, ideal for bulk grading or data collection.
Provides step-by-step processing images and colored outputs, aiding in configuration and troubleshooting, as highlighted in the wiki visuals.
Requires manual installation of Python, OpenCV, and dependencies, with documented issues on Windows and Linux needing troubleshooting steps.
Lacks a graphical user interface; all operations are command-line based, making it inaccessible for non-technical end-users.
Accuracy falls to about 90% on mobile images, per the README, which may require additional quality checks for high-stakes applications.