Local bubble sheet grader with printable answer templates
Create your own answer sheet and turn its filled bubbles into a reviewable grading ledger.
Bubble Grader
Choose your inputs, or load the working example to explore the result. Your files stay on this device.
Your inputs
Required fields are marked with an asterisk.
Your result
Review your output, then save it to your device.
Make the next step clear.
Your findings, assumptions and next steps will appear here after you run the check.
Bubble Grader · https://grader.kitforma.com/ · KitForma
Printable A4 answer sheets
Perspective-aligned local OMR
Ambiguous marks remain visible
Understand the evidence.
Focused guides explain the rules, the edge cases and the checks worth doing before you act.
Print an answer sheet the reader can recognize
Keep template geometry and marks intact.
Read the guide ↗Field guide / 02Review ambiguous OMR results before assigning grades
Treat ink measurements as evidence, not certainty.
Read the guide ↗Field guide / 03Keep a grading ledger you can audit
Export both totals and the underlying answers.
Read the guide ↗Before you start
Can it read another company’s bubble sheet?
No. It requires the KitForma KF-OMR-1 template and matching question/choice settings.
Are ambiguous answers counted as wrong?
They are labelled review rather than guessed. Confirm or correct them before recording a final grade.
Do student images leave the browser?
No. Image decoding, alignment and bubble measurements run locally in the page.
Can I grade a PDF scan?
This release takes JPEG, PNG or WebP photos. Export PDF pages as images with all corner marks visible first.
Sources & assumptions
Formats, algorithms and supported features are documented below. Check the stated scope and inspect your output before using it.
- OpenCV geometric transformations ↗
A planar page can be aligned with a projective transformation.
- Canvas pixel processing ↗
Pixels can be processed locally without sending images.
- OMR form design guidance ↗
Mark placement and form structure matter for optical recognition.
Reviewed 2026-10-17. Read our methodology or report an issue.