Format-specific converter
What this converter does
Images do not contain a selectable text layer, so this route uses optical character recognition. The result is best for sharp, upright images with clear printed text and visible table boundaries.
Input and output
- Input: PNG, JPG, JPEG, WEBP, TIFF, or TIF
- Output: Editable Markdown text
- Method: OCR with layout-aware Markdown output
Before-and-after example
This example shows the kind of structure the converter attempts to recover. Actual output depends on the source file.
[Screenshot] Release checklist ✓ Tests pass ✓ Backup verified
# Release checklist - Tests pass - Backup verified
Formatting behavior
| Element | Behavior |
|---|---|
| Printed text | Recognized and returned as editable text |
| Visible headings | Mapped when size and layout make hierarchy clear |
| Simple tables | Mapped when rows and columns can be recognized |
| Handwriting | May be incomplete or inaccurate |
Known limitations
- Blur, glare, skew, handwriting, and low contrast reduce OCR accuracy.
- The converter reads text; it does not recreate the original graphic design.
- Always verify names, numbers, and legal or financial text against the source image.
File lifecycle and privacy
The source file is processed in a request-scoped temporary directory and deleted when the request ends. Generated Markdown is stored in the service database so it can be delivered after account verification; there is not yet an automatic time-based deletion policy. Read the privacy notice or request deletion before uploading sensitive material.
Local and online alternatives
A phone scanner app can improve perspective and contrast before conversion. A local OCR engine is better for highly sensitive material or large automated batches. This route is aimed at fast browser-based extraction with no local setup.