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Image to Markdown Converter
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Turn printed text into a useful starting point.
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Optional: download audit files for verification or troubleshooting.
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Your link, in Markdown
Upload a clear screenshot or scanned page. This image OCR to Markdown workflow returns reviewable text and keeps the original image beside it for AI use. Download the result as Markdown (.md).
PNG, JPEG, WebP, TIFF, and BMP are supported. We show the estimate first; Credit v2 bills 0.5 Credit per actual OCR image.
The Markdown contains OCR text and a relative reference to the original image. Metadata records line-level confidence and the exact low-confidence lines so weak output is visible before reuse.
Markovo checks the extension, MIME type, image signature, file size, and decoded pixel limit.
Offline OCR reads clear text without sending the image to another conversion API.
Download output.md or the full bundle with assets/source.* and quality evidence.
image-to-markdownUse the browser, API, CLI, or MCP through one account and History.
Single-column scans and high-contrast text are the safest first use cases.
Tables, formulas, handwriting, charts, and multi-column reading order may need review.
Markdown, the source image, metadata, source map, quality report, manifest, and ZIP use one contract.
curl -X POST https://markovo.net/v1/convert \
-H "Authorization: Bearer ${MARKOVO_API_KEY}" \
-F "file=@scan.png" \
-F "capability_id=image-to-markdown" \
-F "max_credits=0.5"markovo convert scan.png \
--out runs/scan \
--max-credits 0.5markovo_convert({
"input_path": "scan.png",
"max_credits": 0.5
})OCR converts visible pixels into candidate text; it does not make the source image unnecessary. Markovo keeps the original beside the Markdown so uncertain characters and layout can be checked.
High contrast, readable type, complete margins, and a consistent orientation improve extraction. Blur, shadows, compression, handwriting, tiny text, curved pages, and mixed scripts can reduce confidence.
Columns, forms, receipts, screenshots, and tables may need manual ordering. OCR can recover words without fully preserving the visual relationship among labels, values, icons, or diagram elements.
Compare names, identifiers, totals, dates, equations, and low-confidence spans with the original. Do not treat valid Markdown as proof that every character is correct.
For receipts, forms, research figures, screenshots, or identity-sensitive material, retain the original asset and compare every consequential field. The bundle makes that review possible without presenting OCR confidence as guaranteed accuracy.
OCR is a starting point with receipts, not a transcript guarantee: use it to make photos and scans searchable, citable, and diffable, then keep the source image beside the Markdown wherever the text feeds something consequential — invoices, datasets, or AI context.
Images have no text layer — this route is OCR-first by design. Line-level confidence and the exact low-confidence lines are recorded in the bundle's metadata, not silently approximated.
Screenshots, photos of documents and scanned pages convert to Markdown — visible text lands as structured output.
Handwriting is a listed known limit of this route — always compare with the source image.
Dense grids and small print are where image OCR degrades — check cells and footnote-size text against the image.
Non-textual marks are easy to misread — compare annotated or stamped regions against the original.
Each uploaded image converts as its own job — for multi-page scans or document photos, use PDF to Markdown so pages keep their order and per-page routing.
Format references: CommonMark · how the pipeline routes each page is covered in the converter comparison guide. Multi-page scans? PDF to Markdown keeps page structure.
Image to MD uses OCR to put visible text into a Markdown (.md) document. Compare the output with the image, especially small print, tables, and symbols.
PNG, JPEG, WebP, TIFF, and BMP. The file’s extension, MIME type, image signature, size, and decoded pixel count are all validated before OCR runs.
Each image converts as its own job — upload several images and they are queued separately. For multi-page scans or document photos, use PDF to Markdown — pages keep their order and get per-page routing.
Metadata records line-level OCR confidence and names the exact lines that scored low. Treat those lines as a review checklist — compare names, totals, dates, and symbols with the original image before reuse.
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