Convert to Markdown

Converts PDF, Word, PowerPoint, Excel and image files in your vault into Markdown notes, images and all.

No LLM, no API key, no cloud service, no external binary. Nothing you convert is uploaded anywhere — every byte is processed on your machine.

Documents (.pdf, .docx, .pptx, .xlsx) are parsed directly from their own structure, which makes them fully deterministic and fully offline: the same file always produces byte-identical Markdown.

Image files are the one exception, and differ on both counts. Pixels carry no structure, so reading one means OCR — statistical rather than structural, and occasionally wrong, which is why it reports its confidence. Tesseract is a local neural recogniser, not a language model and not a service. It also downloads its engine the first time you use it. Details under OCR.

Installing

Settings → Community plugins → Browse → search Convert to Markdown → Install, then Enable.

Nothing else. No runtime to install, no binary to put on PATH, no account. Desktop only — it uses Node's zlib, which Obsidian mobile doesn't have.

The first time you convert an image, there's a one-off engine download (see OCR); the notice shows its progress. Everything else works immediately and offline.

Usage

• Right-click a supported file in the file explorer → Convert to Markdown
• Or run Convert to Markdown: Convert a file from the command palette

The note is written next to the original (configurable), never overwriting an existing note. Anything the converter dropped — images, hidden sheets, pages with no text layer — is listed in a collapsed callout at the end.

Compared to markitdown

The Obsidian plugins in this space wrap Microsoft's markitdown, which is one abstraction over every format: it makes one-size-fits-all decisions about what structure means, and those decisions are where the mess comes from.

Nothing to install. A markitdown-based plugin needs Python on the machine and pip install markitdown, and fails with "Python is not installed or not found at the configured path" until it has both. This one is plain JavaScript inside Obsidian — which also means it works on a locked-down machine where installing Python is the step that's blocked.

Structure survives. Headings keep their levels, lists stay lists, tables stay tables, and images are written into the vault and embedded at the point they appeared. Running the same PDF through both, markitdown returns the text hard-wrapped exactly where the PDF's column broke, hyphens included — medica- / tions, occlu- / sion — because a PDF line break is a typesetting artifact it preserves rather than undoes. This one rejoins the paragraph and repairs the hyphenation.

Multi-column PDFs read in order. Columns are detected per page and each is read top to bottom before the next, so a two-column paper doesn't come out interleaved. Full-width titles and headings are recognised as spanning the columns and stay where they belong, and running headers are stripped before the columns are worked out — otherwise a footer spread along the page bottom lands in the middle of the text.

Per format, what's read and what it buys:

Macro-enabled variants (.docm, .pptm, .xlsm) are the same parts plus a VBA blob, and convert identically.

Images

Images are pulled out of the source file, written to <note name> attachments/ beside the note, and embedded where they actually sat — a figure inside a Word table cell comes out inside that table cell. Identical images are written once no matter how many times they're used, so a logo on forty slides is one file.

Word, PowerPoint and Excel store images in their original encoding, so those come out untouched (.jpeg stays .jpeg). A PDF doesn't store files at all — it stores decoded pixels — so images from a PDF are re-encoded as PNG. Images under 64px on a side are treated as rules, bullets and icons and skipped.

Turn the whole thing off with Extract images in settings for text-only notes.

OCR

An image file has no structure to read, so converting one runs Tesseract — a classical OCR engine (line segmentation plus an LSTM character recogniser) compiled to WASM. It is not an LLM, takes no API key, and the image never leaves your machine.

The engine and its English model are not shipped in the plugin — an Obsidian release can only contain main.js, manifest.json and styles.css — so they download from jsdelivr the first time you convert an image:

That traffic is one-way: it fetches the engine, it never sends the image. After the first run OCR works with the network off, and nothing else in the plugin touches the network at all.

The download happens inside the first conversion, so that one takes noticeably longer than the rest. The notice reports what it's doing while it waits (loading language traineddata — 61%) rather than sitting on "Converting…".

Regions Tesseract is unsure of — lettering picked out of a photograph, logo marks, JPEG artefacts — are dropped rather than written into the note as gibberish, and counted in the conversion notes. Large display type reversed out of a coloured background is the common thing OCR misses; check the note against the image when the confidence warning appears.

Locked-down machines

If that CDN is blocked — common on corporate networks — put the two files in a vault folder and name it in OCR engine folder in settings. OCR then reads them straight from disk and makes no network request at all, on the first run or any other.

Download them once somewhere with access:

• https://cdn.jsdelivr.net/npm/tesseract.js-core@7/tesseract-core-simd-lstm.wasm.js
• https://cdn.jsdelivr.net/npm/@tesseract.js-data/eng/4.0.0_best_int/eng.traineddata.gz

Both go in the same folder, keeping their filenames (the .gz may be unzipped, either works). If the folder is set but a file is missing, the conversion says which one.

Known limits

• Column detection is geometric, not semantic. It reads the horizontal distribution of ink per page, so a layout no gutter runs through — text wrapped around a figure, a magazine-style collage — can still come out in the wrong order.
• Scanned PDFs are refused, not OCR'd. A PDF that is only page images has no text layer, and it is reported as an error rather than silently written as an empty note. The OCR path exists but is not wired into the PDF extractor.
• Windows metafiles (EMF/WMF) can't be embedded — nothing in Obsidian renders them — so they're skipped and counted.
• Excel formulas export as their last-calculated value — the value Excel itself stored in the file.
• Charts and embedded objects in decks are skipped and counted; a chart is a data structure, not a picture, so there's nothing to embed.
• Letter-spaced PDF headings can pick up stray spaces (THI S BOOK); the gap between tracked glyphs is genuinely wider than an unspaced word break.

Development

npm install
npm run dev     # watch build into main.js
npm run build   # type-check + production bundle

tools/convert.mjs runs the extractors outside Obsidian, so output can be checked against real files without reloading a vault:

OUT_DIR=/tmp/out node tools/convert.mjs ~/Downloads/deck.pptx ~/Downloads/report.pdf

It shims the two DOM globals Obsidian gets from Electron and otherwise runs the real extractor code. OCR_PROGRESS=1 prints the OCR stage reporting that the plugin puts in its notice.

Note on dependencies

The zip reader is hand-rolled (src/zip.ts) rather than JSZip. JSZip's transitive dependencies create <script> elements as a legacy task-scheduling trick, which gets plugins flagged by Obsidian's community-plugin review as "code obfuscation" — a false positive that is simpler to avoid than to argue. PNG encoding for PDF images is hand-rolled too (src/png.ts), on top of the zlib the zip reader already uses, so it works identically in Obsidian and in the Node harness.

The runtime dependencies are pdfjs-dist and tesseract.js. Both normally load their worker script from a separate file or a CDN at runtime; a plugin release can only ship main.js, manifest.json and styles.css, so both workers are inlined at build time and handed to the library as a Blob URL. Tesseract's WASM engine and language data still come from a CDN on first use — they're too large to inline, and the language data has to be fetched somehow.

License

MIT

Third-party licenses

The released main.js is a bundle, so it carries these with it:

Fetched on the first image conversion rather than redistributed here:

Apache-2.0 is compatible with this plugin's MIT license, and none of these ship a NOTICE file that would require further attribution. Nothing else is bundled: the zip reader and the PNG encoder are hand-rolled (src/zip.ts, src/png.ts) precisely so there is nothing more to carry.