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Use the community node @bitovi/n8n-nodes-pdf-to-png to render a PDF into one PNG binary item per page. Put the PDF in an n8n binary property (normally data), configure the page range and scale, and connect the node’s output to storage or the next processing step. n8n’s built-in PDF integration extracts text and metadata; it is not documented as a page-image renderer.
What n8n can and cannot do natively
n8n handles documents and images as binary data attached to workflow items. The documented file tools include Convert to File, Extract From File, and Read/Write Files from Disk, so a PDF can move through a workflow without first becoming text. See n8n’s file and image documentation.
Rendering is a different operation from extraction. The Extract From File integration lists “Extract From PDF” for PDF content and metadata. It does not describe rasterizing every page. If your output must look like the original page—tables, drawings, scanned text, fonts and layout—you need a PDF renderer.
The directly documented n8n route is the community package @bitovi/n8n-nodes-pdf-to-png. Its project documentation says the node accepts a PDF from a binary property, creates one PNG image per page, and emits one item for each page.
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Requirements and compatibility
- n8n with community packages enabled.
- A PDF available as binary data in an incoming item.
- Permission to install and run a third-party node.
- For the project’s stated compatibility range: n8n 1.0.0 or newer and Node.js 18.10 or newer. The README reports testing with n8n 2.9.4; these are project-reported values, not a guarantee for every current deployment.
The node’s README says it uses pdf-to-png-converter, pdf.js and @napi-rs/canvas. Community-node policy, package maintenance and supported runtimes can change, so check the current project page before installing in production.
Install the PDF-to-PNG node
- Open n8n’s settings and find the community-node or community-package management screen. The exact menu label depends on your n8n release.
- Enable community packages if your deployment policy allows them.
- Install
@bitovi/n8n-nodes-pdf-to-pngby its package name. - Restart n8n if your installation requires a restart before newly installed nodes appear.
- Create a test workflow and confirm that the PDF to PNG node is available in the node picker.
Cloud and self-hosted n8n deployments have different controls over packages, binaries and filesystem access. n8n documents both deployment approaches on its documentation home page; verify that your administrator permits community nodes before designing a production workflow.
Build the workflow
1. Get the PDF into binary data
Use an HTTP Request, a trigger that supplies an attachment, Read/Write Files from Disk, or another file-producing node. The important result is an item with a binary property containing the PDF. Most n8n file examples use the property name data.
Inspect the incoming item in the execution data panel. Under Binary, confirm that the property exists and that its MIME type is a PDF, normally application/pdf. If the file is base64 text in JSON rather than binary data, convert it with a file-handling node before the renderer.
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- Add the Bitovi PDF-to-PNG node after the node that supplies the PDF.
- Set Input Binary Property to the property holding the PDF, usually
data. - Leave Page Range blank to render every page, or enter the range/list syntax shown by the node’s current UI for a subset.
- Set Scale. The project documents a default of
2.0and a range from0.5to5.0. Higher values produce larger, more detailed images and consume more memory and storage. - Choose the output binary property, normally
data. Use another name if you need to preserve the original PDF on the same item. - Execute the node with a small PDF first.
According to the project documentation, each output item contains the page number, page dimensions, total page count, source filename and PNG binary data. The result is therefore naturally suited to an Item Lists-style fan-out: one downstream execution branch can process, upload or classify each page.
3. Store or process the images
Connect the output to the next operation that accepts binary data: an object-storage upload, an email attachment, OCR, image analysis or a database record containing a file reference. If you write files locally, use n8n’s supported file nodes and confirm that the process has permission to write to the target directory. In hosted environments, local disk may be ephemeral or unavailable; n8n documents external binary-data storage considerations here: external storage for binary data.
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Use the page number supplied by the node when constructing names such as invoice-001.png. Do not rely on item position alone if you later filter or merge pages.
Page ranges, scale and output choices
| Setting | Documented behavior | Practical decision |
|---|---|---|
| Input binary property | Defaults to data |
Match the actual incoming PDF property. |
| Page range | Blank means all pages; a range or list can select pages | Render only pages needed for previews or targeted OCR. |
| Scale | Default 2.0; documented range 0.5–5.0 | Start at 2.0, then lower it for thumbnails or raise it for small print. |
| Output binary property | Defaults to data |
Use a different name when retaining the source PDF. |
| Output shape | One PNG binary item per page | Fan out naturally to per-page processing and storage. |
PNG is lossless and appropriate for text, diagrams and screenshots. The documented node route outputs PNG; if a downstream service requires JPEG or WebP, add a separate image-conversion step after rendering rather than assuming the PDF node changes formats.
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Common problems and fixes
The node does not appear
Community packages may be disabled, installation may have failed, or a restart may be required. Recheck the package name, n8n’s community-node policy and the server logs. In a managed workspace, ask the administrator whether third-party nodes are allowed.
“Binary property not found”
The configured property does not match the incoming item. Open the execution data, inspect the Binary section and copy the exact property name into the node. If the PDF arrived as JSON/base64, convert it to binary first.
The workflow outputs text but no images
You probably used Extract From File’s PDF operation. That operation is for content and metadata extraction, not documented page rasterization. Replace it with the PDF-to-PNG community node when the required output is a visual page image.
Only some pages are produced
Check Page Range for an accidental subset or malformed range. Remove the value to request all pages, then test again with a short document. Also verify that a downstream filter is not discarding items after rendering.
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Large PDFs consume too much memory
Rendering every page at scale 5.0 creates large in-memory PNGs. Lower the scale, process a page range in batches, and upload or delete each page promptly. Keep binary-data storage settings appropriate for your deployment instead of retaining every intermediate item indefinitely.
Fonts, images or scanned pages look wrong
PDF rendering depends on the renderer and the document’s embedded resources. Confirm that the issue occurs in the conversion node itself by opening its output before downstream processing. Try a different scale and a second sample PDF. If the problem is specific to a font or malformed PDF, preserve the original and test with a current package release before changing the workflow.
It works locally but not after deployment
Compare n8n and Node.js versions, package installation state, memory limits and binary-data configuration. The project’s compatibility statements are not a promise for every hosting environment. Reinstall the package in the target environment and check its current README for changed requirements.
Performance and reliability planning
Estimate the workload
Output count equals the number of rendered pages, so a 200-page document creates 200 binary items. Image size rises with page dimensions, embedded graphics and scale. Measure a representative PDF at your chosen scale before setting queue or concurrency limits.
Preserve traceability
Carry the source filename, document ID and page number into your storage key or database row. Keep the original PDF until the page set has been validated. If a later node fails, you can retry only the missing page range instead of rendering the entire document again.
Choose storage deliberately
Local files are convenient on a self-hosted instance with a persistent volume. Cloud or horizontally scaled workers generally need the binary-storage approach supported by that deployment. n8n’s external-storage documentation explains the configuration concepts, but your hosting plan determines which option is available.
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Handle retries safely
Use deterministic names containing a document identifier and zero-padded page number. Before writing, decide whether an existing object should be overwritten, skipped or versioned. This prevents a retry from producing ambiguous duplicate pages.
When an external renderer is appropriate
A self-hosted workflow can also call a system PDF renderer and read the resulting files back into n8n. However, exact command names, node availability and cloud compatibility depend on the operating system and deployment; the available n8n documentation does not establish a single supported command-node recipe. Choose this route only when you control the host, can install and patch the renderer, and have verified its security and filesystem behavior.
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The community node is usually simpler when installing a package is permitted. An external renderer may be preferable when your organization standardizes on system packages, needs a particular PDF engine, or prohibits community nodes. Compare the routes on package policy, page-range control, scale/DPI control, output shape, runtime limits and maintenance responsibility.
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For the complete parameter list, see the ScreenshotNeo API documentation. This cURL request returns a WebP image for the target URL:
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open("shot.webp", "wb").write(r.content)Equivalent Node.js:
const q = new URLSearchParams({ access_key: 'YOUR_API_KEY', url: 'https://stripe.com' });
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FAQ
Does n8n have a built-in PDF page-to-image node?
The documented built-in PDF operation is extraction of content and metadata. The page-rendering option documented for this workflow is the Bitovi community node.
Can I output one item per PDF page?
Yes. The Bitovi node documents one PNG image item for each rendered page, including page metadata and binary data.
Can I render only selected pages?
Yes. Leave Page Range blank for all pages or configure a range/list in the node’s current interface.
What should I do if community nodes are prohibited?
Use an approved external rendering service or a self-hosted renderer that your platform team supports. Validate its commands, filesystem access and security requirements for your exact environment before putting it in production.
Frequently Asked Questions
Will the node preserve selectable PDF text?
No. Its output is raster PNG data. Keep the original PDF or run a separate text-extraction step when searchable text is also required.
Is scale the same as a guaranteed DPI setting?
The project documents a scale value from 0.5 to 5.0, not a universal DPI guarantee. Treat the resulting pixel dimensions as the practical resolution control.
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