Turn a photo into illustration and painting styles

Convert your own photo into 7 illustration, anime and painting styles at once. Great for social-media avatars and profile pictures. Photos never leave your device.

Checking your environment…

The first run downloads an AI model (about 50 MB); later runs use the copy stored in your browser. Your files are never uploaded.

Settings

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Which one to use — lightweight vs. diffusion

There are two tools for turning photos into illustrations. Choose by your device and what you want. We suggest trying the lightweight one first and moving to the diffusion model if you want more.

Illustration & painting stylesThis page

Method
Lightweight GANs (AnimeGANv2 / fast-neural-style) that swap only the visual style
Requirements
Works without WebGPU, including phones and older laptops
First download
About 8MB per style, about 50MB for all 7
Time per image
Under a second with WebGPU, a few seconds on CPU
Style control
Pick from 7 fixed styles
Result
Composition, expression and facial features stay intact; rarely fails
Best for
Quick avatars, or devices with modest specs

AI illustration (diffusion)

Method
Diffusion model (LCM Dreamshaper v7) that repaints the photo from a prompt
Requirements
WebGPU required, 4GB+ of GPU memory (shared memory on integrated GPUs)
First download
About 2.1GB. Currently around 10 minutes due to our server's bandwidth
Time per image
20–40 seconds on an integrated GPU, a few seconds on a discrete GPU
Style control
5 presets plus free-form English prompts
Result
Richer, painterly results; higher strength drifts away from the original face
Best for
Gaming PCs or Apple Silicon Macs, and people who want fine control over the style

How to use

  1. 1

    Add a photo

    Drop the photo you want to stylize. Portraits suit the illustration styles; landscapes suit the painting styles.

  2. 2

    Choose styles

    “All” generates 7 variations at once. The first run downloads each style model (about 8 MB each).

  3. 3

    Save the ones you like

    The results appear side by side. Click a thumbnail to save it, or save everything as a ZIP.

The steps for converting into the seven styles, and how this compares with redrawing via an image-generation AI, are explained in the article “How to Turn Photos into Illustrations and Anime Art” on our blog.

The models and what they suit

The three illustration styles use AnimeGANv2 (MIT licence): face_paint for portraits, paprika for an anime-film look including backgrounds, and celeba_distill for a sketch-like result. The four painting styles use fast-neural-style (oil paint, mosaic, pointillism, abstract) and also suit landscapes and buildings.

Each model is about 8 MB; with WebGPU a style takes under a second, and a few seconds without it. There is no free-form prompting as with diffusion models, but results are instant and the composition and expression of the photo are preserved.

Frequently asked questions

Are my photos sent to a server?

No. The models are downloaded into your browser and the conversion runs on your device. Processing statistics used to fix bugs (device specs, error types and so on; never the photos themselves or their file names) are sent to this site's server. You can turn this off with the switch under “Help us improve the service” at the bottom of the page.

Which style works best for people?

“Illustration (portrait)” is the most suited to people. “Anime (Paprika)” works when you want the background painted too; “Sketch-like” suits simple avatars.

Does it exaggerate features like a caricature?

No. It keeps the composition and facial features and changes only the rendering style; it does not produce caricatures.

Can I specify a custom style?

The 7 styles are fixed. If you want to specify the style with a prompt, use “AI illustration (diffusion)”, which repaints the photo with a diffusion model. It needs WebGPU and a 2GB+ download, but gives far more freedom.

Help us improve the service

If a conversion fails, sending us the circumstances helps us track down the cause. Knowing which devices and formats fail most often, and how long processing takes, lets us revise the supported formats and fix the bugs behind them. If you don't mind, leaving this on is a real help.

What is sent

  • The tool you used and the settings you chose (output format, quality, etc.)
  • Your device specs (GPU, memory, core count)
  • The input format with a rough size
  • How many files succeeded or failed and how long it took
  • The error type and details when something fails

What is never sent

  • The files themselves and file names
  • Text, subtitles or prompts you add to a video
  • The text to be read aloud, voice descriptions, the pronunciation dictionary and saved voices
  • The text in PDFs, the text you rewrote or redacted, passwords, font names and the page ranges you enter
  • IP addresses

The data goes only to this site's own server, never to a third-party service.

Details sent by specific tools (counts, times, kinds and yes/no only)

In addition to “What is sent”, text to speech and the PDF tools send the following details.

Text to speech
The approximate number of characters and sentences, how many parts the text was generated in, and how long the AI model took to load.
PDF tools (all)
The page count range, whether editing is restricted, whether a permissions password was entered, and whether the PDF is signed or encrypted.
PDF text editing and redaction
The numbers of rewrites, deletions, white-outs and redactions, the number of rewritten characters by source (original font or fallback font, the latter as a range) and the fallback typeface, the kinds of reasons why lines cannot be edited, and the number of pages turned into images by redaction and the reasons.
PDF page operations and conversion between images and PDF
The numbers of inputs and outputs, of pages rotated, deleted, duplicated or moved, of images inserted as they are, converted, in HEIC format or with corrected orientation, and of pages rendered at a lower resolution (all as ranges), whether the original was updated in place or a new document was created, and whether the original protection was reapplied, form fields were written into the page and bookmarks were added back.
PDF compression
The numbers of inputs and outputs, of images downsized, not downsized and black-and-white, of downsized images whose transparency was also downsized, that stayed lossless or that were converted from CMYK to RGB, and how many times the file was compressed (all as ranges), the kinds of reasons images were not downsized, whether the target size was met and the kind of reason it was not met, the range of how much smaller the file got, whether the original protection was reapplied, and whether the original PDF was returned unchanged.
PDF cropping and page numbers
The numbers of inputs and outputs and of pages cropped, numbered or with their margins reduced (all as ranges), how the margins were set, how the pages to crop or number were chosen, the number format and position, the range of the starting number, that the original was updated in place, and whether the original protection was reapplied.

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