Turn photos into illustrations with AI (diffusion model)

Runs a Stable Diffusion–based diffusion model inside your browser to redraw photos in anime, watercolour, oil and other styles. More flexible than “Illustration & painting styles”, with prompt control. Photos never leave your device.

This tool downloads an AI model (about 2100 MB) on the first run. Because of current server-side bandwidth limits, the download can take around 10 minutes; later runs use the copy stored in your browser. WebGPU is required.

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 styles

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)This page

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 one photo. The central square (512×512) is used, so photos with the face in the middle work best.

  2. 2

    Choose a style and strength

    Pick anime, watercolour, oil, comic or pixel art, or write your own English prompt. Higher strength gives a stronger style; lower keeps more of the original face.

  3. 3

    Generate and pick

    The requested number of images is generated side by side. Save the ones you like; running again with the same settings gives different results.

How it works and what to know first

LCM Dreamshaper v7 (MIT licence) converted to fp16 ONNX runs on onnxruntime-web with WebGPU. The photo is encoded to a latent, noise is added, and the model redraws it in 4 steps following the prompt (img2img). Strength is the amount of noise; around 0.5 changes the style while keeping the person recognisable.

The models total 2.1 GB, so the first download takes a while. Because of current server-side bandwidth (the primary proxy’s uplink) it can take around 10 minutes; this will improve with an infrastructure move. Later runs use the copy stored in your browser. WebGPU and about 4 GB of GPU memory (shared memory on integrated GPUs) are required; each image takes 20–40 s on an integrated GPU or a few seconds on a discrete one.

Frequently asked questions

Are my photos sent to a server?

No. The models are downloaded into your browser and generation runs on your device’s GPU.

The download is slow

Server-side bandwidth currently caps at about 4–5 MB/s, so 2.1 GB takes around 10 minutes. A bandwidth upgrade is planned. The download happens once; later runs use the stored copy.

The face no longer looks like the person

Diffusion img2img drifts further from the photo as strength rises. Lower it to 0.4–0.5 to keep the likeness. If facial details break up, run “Face restoration” on the result.

How is this different from “Illustration & painting styles”?

That tool uses lightweight GANs that keep the composition and only change the rendering (seconds, 8 MB models). This one redraws the image with a diffusion model, so it is more flexible and prompt-driven, but the model is large and WebGPU is required.

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, and the error type and details when something fails.

What is never sent

The files themselves, file names, text, subtitles or prompts you add to a video, and IP addresses. The data goes only to this site's own server, never to a third-party service.

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