# Running an AI image upscaler & sharpener 100% in the browser (TensorFlow.js)

> Source: <https://dev.to/zephyrtran/running-an-ai-image-upscaler-sharpener-100-in-the-browser-tensorflowjs-47b8>
> Published: 2026-08-11 03:47:29+00:00

I wanted to sharpen and upscale images **without uploading them to some server**. It turns out you can run the whole ML model right in the browser — the image never leaves the device. Here's what I learned shipping it as two free tools.

The core is one call: `new Upscaler({ model })`

, then `await upscaler.upscale(img, { patchSize: 64, padding: 4, progress })`

. The `patchSize`

option is the important one — more on that below.

**Memory.** Running 4× on a large image tries to allocate a huge tensor and the tab dies. The fix is `patchSize`

— process the image in tiles and stitch them back, so memory stays bounded regardless of input size.

**Model choice matters more than I expected.** I benchmarked three ESRGAN variants on the same image: `slim`

is fast (~2.5s on a small image) but slightly soft, `medium`

had visible tiling artifacts (rejected), and `thick`

was clearly the sharpest but ~3× slower. So I default to `slim`

and offer `thick`

as a "max detail" mode.

**Lightweight upscalers smooth the image.** ESRGAN-slim enlarges cleanly but the result can look soft. A small unsharp-mask pass afterward restores the bite without an obvious "sharpened" halo.

**Sharpen vs upscale are different jobs.** To make a sharpener that keeps the original size, I run the same model then draw the result back down to native dimensions — the AI detail survives the downscale, so you get a clearer image at the same size. That became the [AI photo sharpener](https://snapvi.app/sharpen-image); the enlarge-2×/4× version is the [AI image upscaler](https://snapvi.app/image-upscaler).

The trade-off is a one-time model download and slower runs on weak phones, which I gate with size caps and a fast/max toggle.

Happy to answer anything about the TF.js side — what would you run in-browser next?