I’ve been playing around with the newly-released Squoosh, the spiritual successor to Jake’s SVGOMG. You can drag images into the browser window, and eyeball the changes that any optimisations might make.
On a project that Cassie is working on, it worked really well for optimising some JPEGs. But there were a few images that would require a bit more fine-grained control of the optimisations. Specifically, pictures with human faces in them.
I’ve written about this before. If there’s a human face in image, I open that image in a graphics editing tool like Photoshop, select everything but the face, and add a bit of blur. Because humans are hard-wired to focus on faces, we’ll notice any jaggy artifacts on a face, but we’re far less likely to notice jagginess in background imagery: walls, materials, clothing, etc.
On the face of it (hah!), a browser-based tool like Squoosh wouldn’t be able to optimise for faces, but then Cassie pointed out something really interesting…
When we were both at FFConf on Friday, there was a great talk by Eleanor Haproff on machine learning with JavaScript. It turns out there are plenty of smart toolkits out there, and one of them is facial recognition. So I wonder if it’s possible to build an in-browser tool with this workflow:
- Drag or upload an image into the browser window,
- A facial recognition algorithm finds any faces in the image,
- Those portions of the image remain crisp,
- The rest of the image gets a slight blur,
- Download the optimised image.
Maybe the selecting/blurring part would need canvas? I don’t know.
Anyway, I thought this was a brilliant bit of synthesis from Cassie, and now I’ve got two questions:
- Does this exist yet? And, if not,
- Does anyone want to try building it?