The Community Ads for 2016 have the nice feature that you can use an image that's double the size (i.e. 600×500px, instead of the standard 300×250px) and this will produce a better display in retina-like high-resolution devices that use a higher pixel density than normal.
One downside of this is that in the community ad threads on meta sites, each individual ad looks twice as big as will be displayed, and this (i) makes it harder to gauge how the ad will actually look when it goes live, and (ii) makes the ads clunkier and the thread harder to navigate around.
Fortunately, though, there is a nice markdown-like way to scale such images down. Consider, for example the advert
[![Detexify: automated LaTeX symbol recognition]] : https://i.stack.imgur.com/E9D64.png : http://detexify.kirelabs.org/classify.html
with its huge big image. As it turns out you can get a medium-sized version of this image by appending an
m to the file name, so that
[![Detexify: automated LaTeX symbol recognition]] : https://i.stack.imgur.com/E9D64m.png : http://detexify.kirelabs.org/classify.html
and give a much better sense of how the ad will display.
Before this can be used, though, it requires the parsing algorithm (the bit that grabs the images from the answers and serves them as ads) be adjusted so that the correct image will be displayed. Luckily this is a pretty easy feature request:
- Please adjust the parsing algorithm so that it will remove the
ms from any images that use it before displaying them as ads.
Alternatively, if this doesn't work, it would be nice to have some way to size down the images in the thread that doesn't impact the actual displayed size. As an example, the threads could use Mou-like syntax so that, say,
[![Detexify: automated LaTeX symbol recognition]] : https://i.stack.imgur.com/E9D64.png =300x250 : http://detexify.kirelabs.org/classify.html
also rendered at that width.
Straying a bit from the markdown route, it's always been possible to use explicit html image tags to set the displayed width. If the ad-processing algorithm can be updated to parse correctly posts of the form
[<img src="https://i.stack.imgur.com/E9D64.png" width="300" title="Detexify: automated LaTeX symbol recognition">] : http://detexify.kirelabs.org/classify.html
then that would also work.
Is either of these options a reasonable thing to implement?