I'm not comfortable calling out flaws without being an absolute expert on the topic. It's not strictly true that it doesn't [play nice with other languages](http://ilovesymposia.com/2014/02/26/fiji-jython/), nor would I call their ImagePlus object a sandbox any more than numpy arrays are a sandbox. All Java functions are available to you, since it's very easy to extract the raw arrays and convert them back to images afterwards. In fact, Fiji has a Weka segmentation plugin, so that's already not a great example. I'm pretty sure it would not be hard to bake a Weka image classifier into their GUI, either.

I'm not sure about the full extent of Fiji plugins, but "not very difficult to port" is certainly not true of some of their 3D registration plugins, or multi-dimensional tiling, both of which I have had use for.

Generally, I think Fiji is incredibly powerful, more developer-friendly than we give it credit for, and we should show some deference here, while, I agree, also pointing out our advantages. There's certainly quite a few reasons why I'm a scikit-image dev and not a Fiji dev, but I want to avoid making sweeping statements such as "doesn't play nice with others", which can be easily disproven in at least some contexts.