Color Table in BigDataViewer

fiji
bigdataviewer

#1

Is there a way to use a colortable / LUT in (default) BigDataViewer?
I would like to look at a volume containing labels where e.g. glasbey or inverted glasbey would be suitable.


#2

Can you use Paintera?

Update: Thinking about it, you are probably thinking about using BDV from within Fiji/ImageJ. In that case, Paintera is not an option, of course.


#3

Exactly. Would be very helpful to have this as a quick option to inspect a label volume without setting up a paintera project.


#4

Generally, you don’t need to set up a project (you can open datasets from within Paintera with Ctrl + O). If that is still too cumbersome, have you tried paintera-show-container (ships with the conda package). paintera-show-container opens all datasets in the specified container and I use that, for example, to look at snapshots of neural network training.


#5

Didn’t know about it, sounds very useful.
I will check it out.


#6

The plan is to merge it into the Paintera main class via command line options, rather than having somewhat redundant functionality. Currently, this is limited by


#7

There is no LUT stuff in the default BigDataViewer UI.
If you can just use Paintera to do the LUTs, that would be easiest.

If you use it through bigdataviewer-vistools, it should be relatively easy to do by hand.
You can do it now by using a Converter to convert your data to ARGBType with a LUT, then show the RandomAccessibleInterval<ARGBType>,
(It would be cleaner if you could give the source data of type T and a converter to ARGBType. This is how Sources are added in bdv-core. We can easily expose a BdvFunctions.show() function where you specify the converter.)


#8

My idea was to use this to quickly check labels. Paintera can be pretty slow to load, so I thought BDV
would be helpful to do this with less friction.
Anyway, paintera will still be much faster than me trying to mess with any java…

Or is there a way to use pyimagej to call bigdataviewer-vistools from python?


#9

There is currently a bug in the jgo Python bindings that ignores the cache. This could be the cause for the slow start-up. I will let you know when this is fixed. Hopefully, Paintera will start-up faster, then.


#10

@constantinpape https://github.com/scijava/jgo/pull/33 will hopefully speed up start-up time of pyjgo projects. There probably is room for improvement in paintera itself, though.


#11

@constantinpape I released a new version of jgo yersteday and it is available on conda now for improved start-up times:

 ▲ ~ time paintera -u -- --version
[JavaFX Application Thread] INFO org.janelia.saalfeldlab.paintera.PainteraCommandLineArgs - Paintera version: 0.9.0
paintera -u -- --version  7.03s user 0.27s system 327% cpu 2.235 total

 ▲ ~ time paintera -- --version
[JavaFX Application Thread] INFO org.janelia.saalfeldlab.paintera.PainteraCommandLineArgs - Paintera version: 0.9.0
paintera -- --version  0.75s user 0.07s system 168% cpu 0.490 total

To update, run

conda update -c conda-forge jgo

Conda should find version 0.3.0.


#12

Thanks! I updated jgo and indeed start up seems to be faster,