Sorry for not responding to this!
The output needs to be normalized in the same way that varying read depth across samples needs to be normalized in some way. So for STAMP for instance I believe most plots show relative abundance. If you were to run a compositional-aware tool like ANCOM then you could round the abundance data to the nearest integer instead. I believe that STAMP automatically converts data to relative abundance for this purpose so in this case you wouldn’t need to do anything, but make sure to check that. The input file format is simply a tab-delimited file, so it’s very similar to the PICRUSt2 output - you may just need to change the headers to match the input file description in the STAMP manual.
Just to be clear - if you wanted to transform to relative abundance this would be for each sample separately, so it would be each column of the output table.
I would personally use custom R or Python code for visualization so I don’t have any other recommendations for specific software.
All the best,