Open jacopoabramo opened 2 months ago
I typically do the same, albeit by plotting the number of features found for each minmass
and then setting a threshold.
Jupyter widgets can also offer a convenient way to interactively play with each parameter and see the results.
I'm currently using trackpy for tracking particles over 3D. For various reasons I'm not using 3D feature finding but instead I'm scanning a volume over
z
and finding centroids in 2D. Then I do some other processing to obtain the estimation overz
with a different method. I cannot unfortunately go into details on this matter at this time, but for the purpose of my question is not relevant.I would like to perform an initial estimation of the minimum value of
minmass
that I would need to identify atarget
number of particles in my images. At this time I'm doing something on these lines:Helper function:
Actual estimation:
I understand that
trackpy
currently offers a variety of other APIs that I could use for a (possibly) more accurate and more efficient approach to this problem, i.e. using somehowgrey_dilation
together with other APIs to obtain an initial estimation.Currently I'm content with this approach but any insight in other possibilities would be appreciated.