Object 跟踪没有 openCV

Question

I am trying to build up an algorithm to detect some objects and track them over time. My input data is a tif multi-stack file, which I read as a np array. I apply a U-Net model to create a binary mask and then identify the coordinates of single objects using scipy .

Up to here everything kind of works but I just cannot get my head around the tracking. I have a dictionary where keys are the frame numbers and values are lists of tuples. Each tuple contain the coordinates of each object.

Now I have to link the objects together, which on paper seems pretty simple. I was hoping there was a function or a package to do so (ideally something similar to trackMate or M2track on ImageJ ), but I cannot find anything like that. I am considering writing my own nearest neighbor tool but I'd like to know whether there is a less painful way (and also, I would like to consider also more advanced metrics).

The other option I considered is using cv2 , but this would require converting the data in a format cv2 likes, which will significantly slow down the code. In addition, I would like to keep the data as close as possible to the original input, so no cv2 for me.

Answer 1

I solved it using trackpy. http://soft-matter.github.io/trackpy/v0.5.0/ trackpy properly reads multistack tiff files (OpenCv can't).