Hi Johannes,
I've seen this error before. I have seen a similar one but in parts of the code that are parallelized. I am not sure why this error occurs at this point of the tracking pipeline. It could be that the computer has a lot of memory in use from previous processes and that at this point it has not been cleaned yet.
I can recommend two things:
1.- Monitor the RAM memory while tracking to see if the problem is there.
2.- Try to lower the number of threads used during parallel computations using the advanced parameters:
NUMBER_OF_JOBS_FOR_SEGMENTATION
NUMBER_OF_JOBS_FOR_SETTING_ID_IMAGES
3.- If the size of your animals in pixels is above 500 pxs/animal, try to use the resolution reduction parameter to downsample the video. This will generate smaller lists of pixels and smaller segmentation images and identification images, using less RAM. If you stay in the range of ~150 pxs/animal, the accuracy of the tracking should still be high.
I hope this helps,
We will explore ways of monitoring the resources and fixing this issues in the next versions.
It would be great if you could report this error in a Gitlab issue, enphasizing the specs of the computer, OS,
idtracker.ai version, length of the video, number of animals, size of animals, the values of the advance parameters.
Thanks for reporting this problem
Francisco Romero-Ferrero
PhD student at Collective Behaviour Lab, Champalimaud Research
Av. de Brasilia, Doca de Pedrouços
1400-038 Lisboa, Portugal