![]() Please let me know if this is not enough info/not the right info. Here is the info about the python version and Topaz version that we have (we are using Topaz that is supported by SBGrid). Thanks in advance for any help!īeta Was this translation helpful? Give feedback. Has anyone else seen this happen before? Or know what might be going on? I happy to provide more information on what I have done/clarify anything I wrote above. Next, I looked at the precision recall curves and it appears like every particle has the exact same score (-4.535172, a screenshot of the PRCcurve Jupyter notebook below) It extracted 10864881 particles, however when I tried to apply a score threshold (I used -2), there was nothing above this threshold. This was pretty surprising, so I double checked my input files to confirm they were what I thought they were before extracting a random epoch from a model to see what it was picking (I choose modelc, epoch 10). ![]() For every epoch in each model, the AUPRC is exactly the same and also pretty low (1.57444e-05, also shown in screenshot below). I then trained 6 models with 10 epochs, each differing only by the number or particles/image (I tried n=10, 50, 100, 200, 300, 500). I have a dataset of 2480 micrographs, and have picked a total of 1009 particles (using EMAN2), then split out a test set with 220 particles (21.8% total picked particles). ![]() I am using Topaz as a standalone program and there seems to be something going on when training the models.
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