Hi, I’ve been working with CPA2.0 the past few weeks to classify colonies in competition experiments as belonging to one species or another. It has been working fairly well, but I was hoping to generate some sort of measure of confidence about the scoring. Since I have so many images, I’d really like to prioritize manual verification to images with lots of borderline cases rather than images with generally high confidence, but a few outliers.
If I could get at the scores for each class for each object, then I could know whether an object has only one high scoring class (wouldn’t need manual verification), or if it scored very closely in two classes (might be worth verifying if time permits).
Similar topics seemed to refer to CPA1, is there a better way to do this in CPA2.0? Thanks for all your hard work!