Hope you’re doing well. I’m working on a project using point annotations to train an object classifier over cellular detections in QuPath. We have quite a large amount of slides, so we’ve built a Docker container to perform detections on our cluster using groovy scripts.
There are some caveats we’ve run into using the Dockerized QuPath. For example – so far, to our knowledge, we haven’t been able to get a “Project” loaded in; however, we’ve been able to work around this by having the docker execute the groovy script independently for each slide and outputting a per-slide GeoJSON file of cellular detections.
After importing the cellular detection objects and point annotations (labels), the final step we hope to achieve is to train an ANN object classifier to classify the cells according to their corresponding point annotation labels. We’ve been able to achieve this in the QuPath GUI with a small test set of slides, but this likely wont scale to the entire cohort of slides we have.
I wanted to ask if it’s possible to train an ANN object classifier in QuPath using Groovy commands / if there’s a way you think we could train an object classifier given the no-project constraint we’re facing? I was thinking I could maybe concatenate all slide-level GeoJSONS into a single file (likewise with the point annotation GeoJSONs), load these two files in as detections and annotations into qupath, and potentially pass these as arguments into a training function, depending on how the ObjectClassification function is set up.
Any guidance or ideas would be tremendously appreciated!
Thanks for your help as always,