Hello, I’m curious about some aspects of submodel sizes, and would appreciate any insight. When I run clusterodm with 3000 images, 3 nodes(each having the same max-images setting) and a split of 1000, my submodels have widely varying sizes. While I know the submodel size is due in part to the overlap, I’m still getting bizarre results, such as submodel0 1500 images submodel1 700 images submodel2 1200 images. I’ve been hesitant to manually choose the images for each submodels, mainly because I don’t know the optimal way to split my rectangular flight area, but I’m starting to think it’s the only way to get similarly sized submodels. I’m fine with some variation in size but having one submodel be twice as large as another really increases my processing times.
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