Thank you for your inputs. The problem is basically an object detection type of model, its just using central points over the feature as the labels as opposed to the bounding box. In this case, wouldn’t a resnet model architecture be sufficient? Would either of you recommend moving forward in with configuring the bounding boxes or should I continue on the path I am taking and figure out my own collate function? I found a few examples where individuals had to modify the collate function in these two links (no label modification, and removing samples where points are outside of image after augmentation.). I’m assuming I need to modify the collate function to read in to the length of points in a given image (could be 0 to n). Any guidance on how to accomplish this might be helpful.
Thanks,
Tom