Yes, the production images are of varying size and resolution. Some of these images are thumbnail sized and some are much larger and higher resolution. They are resized to 299, however, just like the training environment.
Maybe train a small image and large image model?
I Will caveat that the problem I’m attempting to tackle is complex, so I guess I’m more or less wondering, do I continue to re-train the model with the data it mis-labeled vs transfer learn my previous model vs use a multi-stage approach (i.e instead of deciding between 8 classes with one inference, use 3 separate models in an if-then approach)