Is it possible to bias the training of an object detection model towards classification in tensorflow ModelMaker?

Question

I'm using Tensorflow 2 Model Maker to perform transfer training of EfficientDet-Lite (ultimately to run on a Coral EdgeTPU) and I care much more about the classification output and much less about the precision of the bounding boxes. Is there a way to modify some training parameters to improve the accuracy of the classes at the expense of the accuracy of the bounding boxes? Or does this not make sense?

Answer 1

Unfortunately, TensorFlow 2 Model Maker doesn't support such customization at this moment.

If you want to do so, you can bypass Model Maker and directly use AutoML repo. The technical detail is to adjust weights for different losses by adding loss_weights in compile() function.