Is there a way to customize the model from object detection model_maker? e.g., get the loss and do some early stopping with the validation loss, save and load it. If it is not possible, is there a way to load the model as a tf/keras model to customize the training? Or maybe print the model summary to try to reproduce on tf/keras…
I followed the tutorial with efficiendet, Object Detection with TensorFlow Lite Model Maker, and it worked fine, besides the fact that the training is being done on CPU.