I’m probably missing something simple here. I’d like to do batch prediction on a dataset, but don’t want to recreate the learn
object or use load_learner
every time I switch the test dataset. For example, I have small test datasets continually coming in that I want to do batch predictions on in real-time, so don’t want to waste time reloading the model before each run.
So is there a way I can just add the test dataset to the learner after the fact and then use get_preds
on it?
Also, I was comparing the speeds of predict
and pred_batch
, and it seems like pred_batch
isn’t any faster per input image. Is that expected behavior? And should I expect get_preds
to be faster per image than a loop of pred_batch
or predict
?
Here’s the similar speed I’ve observed with predict
and pred_batch
: