I am building an image classifier for a dataset where data is divided into two folder one with labeled training data and another with unlabeled testing data. I couldn’t find any information on how to feed this testing data to my learner and make predictions with it. Should I feed the testing data to the dataloader or give it later on to the learner? How do I get the predictions for my testing data? Help appreciated!
test_items = get_image_files(test_folder_path)
test_dl = dls.test_dl(test_items)
preds,_ = learn.get_preds(dl=test_dl)