I manage to train de ResNet18 as suggested. I get 2% classification error or so. I then try to use the cleaner
cleaner = ImageClassifierCleaner(learn)
and retrieve the indices of the images to be moved/deleled.
I then run
for idx in cleaner.delete(): cleaner.fns[idx].unlink()
for idx, cat in cleaner.change(): shutil.move(str(cleaner.fns[idx]), path/cat)
I then rerun
bears = bears.new(
dls = bears.dataloaders(path)
learn = cnn_learner(dls, resnet18, metrics=error_rate)
And when inspecting the highest losses I find that the images I deleted/reclassified are still in the dataset. So my model does not improve. How can I properly move/delete the images in the dataset ? The book just says ‘retrain the model until and see if your accuracy improves’ but I did not succeed.