First of all thanks for this amazing course. Hats off to Jeremy and his team for this awesome project!!
Now the issue:
I’m trying to do single class classification for skin lession diagnosis.
I have a csv which has two columns. The first is the name of the image. The second one the name of the lession.
When I do
data = ImageDataBunch.from_csv(path = tesisPath, folder=trainImagesFolderName, label_delim=',', ds_tfms=get_transforms(), size=64, bs=bs, csv_labels=trainingGroundTruthFileName, suffix=".jpg", valid_pct=0.2, header=0, fn_col=0, label_col=1).normalize(imagenet_stats)
and then I list my ds with
LabelList (5066 items)
Image (3, 64, 64),Image (3, 64, 64),Image (3, 64, 64),Image (3, 64, 64),Image (3, 64, 64)
Path: drive/My Drive/tesis/2019
But I want y to be a single category for each image!
Is there any way to change it? Or something I’m doing wrong?
As it is now I can’t use accurracy as a metric because it fails on the validation part.