Hello friends!
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.
For example
|image, label
ISIC_0000000, NV
ISIC_0000001, NV
ISIC_0000002, MEL
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
data.valid_ds
I get
LabelList (5066 items)
x: ImageList
Image (3, 64, 64),Image (3, 64, 64),Image (3, 64, 64),Image (3, 64, 64),Image (3, 64, 64)
y: MultiCategoryList
NV,BKL,NV,NV,NV
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.