train data’ shape is (3, 224, 224)
label is total 5
label 1 = (0~5)
label 2 = (0~7)
label 3 = (0~3)
label 4 = (0~2)
label 5 = (0~8)
so i mapped
example))
image <-> [1, 7, 3, 1, 4]
and
model = models.resnet50(pretrained=False)
in_features = model.fc.in_features
model.fc = nn.Linear(in_features=in_features, out_features=5)
model.to(device)
print(model)
Is it right to design this?
I have no idea how to set the loss and model if there are multiple such labels using Resnet50.