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AKavun OP t1_irwurmu wrote

Reply to comment by Electronic-Art-2105 in [P] Making attribute classification on an image of a clothing by AKavun

Yeah, this is mostly similar to what I want to do but there is a difference.

In the tutorial, there are only binary attributes like if a celebrity is bald or not. But I want to do multi-value attributes like the color of the clothing which can take a lot of values, not just 1 or 0.

With this in mind, is it still multilabel classification

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Electronic-Art-2105 t1_irwzixb wrote

I see. In the tutorial, for each output, a 1-dimensional Dense layer with a sigmoid activation function is used, along with binary crossentropy as the loss function. You could exchange that by an n-dimensional Dense layer with softmax activation, along with categorical crossentropy. So the basic architecture can remain similar, you just have to adapt the outputs.

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AKavun OP t1_irx83tz wrote

>I see. In the tutorial, for each output, a 1-dimensional Dense layer with a sigmoid activation function is used, along with binary crossentropy as the loss function. You could exchange that by an n-dimensional Dense layer with softmax activation, along with categorical crossentropy. So the basic architecture can remain similar, you just have to adapt the outputs.

I will first learn what these things mean, then I will get back to you. Thank you for your guidance.

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