The tensors are nominally 4D. But you can add whatever additional annotations you want to them in the annotation() field. The tensor is just a block of memory and each layer interprets them however that layer does. So there is no limitation on what you do with it.
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Hi Davis,
As far as I see, dlib supports only 2-d input images in DNN architectures. What about 1-d or 3-d, 4-d signals/images?
The tensors are nominally 4D. But you can add whatever additional annotations you want to them in the annotation() field. The tensor is just a block of memory and each layer interprets them however that layer does. So there is no limitation on what you do with it.
We are very glad to see that if you can add a new example about this issue to dlib/example in the upcoming versions.