The outputs port of the Predict block takes the names of the output
layers of the network loaded. For example, if you specify
googlenet
for MATLAB function
, then the
output port of the Predict block is labeled
output. Based on the network loaded, the output of the
Predict block can represent predicted scores or responses.
Predicted scores or responses, returned as a
N-by-K array, where N is
the number of observations, and K is the number of classes.
If you enable Activations
for a network layer, the
Predict block creates a new output port with the name of the selected
network layer. This port outputs the activations from the selected network
layer.
The activations from the network layer is returned as a numeric array. The format
of output depends on the type of input data and the type of layer output.
For 2-D image output, activations is an
h-by-w-by-c-by-n
array, where h, w, and c are
the height, width, and number of channels for the output of the chosen layer,
respectively, and n is the number of images.
For a single time-step containing vector data, activations is a
c-by-n matrix, where n is
the number of sequences and c is the number of features in the
sequence.
For a single time-step containing 2-D image data, activations is a
h-by-w-by-c-by-n
array, where n is the number of sequences, h,
w, and c are the height, width, and the number
of channels of the images, respectively.