object classes classification layer must be equal in the input trainingData plus 1 for the "Background" class

Hi All Matlab folk,

I am trying to manually code the classes for my network can someone assist me please?

I am trying to gain a better understanding of this error! Can some one help me understand this error in an easier way please?

I changed the input layer details in the DAG network and still this it is arguing!

My Input layer:

imageInputLayer([32 32 3],"Mean",[],"Normalization","zerocenter", "Name","imageinput")

My ERROR:

The number object classes in the network classification layer must be equal to the number of classes defined in the input
trainingData plus 1 for the "Background" class

Answer 1

[Raunak Gupta]

Hi,

As per the example mentioned in trainRCNNObjectDetector the number of classes to be mentioned for training must be (objectClasses + 1) .The objectClasses should also be mentioned in a cell array which can represent the name of those classes. The fullyConnectedLayer will be having outputSize as (objectClasses + 1).You may look into the above-mentioned example for clarity about implementing the same.

[Matpar]

Hey Raunak Gupta,

that was not the issue I solve that aspect of it the bounding box is not drawing and that is challenging me at the moment!

any suggesstions on bonding boxes, systax or a workable format?

let me know pal please!