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

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Matpar
Matpar on 18 Feb 2020
Commented: Matpar on 21 Feb 2020
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

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Answers (1)

Raunak Gupta
Raunak Gupta on 21 Feb 2020
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.

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Matpar
Matpar on 21 Feb 2020
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!

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