object classes classification layer must be equal in the input trainingData plus 1 for the "Background" class
1 回表示 (過去 30 日間)
古いコメントを表示
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
0 件のコメント
回答 (1 件)
Raunak Gupta
2020 年 2 月 21 日
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.
参考
カテゴリ
Help Center および File Exchange で Image Data Workflows についてさらに検索
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!