Error using trainNetwork - Number of observations in X and Y disagree.
3 visualizzazioni (ultimi 30 giorni)
Mostra commenti meno recenti
I want to build a cnn where my input is 1000 images of size 20 x 20 x 110 and output is 1000 images of size 20 x 20.
Therefore I have
net = trainNetwork(TB_train(:,:,:,:),TS_train(:,:,:),Layers,options); and I get an error 'Number of observations in X and Y disagree'. I don't understand as both of my matrices have 1000 images.
My cnn has these layers:
Layers = [imageInputLayer([20 20 110],'Normalization','none') %,'Weights',W,'Bias',B)
convolution2dLayer(3,128,'Padding','same')%,'Weights',W,'Bias',B)
batchNormalizationLayer
reluLayer
convolution2dLayer(1,64,'Padding','same')%,'Weights',W,'Bias',B)
batchNormalizationLayer
reluLayer
convolution2dLayer(1,32,'Padding','same')%,'Weights',W,'Bias',B)
batchNormalizationLayer
reluLayer
convolution2dLayer(1,16,'Padding','same')%,'Weights',W,'Bias',B)
batchNormalizationLayer
reluLayer
convolution2dLayer(1,1,'Padding','same')%,'Weights',W,'Bias',B)
batchNormalizationLayer
reluLayer
regressionLayer];
0 Commenti
Risposte (2)
Divya Gaddipati
il 16 Giu 2020
Try using
net = trainNetwork(TB_train, TS_train, Layers, options);
0 Commenti
Joseph Williams
il 25 Feb 2021
Hello, I know this is an old question, but I am having a very similar difficulty, except with 3D images. I have 4000 (4 x 256 x 4) 3-channel images and want to create 4000 (4 x 256 x 4) 1-channel images.
I have a very similar architecture to yours and using analyzeNetwork(layers) shows that the layer before regression puts in the right size (for both our networks).
What was your solution to generate 1000 images of size 20 x 20? it may be my solution as well.
Thanks!
0 Commenti
Vedere anche
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!