Restart Training in Semantic Segmentation of Multispectral Images Using Deep Learning
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Jacopo Biasetti
il 4 Mar 2023
Risposto: Parth Parikh
il 6 Mar 2023
Hi,
I went through the example "Semantic Segmentation of Multispectral Images Using Deep Learning." I'd like to restart training to improve the network I trained and, according to MATLAB's help, one needs to provide the net.Layers data to trainNetwork.
The command I used to restart training is
[net,info] = trainNetwork(dsTrain,net.Layers,options);
Launching the code I get the following error:
Error using trainNetwork
Invalid network.
Error in Deep_Learning_Testing (line 2357)
[net,info] = trainNetwork(dsTrain,net.Layers,options);
Caused by:
Layer 'Decoder-Section-1-DepthConcatenation': Unconnected input. Each layer input must be connected to the output of another layer.
Layer 'Decoder-Section-2-DepthConcatenation': Unconnected input. Each layer input must be connected to the output of another layer.
Layer 'Decoder-Section-3-DepthConcatenation': Unconnected input. Each layer input must be connected to the output of another layer.
Layer 'Decoder-Section-4-DepthConcatenation': Unconnected input. Each layer input must be connected to the output of another layer.
Any idea why this error pops up?
Thanks,
Jacopo
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Parth Parikh
il 6 Mar 2023
Hi,
Mostly the error is due to DAGNet object is being passed to trainedNetwork, the input should be a layergraph object.
Instead of this: [net,info] = trainNetwork(dsTrain,net.Layers,options);
It should be: [net,info] = trainNetwork(dsTrain,layerGraph(net),options);
If you would like to know more about the hyperspectral/multispectral features than take a look at Hyperspectral Imaging library:
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