I need to segment my input image using unet segmentation
Show older comments
where inp is my input image
inp=b
DatasetPath=fullfile('C:\Users\Desktop\to');
imds=imageDatastore(DatasetPath, 'IncludeSubfolders', true,...
'LabelSource','foldernames','fileextension',{'.dcm'});
labelDir = fullfile(DatasetPath,'testImages');
I = readimage(imds,1);
I = histeq(I);
imshow(I)
classes = [
"MALIGNANT","BENIGN"
];
labelIDs=[255 0]
inputlayer = imageInputLayer([512 512 1],'Name','inp')
numFilters = 64;
numLayers = 16;
layers = [ ...
imageInputLayer([512 512 1])
convolution2dLayer(5,20)
batchNormalizationLayer
reluLayer
maxPooling2dLayer(2,'Stride',2)
convolution2dLayer(5,20)
batchNormalizationLayer
reluLayer
maxPooling2dLayer(2,'Stride',2)
transposedConv2dLayer(4,numFilters,'Stride',2,'Cropping',1);
convolution2dLayer(5,20)
batchNormalizationLayer
reluLayer
transposedConv2dLayer(4,numFilters,'Stride',2,'Cropping',1);
convolution2dLayer(5,20)
batchNormalizationLayer
reluLayer
convolution2dLayer(5,20)
fullyConnectedLayer(4)
softmaxLayer
pixelClassificationLayer
]
% pxds = pixelLabelDatastore(labelDir,classes,labelIDs);
options = trainingOptions('sgdm', ...
'InitialLearnRate',0.01, ...
'MaxEpochs',1, ...
'Shuffle','every-epoch', ...
'ValidationFrequency',30, ...
'Verbose',false);
net=trainNetwork(imds,layers,options);
res = activations(net,inp,net.Layers(numLayers-1).Name,'OutputAs','channels');
I = read(imds);
% C = read(pxds)
C = semanticseg(I, net);
% Overlay pixel label data on the image and display.
B = labeloverlay(I, C);
figure(12)
imshow(B)
I got error @
Error using trainNetwork
Not enough input arguments.
Error in
net=trainNetwork(imds,layers,options);I
2 Comments
SARAH LONER
on 27 Nov 2019
Manjunath R V
on 21 Apr 2021
have u got solution for the above query sarah if so please share it
Accepted Answer
More Answers (0)
Categories
Find more on Deep Learning Toolbox in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!