How to Resize images stored in matlab.io.​datastore.​ImageDatas​tore to [224 224 3]

Hello I'm new in using pretrained networks in MATLAB for Object Detection and I was following a guide in Youtube which uses YOLO for detection. In this guide, it also used the resnet50 pretrained network which has an input layer that expects images of size (224x224x3).

Below is the code:

trainData1 = Data;

%%% Create resnet50 pretrained network

netWidth = 16;

layers = [

imageInputLayer([224 224 3], 'Name', 'input')

convolution2dLayer(3, netWidth, 'Padding','same', 'Name', 'convInp')

batchNormalizationLayer('Name', 'BNInp')

reluLayer('Name', 'reluInp')

convolutionalUnit(netWidth, 1, 'S1U1')

additionLayer(2, 'Name', 'add11')

reluLayer('Name', 'relu11')

convolutionalUnit(netWidth, 1, 'S1U2')

additionLayer(2, 'Name', 'add12')

reluLayer('Name', 'relu12')

convolutionalUnit(2*netWidth, 2, 'S2U1')

additionLayer(2, 'Name', 'add21')

reluLayer('Name', 'relu21')

convolutionalUnit(2*netWidth , 1, 'S2U2')

additionLayer(2, 'Name', 'add22')

reluLayer('Name', 'relu22')

convolutionalUnit(4*netWidth, 2, 'S3U1')

additionLayer(2, 'Name', 'add31')

reluLayer('Name', 'relu31')

convolutionalUnit(4*netWidth, 1, 'S3U2')

additionLayer(2, 'Name', 'add32')

reluLayer('Name', 'relu32')

averagePooling2dLayer(8, 'Name', 'globalPool')

fullyConnectedLayer(4, 'Name', 'fcFinal')

softmaxLayer('Name', 'softmax')

classificationLayer('Name', 'classoutput')

];

lgraph = layerGraph(layers);

lgraph = connectLayers(lgraph, 'reluInp', 'add11/in2');

lgraph = connectLayers(lgraph, 'relu11', 'add12/in2');

skip1 = [

convolution2dLayer(1,2*netWidth, 'Stride', 2, 'Name', 'skipConv1')

batchNormalizationLayer('Name', 'skipBN1')];

lgraph = addLayers(lgraph, skip1);

lgraph = connectLayers(lgraph, 'relu12', 'skipConv1');

lgraph = connectLayers(lgraph, 'skipBN1', 'add21/in2');

lgraph = connectLayers(lgraph, 'relu21', 'add22/in2');

skip2 = [

convolution2dLayer(1, 4*netWidth, 'Stride',2, 'Name', 'skipConv2')

batchNormalizationLayer('Name','skipBN2')];

lgraph = addLayers(lgraph, skip2);

lgraph = connectLayers(lgraph, 'relu22', 'skipConv2');

lgraph = connectLayers(lgraph, 'skipBN2', 'add31/in2');

%add last identity connection and plot the final layer graph

lgraph = connectLayers(lgraph, 'relu31', 'add32/in2');

%training options

options = trainingOptions("sgdm", ...

'MiniBatchSize', 128, ...

'MaxEpochs', 1, ...

'InitialLearnRate',1e-4);

% network training

[trainedNet1, traininfo] = trainNetwork(trainData1, lgraph, options);

And the output error is this:

% network training

[trainedNet1, traininfo] = trainNetwork(trainData1, lgraph, options);

Error using trainNetwork

The training images are of size 3024×4032×3 but the input layer expects images of size 224×224×3.

My workspace is this:

Thank You. Hope You Can Help.

Answer 1

[Ganesh Gudipati]

Hi,

The resolution of input image is different from the expected resolution.

Resizing the images will resolve your issue. Please refer to Resize image documentation.

I hope this resolves your issue.