MATLAB 的UNET代码
时间: 2023-07-02 17:03:30 浏览: 53
下面是一个简单的 MATLAB UNet 代码示例:
```matlab
%% 加载数据
data = load('image_data.mat');
inputData = data.inputData;
targetData = data.targetData;
%% 定义网络架构
inputSize = size(inputData);
numClasses = 2;
layers = [
imageInputLayer(inputSize)
convolution2dLayer(3,16,'Padding','same')
batchNormalizationLayer
reluLayer
maxPooling2dLayer(2,'Stride',2)
convolution2dLayer(3,32,'Padding','same')
batchNormalizationLayer
reluLayer
maxPooling2dLayer(2,'Stride',2)
convolution2dLayer(3,64,'Padding','same')
batchNormalizationLayer
reluLayer
transposedConv2dLayer(2,64,'Stride',2,'Cropping','same')
concatenationLayer(3)
convolution2dLayer(3,32,'Padding','same')
batchNormalizationLayer
reluLayer
transposedConv2dLayer(2,32,'Stride',2,'Cropping','same')
concatenationLayer(3)
convolution2dLayer(3,16,'Padding','same')
batchNormalizationLayer
reluLayer
convolution2dLayer(1,numClasses)
softmaxLayer
pixelClassificationLayer
];
%% 训练网络
options = trainingOptions('adam', ...
'InitialLearnRate',1e-3, ...
'MaxEpochs',50, ...
'MiniBatchSize',64, ...
'Shuffle','every-epoch', ...
'ValidationData',{inputData,targetData}, ...
'ValidationFrequency',10, ...
'Plots','training-progress');
net = trainNetwork(inputData,targetData,layers,options);
```
这个代码定义了一个简单的 UNet 架构,包括卷积层、批量归一化层、ReLU 激活函数、最大池化层、转置卷积层、拼接层、softmax 层和像素分类层。然后使用 `trainNetwork` 函数训练网络,并使用一些选项来配置训练过程,例如学习率、最大 epochs 数量、mini-batch 大小等。