show the confusion metrics as figure?

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mohd akmal masud
mohd akmal masud el 27 de Jul. de 2023
Comentada: Mrutyunjaya Hiremath el 27 de Jul. de 2023
Dear All,
I was evaluate the segmentation result deep learning method as below.
>> %Evaluate the prediction results against the ground truth.
metrics = evaluateSemanticSegmentation(pxdsResults,pxdsTest);
%Display the properties of the semanticSegmentationMetrics object.
metrics
%Display the classification accuracy, the intersection over union, and the boundary F-1 score for each class. These values are stored in the ClassMetrics property.
metrics.ClassMetrics
%Display the normalized confusion matrix that is stored in the NormalizedConfusionMatrix property.
metrics.ConfusionMatrix
Evaluating semantic segmentation results
----------------------------------------
* Selected metrics: global accuracy, class accuracy, IoU, weighted IoU, BF score.
* Processed 1 images.
* Finalizing... Done.
* Data set metrics:
GlobalAccuracy MeanAccuracy MeanIoU WeightedIoU MeanBFScore
______________ ____________ _______ ___________ ___________
0.99961 0.75114 0.74253 0.99923 0.9087
metrics =
semanticSegmentationMetrics with properties:
ConfusionMatrix: [2×2 table]
NormalizedConfusionMatrix: [2×2 table]
DataSetMetrics: [1×5 table]
ClassMetrics: [2×3 table]
ImageMetrics: [1×5 table]
ans =
2×3 table
Accuracy IoU MeanBFScore
________ _______ ___________
background 0.99997 0.99961 0.99867
tumor 0.50231 0.48546 0.81873
ans =
2×2 table
background tumor
__________ _____
background 5.8938e+05 15
tumor 215 217
Anyone know how to show the confusion metrics as figure?
  3 comentarios
mohd akmal masud
mohd akmal masud el 27 de Jul. de 2023
?
Chunru
Chunru el 27 de Jul. de 2023
???

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Respuesta aceptada

Mrutyunjaya Hiremath
Mrutyunjaya Hiremath el 27 de Jul. de 2023
After Evaluating semantic segmentation results, add the below code:
% Get the confusion matrix from the 'metrics' object
confusion_matrix = table2array(metrics.ConfusionMatrix);
classLabels = categorical({'background','tumor'})
cm = confusionchart(confusion_matrix, classLabels,...
'Title','Confusion Matrix',...
'ColumnSummary','column-normalized', ...
'RowSummary','row-normalized');
  2 comentarios
mohd akmal masud
mohd akmal masud el 27 de Jul. de 2023
Thank you sir. Its work!
Mrutyunjaya Hiremath
Mrutyunjaya Hiremath el 27 de Jul. de 2023
Most Welcome Sir.. :)

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