--- a
+++ b/testingCode.m
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+% Testing on New Data (capsule endoscopy images)
+% Developer: Tonmoy Ghosh (tghosh@crimson.ua.edu)
+
+clear; close all; clc;
+% load trained network
+data = load('CEtrainedSegNet.mat');
+net = data.net;
+labelIDs = PixelLabelIDs();
+cmap = CEColorMap;
+classes = [
+    "Bleeding"
+    "Non_Bleeding"
+    "Background"
+    ];
+
+
+
+imdsTest = imageDatastore('testImage.png'); % image location and name
+pxdsTest = pixelLabelDatastore('testLabel.png',classes,labelIDs);
+tic
+I = read(imdsTest);
+I = imresize(I,[256 256]);
+C = semanticseg(I, net);
+
+%Display the results.
+B = labeloverlay(I, C, 'Colormap', cmap, 'Transparency',0.4);
+figure
+imshow(B)
+pixelLabelColorbar(cmap, classes);
+
+L = read(pxdsTest);
+expectedResult = imresize(L{1},[256 256],'nearest');
+actual = uint8(C);
+expected = uint8(expectedResult);
+figure;
+imshowpair(actual, expected)
+
+iou = jaccard(C, expectedResult);
+table(classes,iou)
+
+%Evaluate Trained Network
+pxdsResults = semanticseg(imdsTest,net,'WriteLocation',tempdir,'Verbose',false);
+metrics = evaluateSemanticSegmentation(pxdsResults,pxdsTest,'Verbose',false);
+
+toc
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