What part of this training and testing steps need(s) to be modified to get the correct missing rate?

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I got missing rate = 1 with this attached code, but my class's auto grading system says it's incorrect.
What part of this training and testing steps need(s) to be modified to get the correct missing rate?
[Current Code]
load("C:\Users\xxoox\OneDrive\デスクトップ\MATLAB works\Computer Vision for Engineering and Science\C2-MachineLearningForComputerVision\Module 4\WoodKnotsGroundTruth.mat");
testPath = overwriteGTruthLocations(gTruthTrain);
imageLabeler(gTruthTrain)
imageLabeler(testPath)
load("C:\Users\xxoox\OneDrive\デスクトップ\MATLAB works\Computer Vision for Engineering and Science\C2-MachineLearningForComputerVision\Module 4\WoodKnotsGroundTruthTest2.mat");
imdsTest = imageDatastore(testPath);
gTruth.LabelDefinitions
gTruth.DataSource
gTruth.LabelData
objectTrainingData = objectDetectorTrainingData(gTruthTrain)
acfDetector = trainACFObjectDetector(objectTrainingData)
imdsTest = imageDatastore(testPath)
bboxes = detect(acfDetector,imdsTest)
evaluateDetectionMissRate(bboxes,gTruthTest.LabelData)
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