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:UsersxxooxOneDriveデスクトップMATLAB worksComputer Vision for Engineering and ScienceC2-MachineLearningForComputerVisionModule 4WoodKnotsGroundTruth.mat");

testPath = overwriteGTruthLocations(gTruthTrain);

imageLabeler(gTruthTrain)

imageLabeler(testPath)

load("C:UsersxxooxOneDriveデスクトップMATLAB worksComputer Vision for Engineering and ScienceC2-MachineLearningForComputerVisionModule 4WoodKnotsGroundTruthTest2.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)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:UsersxxooxOneDriveデスクトップMATLAB worksComputer Vision for Engineering and ScienceC2-MachineLearningForComputerVisionModule 4WoodKnotsGroundTruth.mat");

testPath = overwriteGTruthLocations(gTruthTrain);

imageLabeler(gTruthTrain)

imageLabeler(testPath)

load("C:UsersxxooxOneDriveデスクトップMATLAB worksComputer Vision for Engineering and ScienceC2-MachineLearningForComputerVisionModule 4WoodKnotsGroundTruthTest2.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) 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:UsersxxooxOneDriveデスクトップMATLAB worksComputer Vision for Engineering and ScienceC2-MachineLearningForComputerVisionModule 4WoodKnotsGroundTruth.mat");

testPath = overwriteGTruthLocations(gTruthTrain);

imageLabeler(gTruthTrain)

imageLabeler(testPath)

load("C:UsersxxooxOneDriveデスクトップMATLAB worksComputer Vision for Engineering and ScienceC2-MachineLearningForComputerVisionModule 4WoodKnotsGroundTruthTest2.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) matlab, machine learning, testing, training, image labeling MATLAB Answers — New Questions

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