precision-recall curve for faster rcnn

hi

i want to find precision-recall curve of my tranied faster rcnn detector.i tried thi code

testData = transform(testData,@(data)preprocessData(data,inputSize));
detectionResults = detect(detector,testData,'MinibatchSize',4);   
classID = 1;
metrics = evaluateObjectDetection(detectionResults,testData);
precision = metrics.ClassMetrics.Precision{classID};
recall = metrics.ClassMetrics.Recall{classID};
figure
plot(recall,precision)
xlabel('Recall')
ylabel('Precision')
grid on
title(sprintf('Average Precision = %.2f', metrics.ClassMetrics.mAP(classID)))

but it shows error on evaluateObjectDetection that this is not in matlab second is that it show error that dot errorr is not worked in this( metrics.ClassMetrics.Precision{classID};)

so is there any other way to find precission-recall for multiple classes

Answer 1

[Walter Roberson]

https://www.mathworks.com/help/vision/ref/evaluateobjectdetection.html was introduced in R2023b, but you have R2023a.

There are no functions available in R2023a that return metrics.