how is it possible to have different results (true positive) using the following methods?
1) augimds = augmentedImageDatastore(inputSize(1:2), imds); %only resize
[predictedClasses1, predictedScores1] = classify(net, augimds);
create a datastore, resize the image of the datastore, classify the images
2)[YPred,scores] = classify(net,imgLaikaGrass);
take each image belonging to the previous datastore (one-by-one) and classify it. Images have been already resized accordingly.
Confusion chart results in a different number of true positives in comparing the two methods. In other words, why an image correctly classified in 1) is not correctly classified using 2).