My goal is to train a pretrained mask rcnn on the TACO trash detection dataset of images. I want to match the annotations information with their corresponding images?

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The data can be downloaded from Kaggle:
The code I was following can be found with this link in github:
I want to train a pretrained maskr rcnn network on a trash dataset for detecting trash in the wild. So far I have this;
SetDir = fullfile('Training data');
Imds = imageDatastore(SetDir,'IncludeSubfolders',true,'LabelSource','foldernames');
annotationFile = jsondecode(fileread("annotations.json"));
trainClassNames = {'Bottle', 'Can','Bottle cap'};
numClasses = length(trainClassNames);
imageSizeTrain = [800 800 3];
cocoAPIDir = fullfile("cocoapi-master","MatlabAPI");
unpackAnnotationDir = fullfile(SetDir,"annotations_unpacked","matFiles");
if ~exist(unpackAnnotationDir,'dir')

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