%% File was used to demostrate how to estimate training results
% draws confusionchart

% you have to modify directory
% it will be path to the images
% but download Linnaeus data set first
% and place in neural_network_training_sets folder
% Linnaeus 5 256X256 subfolder
% (link is in neural_network_training_sets folder)
% e.g.
% .\neural_network_training_sets\Linnaeus 5 256X256


%directory = "D:\from_Downloads\Linnaeus 5 256X256\";

directory = "./neural_network_training_sets/Linnaeus 5 256X256/"
imds = imageDatastore(directory+"test","IncludeSubfolders",...
    true,'LabelSource','foldernames');
augsTest = augmentedImageDatastore([227 227],imds,'ColorPreprocessing','gray2rgb');
% opts = trainingOptions("sgdm");
% opts.InitialLearnRate = 0.001;
% opts.LearnRateDropFactor = 0.5;
% opts.LearnRateDropPeriod = 10;
% opts.MiniBatchSize= 2048;
% opts.LearnRateSchedule = 'piecewise';
% opts.ExecutionEnvironment = 'multi-gpu';
% [flowernet,info] = trainNetwork(auds,layers_1,opts);
realClass = imds.Labels;

%load alexnet_with_weights_modified_for_5_classes.mat

load fine_tuning_example2.mat

[predClass,scores] = flowernet.classify(augsTest);
confusionchart(realClass,predClass);

prob = nnz(realClass==predClass)/numel(realClass);

% also problematic images... show