comparison sceneClassificationMetrics_eval.m @ 1:96b1b8697b60

challenge version

+% from https://soundsoftware.ac.uk/projects/aasp-d-case-metrics
+
+function [confusionMat, AccFolds, Acc, Std] = sceneClassificationMetrics_eval(numfolds, foldsGTlist, foldstestlist)
+
+% Function takes as input a number of folds (numfolds), a text file
+% containing a list of filenames with the ground truth per fold (foldsGTlist), 
+% and a text file containing a list of filenames with the classification
+% output (foldstestlist)
+%
+% e.g. [confusionMat, AccFolds, Acc, Std] = sceneClassificationMetrics_eval(5, 'foldGTlist.txt', 'foldtestlist.txt');
+
+
+% Initialize
+classList = {'bus','busystreet','office','openairmarket','park','quietstreet','restaurant','supermarket','tube','tubestation'};
+confusionMat = zeros(10,10);
+AccFolds = zeros(1,numfolds);
+
+
+% For each fold
+fid1 = fopen(foldsGTlist,'r+');
+fid2 = fopen(foldstestlist,'r+');
+for i=1:numfolds
+    
+    % Load classification output and ground truth
+    tline1 = fgetl(fid1);
+    [fileIDGT,classIDGT] = loadClassificationOutput(tline1);
+    tline2 = fgetl(fid2);
+    [fileID,classID] = loadClassificationOutput(tline2);
+    
+    % Compute confusion matrix per fold
+    confusionMatTemp = zeros(10,10);
+    for j=1:length(classIDGT)
+        pos = strmatch(fileIDGT{j}, fileID, 'exact');
+        posClassGT = strmatch(classIDGT{j}, classList, 'exact');
+        posClass = strmatch(classID{pos}, classList, 'exact');
+        confusionMatTemp(posClassGT,posClass) = confusionMatTemp(posClassGT,posClass) + 1;
+    end
+    
+    % Compute accuracy per fold
+    AccFolds(i) = sum(diag(confusionMatTemp))/sum(sum(confusionMatTemp));
+    confusionMat = confusionMat + confusionMatTemp;
+    
+end
+fclose(fid1);
+fclose(fid2);
+
+
+% Compute global accuracy and std
+Acc = mean(AccFolds);
+Std = std(AccFolds);