5th semester files

5th-Semester-Fall-2023/Signals-and-Systems/Labs/Final-Project/knnFace.m

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+function bestSubject = knnFace(facePath, k, dctData, dctDim, dctDataClass)
+%{
+    facefile    path to the face image file
+    k           the number of close neighbors to find
+    dctData     the pretrained dataset
+    dctDim      the dimesion of DCT data to work with
+%}
+
+% Find the number of faces in the dataset
+N = length(dctData);
+
+% Get the 1-D feature vector of the DCT of the face
+features = findfeatures(facePath, dctDim);
+
+% Find the distance from the face to each face in the dataset
+dists = zeros(N, 1);
+for idx = 1 : N
+    % Calculate the Euclidean distance in any dimension (found with 2-norm)
+    dists(idx) = norm(features' - dctData(idx,:), 2);
+end
+
+% Sort the distances in ascending order
+[sDists, origIdx] = sort(dists);
+
+% Find the corresponding best subjects for the shortest distances
+bestSubjects = zeros(k,1);
+for idx = 1 : k
+  bestSubjects(idx) = dctDataClass(origIdx(idx));
+end
+
+bestSubject = mode(bestSubjects);