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do it in Matlab please! here's the link if you can't load facesD.mat https://tritoned.ucsd.edu/bbcswebdav/pid-1315526-dt-content-rid-17417932_1/xid-17417932_1 4. (30 points) Download the sample of faces from the Yale
do it in Matlab please!
here's the link if you can't load facesD.mat
https://tritoned.ucsd.edu/bbcswebdav/pid-1315526-dt-content-rid-17417932_1/xid-17417932_1
4. (30 points) Download the sample of faces from the Yale face dataset from TritonEd. Each face is a 192x168 pixel image in grayscale. Once you load the data, you can access the first face by entering Yale_facesf1)} Create a five by two grid of subplots and plot all 10 faces one by one using imagesc(). Images are in grayscale; use colormap(gray) to display the images correctly. a. b. Use reshape) to transform each image into a single column vector. Create a matrix containing all 10 column vectors. Report the size of your matrix and explain what each number represents. Using your matrix from (b), calculate a mean face vector. Reshape your mean vector into the same dimensions as the other faces and plot the mean face using imagesc) c. d. Subtract the mean face from each individual face and plot each mean- subtracted face in a5x 2 grid. e. Can you think of a way to represent how "far away" each face is from the mean? If so, describe your answer. If not, explain why not (there's no wrong answer as long as you indicate you've thought about the problem)Step by Step Solution
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