I need to modify this code to upload an image manually and match the image from stored database

%% Loading the database into matrix v

w=load_database();

%% Initializations

% We randomly pick an image from our database and use the rest of the

% images for training. Training is done on 399 pictues. We later

% use the randomly selectted picture to test the algorithm.

ri=round(2*rand(1,1)); % Randomly pick an index.

r=imread('2.pgm');

k=w(:,ri); % r contains the image we later on will use to test the algorithm

v=w(:,[1:ri-1 ri+1:end]); % v contains the rest of the 399 images.

N=20; % Number of signatures used for each image.

%% Subtracting the mean from v

O=uint8(ones(1,size(v,2)));

m=uint8(mean(v,2)); % m is the maen of all images.

vzm=v-uint8(single(m)*single(O)); % vzm is v with the mean removed.

%% Calculating eignevectors of the correlation matrix

% We are picking N of the 400 eigenfaces.

L=single(vzm)'*single(vzm);

[V,D]=eig(L);

V=single(vzm)*V;

V=V(:,end:-1:end-(N-1)); % Pick the eignevectors corresponding to the 10 largest eigenvalues.

%% Calculating the signature for each image

cv=zeros(size(v,2),N);

for i=1:size(v,2);

cv(i,:)=single(vzm(:,i))'*V; % Each row in cv is the signature for one image.

end

%% Recognition

% Now, we run the algorithm and see if we can correctly recognize the face.

subplot(121);

imshow(reshape(r,112,92));title('Looking for ...','FontWeight','bold','Fontsize',16,'color','red');

subplot(122);

p=k-m; % Subtract the mean

s=single(p)'*V;

z=[];

for i=1:size(v,2)

z=[z,norm(cv(i,:)-s,2)];

if(rem(i,20)==0),imshow(reshape(v(:,i),112,92)),end;

drawnow;

end

[a,i]=min(z);

subplot(122);

imshow(reshape(v(:,i),112,92));title('Found!','FontWeight','bold','Fontsize',16,'color','red');