% This function is one of the top level files that call all the tests and 
% figure out which fish their results indicate.  It also adds noise to the image
% to start with.
function [fishtype] = fishcounterback(file)

fish = imread(file);
fishimage1 = im2double(fish);

% Add noise to the picture
noise = randn(size(fishimage1));
noiselevel = .00;

fishimagenoise = fishimage1 + noiselevel.*noise;
fishimagenoisevals = and(fishimagenoise<1, fishimagenoise>0);
fishimage = fishimagenoise.*fishimagenoisevals;


fishmod = 0;

if  sum(sum(rgb2gray(fishimage)))>100
    
    % If the length to width ratio is less than 2.85 and greater than 2, 
    % its a salmon, and if its greater than 3.5, the fish is a trout.
    [length,width,lwratio] = fishedge(fishimage);
    if  and(lwratio <= 2.85, lwratio>2)
        fishmod = fishmod + 1;
    elseif lwratio >=3.5
        fishmod = fishmod - 1;
    end
    
    % Check to see how much intensity there is in each of the color spectrums
    for i = 1:3
        fishnorm(:,:,i) = fishimage(:,:,i)./norm((fishimage(:,:,i)));
        
        intensitymatrix(:,:,i) = reshape(fishimage(:,:,i), 1, prod(size(fishimage(:,:,1))));
        intensity(:,:,i) = mean(intensitymatrix(:,:,i));
    end
   
    rgintens = intensity(:,:,1)-intensity(:,:,2);
    rbintens = intensity(:,:,1)-intensity(:,:,3);
    
    % If the red is greater than one ofthe other spectrums by at least .4, then
    % it is a trout, if they are within .1 of each other, it is a trout.  Otherwise
    % it is an unknown item.
    if rgintens >.04
        fishmod = fishmod + .5;
    elseif rgintens <.01
        fishmod = fishmod - .5;
    end
    
    if rbintens >.04
        fishmod = fishmod + .5;
    elseif rbintens <.01
        fishmod = fishmod - .5;
    end
    
    % Check the features of the fish.
    [body,head,tail] = featureanalyzer(fishimage);
    
    % If the body is red and the head is green, blue, or both, then its a trout.
    % If the body is all three colors and either the head or the tail or both
    % are the same color and included in the body, then it is a trout.
    if and(body == 'r  ', or(head == 'g  ', or(head == 'gb ', head == 'b  ')))
        fishmod = fishmod + 1.5;
    end
    if and(body == 'rgb', and(head == 'cbd', tail == 'cbd'))
        fishmod = fishmod - 1.5;
    elseif and(body == 'rgb', or(head == 'cbd', tail == 'cbd'))
        fishmod = fishmod - 1;
    end
    

    %Count the fins on the fish.  If it is zero, then its probably trash,
    % otherwise, keep the modifier in its present state.
    numfins = findet(fishimage);
    
    if and(numfins == 0, abs(fishmod)<=2)
        fishmod = 0;
    end
    
else 
    fishmod = 0;
end

% If most of the tests think the fish is a salmon, call it a salmon
% If most of the tests think the fish is a trout, call it a trout
% If the tests all don't know, or if they disagree, call it unknown
if fishmod >0
    fishtype = 'salmon ';
elseif fishmod <0
    fishtype = 'trout  ';
else
    fishtype = 'unknown';
end

% This is the top file for the whole system.  It takes in a matrix of filenames and
% a matrix of what type of fish each of the files is.  It then runs the classification
% program on one fish at a time and then computes the accuracy of the outputs.
function [fishmatrix,statsmat,correct,wrong] = massfishcounter(filematrix,typematrix);

for fishnum = 1:size(filematrix,1)
    
    fishnum
    % Classify the current fish
fishmatrix(fishnum,:) = fishcounter(filematrix(fishnum,:));

end

salmoncount = 0;
troutcount = 0;
undetermined = 0;
correct = 0;
wrong = 0;
salcor = 0;
troutcor = 0;
undetcor = 0;
salwrong = 0
troutwrong = 0;
undetwrong = 0;
salmonpercent = 0;
troutpercent = 0;
undetpercent = 0;
% Check all of the output types to the input matrix of which type each
% fish should be and see how accurate the results were.
for z = 1:size(fishmatrix,1)
    switch fishmatrix(z,:)
    case 'salmon '
        salmoncount = salmoncount + 1;
        if fishmatrix(z,:)==typematrix(z,:);
            salcor = salcor + 1;
        else
            salwrong = salwrong + 1;
        end
    case 'trout  '
        troutcount = troutcount + 1;
        if fishmatrix(z,:)==typematrix(z,:);
            troutcor = troutcor + 1;
        else
            troutwrong = troutwrong + 1;
        end
    case 'unknown'
        undetermined = undetermined + 1;
        if fishmatrix(z,:)==typematrix(z,:);
            undetcor = undetcor + 1;
        else
            undetwrong = undetwrong + 1;
        end
    end
end

 salmonpercent = salcor./(salcor+salwrong);
 troutpercent = troutcor./(troutcor+troutwrong);
 undetpercent = undetcor./(undetcor+undetwrong);
 
 correct = salcor + troutcor + undetcor;
 wrong = salwrong + troutwrong + undetwrong;
 
statsmat = [salcor salwrong salmonpercent; troutcor troutwrong troutpercent; undetcor undetwrong undetpercent];

% This function subtract a predeterminded background image from the input image
% and returns just the plain fish.
function [justfish] = subback(file);

fish1 = double(imread(file));

back1 = double(imread('bkunderwater1.jpg','jpg'));
justfish = fish1 - back1;

% This is the same as the fishcounter file, but it works for a non-ideal
% situation, where the backgroup behind the fish must be subtracted off.
function [fishtype] = fishcounterback(file)

% Subtract the background from the picture.
fishimage1 = subback(file);

% Add noise to the picture
noise = randn(size(fishimage1));
noiselevel = 100;

fishimagenoise = fishimage1 + noiselevel.*noise;
fishimagenoisevals = and(fishimagenoise<256, fishimagenoise>0);
fishimage = fishimagenoise.*fishimagenoisevals;

fishmod = 0;

if  sum(sum(rgb2gray(fishimage)))>100
    
    % If the length to width ratio is less than 2.85 and greater than 2, 
    % its a salmon, and if its greater than 3.5, the fish is a trout.
    [length,width,lwratio] = fishedge(fishimage);
    if  and(lwratio <= 2.85, lwratio>2)
        fishmod = fishmod + 1;
    elseif lwratio >=3.5
        fishmod = fishmod - 1;
    end
    
    % Check to see how much intensity there is in each of the color spectrums
    for i = 1:3
        fishnorm(:,:,i) = fishimage(:,:,i)./norm((fishimage(:,:,i)));
        
        intensitymatrix(:,:,i) = reshape(fishimage(:,:,i), 1, prod(size(fishimage(:,:,1))));
        intensity(:,:,i) = mean(intensitymatrix(:,:,i));
    end
    
    rgintens = intensity(:,:,1)-intensity(:,:,2);
    rbintens = intensity(:,:,1)-intensity(:,:,3);
    
    % If the red is greater than one ofthe other spectrums by at least .4, then
    % it is a trout, if they are within .1 of each other, it is a trout.  Otherwise
    % it is an unknown item.
    if rgintens >.04
        fishmod = fishmod + .5;
    elseif rgintens <.01
        fishmod = fishmod - .5;
    end
    
    if rbintens >.04
        fishmod = fishmod + .5;
    elseif rbintens <.01
        fishmod = fishmod - .5;
    end

    % Check the features of the fish.
    [body,head,tail] = featureanalyzer(fishimage);
    
    % If the body is red and the head is green, blue, or both, then its a trout.
    % If the body is all three colors and either the head or the tail or both
    % are the same color and included in the body, then it is a trout.
    if and(body == 'r  ', or(head == 'g  ', or(head == 'gb ', head == 'b  ')))
        fishmod = fishmod + 1.5;
    end
    if and(body == 'rgb', and(head == 'cbd', tail == 'cbd'))
        fishmod = fishmod - 1.5;
    elseif and(body == 'rgb', or(head == 'cbd', tail == 'cbd'))
        fishmod = fishmod - 1;
    end
    
    %Count the fins on the fish.  If it is zero, then its probably trash,
    % otherwise, keep the modifier in its present state.
    numfins = findet(fishimage);
    
    if and(numfins == 0, abs(fishmod)<=2)
        fishmod = 0;
    end
    
else 
    fishmod = 0;
end

% If most of the tests think the fish is a salmon, call it a salmon
% If most of the tests think the fish is a trout, call it a trout
% If the tests all don't know, or if they disagree, call it unknown
if fishmod >0
    fishtype = 'salmon ';
elseif fishmod <0
    fishtype = 'trout  ';
else
    fishtype = 'unknown';
end

% This is the top file for the whole system when the background must be subtracte from 
% the image before it is analyzed.  It takes in a matrix of filenames and
% a matrix of what type of fish each of the files is.  It then runs the classification
% program on one fish at a time and then computes the accuracy of the outputs.
function [fishmatrix,statsmat,correct,wrong] = massfishcounterback(filematrix,typematrix);

for fishnum = 1:size(filematrix,1)
    
    fishnum
    % Classify the current fish
fishmatrix(fishnum,:) = fishcounterback(filematrix(fishnum,:));

end

salmoncount = 0;
troutcount = 0;
undetermined = 0;
correct = 0;
wrong = 0;
salcor = 0;
troutcor = 0;
undetcor = 0;
salwrong = 0
troutwrong = 0;
undetwrong = 0;
salmonpercent = 0;
troutpercent = 0;
undetpercent = 0;

% Check all of the output types to the input matrix of which type each
% fish should be and see how accurate the results were.
for z = 1:size(fishmatrix,1)
    switch fishmatrix(z,:)
    case 'salmon '
        salmoncount = salmoncount + 1;
        if fishmatrix(z,:)==typematrix(z,:);
            salcor = salcor + 1;
        else
            salwrong = salwrong + 1;
        end
    case 'trout  '
        troutcount = troutcount + 1;
        if fishmatrix(z,:)==typematrix(z,:);
            troutcor = troutcor + 1;
        else
            troutwrong = troutwrong + 1;
        end
    case 'unknown'
        undetermined = undetermined + 1;
        if fishmatrix(z,:)==typematrix(z,:);
            undetcor = undetcor + 1;
        else
            undetwrong = undetwrong + 1;
        end
    end
end

 salmonpercent = salcor./(salcor+salwrong);
 troutpercent = troutcor./(troutcor+troutwrong);
 undetpercent = undetcor./(undetcor+undetwrong);
 
 correct = salcor + troutcor + undetcor;
 wrong = salwrong + troutwrong + undetwrong;
 
statsmat = [salcor salwrong salmonpercent; troutcor troutwrong troutpercent; undetcor undetwrong undetpercent];