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EUSIPCO_Pipeline.m
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EUSIPCO_Pipeline.m
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clear all;
close all;
clc;
%%
vds=dir('*.avi');
files={vds.name}';
% for i = 1:1:numel(files) % this is for process multiple videos. Doing
% Calculation (Average frame Intensity for detection of blank frame and intensity variation problems..
for i = 1:1:1
[intens, stds] = avr_intensity2(files{i},i);
% [intens, stds, empty_frame] = avr_intensity2(files{i},i);
black_frame(i) = sum(empty_frame);
intens1(i).Name = files{i};
intens1(i).videos(:) = intens;
% intensity(i).intensity(:) = intens(2:length(intens(1,:))-1);
intensity(i).intensity(:) = intens(1:length(intens(1,:))-1);
end
for i = 1:1:numel(files)
% for i = 4:1:4
intens1(i).videos(end) = median(intens1(i).videos);
for k = 1:1:length(intens1(i).videos)
if floor(intens1(i).videos(k)) == 0
efv(i).video(k) = 1;
else
efv(i).video(k) = 0;
end
end
N = length(intens1(i).videos);
for n=1:1:N
std(i).Name = files{i};
std(i).videos(n) = (intens1(i).videos(n)-intens1(i).videos(N))/2.55;
end
end
a = 0.1;
b = 0.3;
for i = 1:1:numel(files)
% for i = 4:1:4
% avr_frame = median(intens1(i).videos);
avr_frame = intens1(i).videos(end);
for k = 1:1:length(intens1(i).videos)-2
if efv(i).video(k) == 0 && efv(i).video(k) == 0
if (intens1(i).videos(k) < (intens1(i).videos(k+1)*(1-a)) || (intens1(i).videos(k) > intens1(i).videos(k+1)*(1+a))) %% need to functionalize it
int_state(i).value(k) = intens1(i).videos(k);
int_state(i).state(k) = 1;
else
int_state(i).value(k) = 0;
int_state(i).state(k) = 0;
end
else
int_state(i).value(k) = 0;
end
if (intens1(i).videos(k) < avr_frame*(1-b) || (intens1(i).videos(k) > avr_frame*(1+b)))&&efv(i).video(k) == 0
int_median_thrs(i).value(k) = 1;
else
int_median_thrs(i).value(k) = 0;
end
end
int_change(i).temporal = sum(int_state(i).value);
int_change(i).global = sum(int_median_thrs(i).value);
black_frame(i,1) = sum(efv(i).video);
% figure,subplot(131), stem(intens1(i).videos);title(sprintf('%s'),files{i},'FontSize',15);
% xlabel('Frame','FontSize',15,'FontWeight','bold');
% ylabel('Average Intensity Value of Frame','FontSize',15,'FontWeight','bold');
%
% subplot(132), stem(int_state(i).value);title('Sequential Frame Analysis','Local Analysis','FontSize',15);
% xlabel('Frame','FontSize',15,'FontWeight','bold');
% ylabel('Value of High Intensity Varrying Frame ','FontSize',15,'FontWeight','bold');
%
% subplot(133), stem(int_median_thrs(i).value);title('Frame Analysis with Median Thresholding','Global Analysis','FontSize',15);
% xlabel('Frame','FontSize',15,'FontWeight','bold');
% ylabel('High Intensity Varrying State','FontSize',15,'FontWeight','bold');
end
%%
for i =1:1:numel(files)
eps = 0.0001;
TP(i,1) = 0;
FP(i,1) = 0;
TN(i,1) = 0;
FN(i,1) = 0;
for k = 1:1:length(VBFI_GT(i).Videos)-2
if (int_median_thrs(i).value(k) == 1) && (VBFI_GT(i).Videos(k) == 1)
TP(i,1) = TP(i,1)+1;
elseif (int_median_thrs(i).value(k) == 1) && (VBFI_GT(i).Videos(k) == 0)
FP(i,1) = FP(i,1)+1;
elseif (int_median_thrs(i).value(k) == 0) && (VBFI_GT(i).Videos(k) == 0)
TN(i,1) = TN(i,1)+1;
elseif (int_median_thrs(i).value(k) == 0) && (VBFI_GT(i).Videos(k) == 1)
FN(i,1) = FN(i,1)+1;
end
end
Accuracy(i,1) = (sum(TP(i))+sum(TN(i)))/((sum(TP(i))+sum(FP(i))+sum(TN(i))+sum(FN(i))));
Specificity(i,1) = (sum(TN(i))+eps)/(sum(TN(i))+sum(FP(i))+eps);
Sensitivity(i,1) = (sum(TP(i))+eps)/(sum(TP(i))+sum(FN(i))+eps);
Precision(i,1) = (sum(TP(i))+eps)/(sum(TP(i))+sum(FP(i))+eps);
end
VideoName = files;
TFmap_IC_pipeline = table(VideoName, TP, FP, TN, FN, Accuracy, Sensitivity, Specificity, Precision);
%%
i = 6;
v= VideoReader(files{i});
myVideo = VideoWriter('enhanced_nonblack.avi');
depVideoPlayer = vision.DeployableVideoPlayer;
open(myVideo);
k= 1;
while hasFrame(v)
frame = readFrame(v);
frame = rgb2gray(frame);
if efv(i).video(k) == 0
if int_median_thrs(i).value(k) == 1
% if intens(k+1)>=min([intens(k), intens(k+2)])*1.05
% frame2 = floor(frame(:,:,:).*(1-(std(i).videos(k))));
% frame2 = floor(frame(:,:,:).*(1-(std(i).videos(k)/100)));
% frame = frame2;
frame2 = floor(frame(:,:,:).*((std(i).videos(k))/100));
frame2 = uint8(double(frame2) + (double(frame(:,:,:)) + ones(size(frame))*((std(i).videos(k))/100)))./2;
writeVideo(myVideo, frame2);
pause(1/v.FrameRate );
else
writeVideo(myVideo, frame);
pause(1/v.FrameRate );
end
end
corrected_mean(k,i) = mean(mean(frame));
if k < length(intens1(i).videos)-2
k = k +1
end
end
%% function avr_intensity2
% 1st input: Name of the video in the same directort,
% 2nd input: current count of the "first loop" (need to display only)
% function [intens, stds, empty_frame] = avr_intensity2(video_name, i)
function [intens, stds] = avr_intensity2(video_name, i)
v= VideoReader(video_name);
k=1;
while hasFrame(v)
frame = rgb2gray(readFrame(v));
% frame = readFrame(v);
intens1(k) = floor(mean(mean(frame)));
k = k +1;
sprintf('intensity analysis video: %d, frame: %d',i, k)
end
% intens = [intens, mean(intens)];
intens = [intens, median(intens)];
N = length(intens);
for k=1:1:N-2
stds(k) = abs(intens(k)-intens(N))/2.55;
% if intens(k) == 0
% empty_frame(k) = 1;
% else
% empty_frame(k) = 0;
% end
end
end
% %% Creating Video from Images
% clc, clear all, close all;
% %%
% images=dir('*.tif');
% files={images.name}';
% myVideo = VideoWriter('Cell_tracking.avi');
% depVideoPlayer = vision.DeployableVideoPlayer;
% open(myVideo);
%
% for k = 1:1: numel(files)
%
% frame = imread(files{k, 1});
% writeVideo(myVideo, frame);
% pause(1/20 );
%
% end
% k = m; % to trigger alarm after video writing is complete
%%
% for i = 3:1:4%numel(efv)
% efv(i).State = sum(efv(i).video(:));
% int_median_thrs(i).State = sum(int_median_thrs(i).value(:));
% figure(i),subplot(121),stem(int_median_thrs(i).value, "r"), xlabel("frame number"),ylabel("state of detection"), title(sprintf(files{i,1}));
% hold on,stem(int_state(i).state,"g");
% subplot(122),stem(intens1(i).videos), xlabel("frame number"),ylabel("AFI"),title(sprintf(files{i,1}));
% hold on,
% z1 = 0.9.*intens1(i).videos;
% plot(z1,"g--o", "LineWidth", 1);
% z2 = 1.1.*intens1(i).videos;
% plot(z2,"g--o", "LineWidth", 1);
% y = median(intens1(i).videos).*ones(length(intens1(i).videos));
% plot(y,"r", "LineWidth", 2);
% y1 = 1.3*median(intens1(i).videos).*ones(length(intens1(i).videos));
% plot(y1,"r--", "LineWidth", 2);
% y2 = 0.7*median(intens1(i).videos).*ones(length(intens1(i).videos));
% plot(y2,"r--", "LineWidth", 2);
% set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
%
% saveas(figure(i), sprintf("%s.tif", files{i,1}))
% close all
% end
% for i = 1:1:14
% for k = 1:1:length(int_median_thrs(i).value)
% VBFI_GT(i).Videos(k) = FramebaseGTofIntensity2{i,k+1};
% end
%
% end