diego0020 · PardoAlejo · Feb 18, 2016 · Feb 18, 2016 · Feb 18, 2016 · Feb 18, 2016
diff --git a/Originals.tif b/Originals.tif
diff --git a/README.md b/README.md
@@ -1,3 +1,4 @@
 # Computer vision lab
 
 This repository will contain guides and scripts required during the lab.
+ok ok ok ok
diff --git a/Retoques.tif b/Retoques.tif
diff --git a/lab01_git/questions.md b/lab01_git/questions.md
@@ -1,7 +1,7 @@
 # Warmup Questions
 
 1.  What is the clone url of this repository?
-    >   answer
+    >   https://github.com/PardoAlejo/lab_vision
 
 2.  What is the output of the ``cal`` command?
 
@@ -12,46 +12,47 @@
 # Homework Questions
 
 1.  What is the ``grep``command?
-    >   answer
+    >   grep allows to look for a command in the code, and helps to make many actions, like print in the screen, count the number of matches, and look for complexes combinations of strings.
 
 2.  What is a *makefile*?
-    >   answer
+    >   Is the file that allow the project to be build. 
 
 4.  What does the ``-prune`` option of ``find`` do? Give an example
-    >   answer
+    >   prune option help to find what we are looking for, without search in all subdirectories or without look in a particular subdirectory. 
 
 5.  Where is the ``grub.cfg``  file
-    >   answer
+    >   This is the default boot loader and launcher of ubuntu, and it is in /boot/grub/grub.cfg.
 
 6.  How many files with ``gnu`` in its name are in ``/usr/src``
-    >   answer
+    >   0 files  using find /usr/src/ - gnu | wc -l.
 
 7.  How many files contain the word ``gpl`` inside in ``/usr/src``
-    >   answer
+    >   844 files, by using: grep -irm 1 "gpl" /usr/src/ | wc -l
+
 
 8.  What does the ``cut`` command do?
-    >   answer
+    >   with the command cut, you can "cut" the number of characters to the number of characters that you want. 
 
 9.  What does the ``wget`` command do?
-    >   answer
+    >   this command follow links of the web and download files, also can create local versions of websites, recreating the directoy of the original file, in order to prevents you to repeat the same processes in the same website many times.
 
 9.  What does the ``rsync`` command do?
-    >   answer
+    >   rsync allows to transfer just the differences between two sets of files across the network link, 
 
 10.  What does the ``diff`` command do?
-    >   answer
+    >   Diff command analize a couple of files and print on the screen the lines which both are different.
 
 10.  What does the ``tail`` command do?
-    >   answer
+    >   read the last lines of a file and write them as an output.
 
 10.  What does the ``tail -f`` command do?
-    >   answer
+    >  with the additional -f, allows to the file to be monitored, if the file is modified by another process, tail shows in the display the changes, it is mainly use to monitor log files.
 
 10.  What does the ``link`` command do?
-    >   answer
+    >   Links two files, and in consecuence any change in one of the files affects the other one. It link the files puting them in the same place of the disk.
 
 11.  How many users exist in the course server?
-    >   answer
+    >  8
 
 12. What command will produce a table of Users and Shells sorted by shell (tip: using ``cut`` and ``sort``)
     >   answer

diff --git a/lab01_git/readme.md b/lab01_git/readme.md
@@ -4,7 +4,7 @@
 
 - Read about version control and Git (sections 1.1 - 1.4)  
   http://git-scm.com/book/en/v2/Getting-Started-About-Version-Control 
-
+asd
 ## Basics
 
 ### Create a repository

diff --git a/lab3_hybrid/data/bicycle.bmp b/lab3_hybrid/data/bicycle.bmp
diff --git a/lab3_hybrid/data/bird.bmp b/lab3_hybrid/data/bird.bmp
diff --git a/lab3_hybrid/data/cat.bmp b/lab3_hybrid/data/cat.bmp
diff --git a/lab3_hybrid/data/dog.bmp b/lab3_hybrid/data/dog.bmp
diff --git a/lab3_hybrid/data/einstein.bmp b/lab3_hybrid/data/einstein.bmp
diff --git a/lab3_hybrid/data/fish.bmp b/lab3_hybrid/data/fish.bmp
diff --git a/lab3_hybrid/data/marilyn.bmp b/lab3_hybrid/data/marilyn.bmp
diff --git a/lab3_hybrid/data/motorcycle.bmp b/lab3_hybrid/data/motorcycle.bmp
diff --git a/lab3_hybrid/data/plane.bmp b/lab3_hybrid/data/plane.bmp
diff --git a/lab3_hybrid/data/submarine.bmp b/lab3_hybrid/data/submarine.bmp
diff --git a/lab3_hybrid/modified.jpg b/lab3_hybrid/modified.jpg
diff --git a/lab3_hybrid/originals.jpg b/lab3_hybrid/originals.jpg
diff --git a/lab3_hybrid/pyramid.jpg b/lab3_hybrid/pyramid.jpg
diff --git a/lab3_hybrid/readme.md b/lab3_hybrid/readme.md
@@ -69,13 +69,76 @@ Create a hybrid image based on images from your own collections. The more origin
 
 Notice that you will have to *align and crop* the images to get a good effect. To do this you may use image edition software like gimp or photoshop. You are free to do any additional processing that you want in order to increase the effect. Also consider how to deal with color on the images.
 
+
+
 Finally, upload to the repository
 
+These are my results:
+
 - The original images
+  ![originales](originals.jpg)
+- My girlfriend and me.
 - The processed images (cropped, aligned, color adjusted)
-- A short description of each image (one paragraph)
+  ![Processed images](modified.jpg)
+-  For my girlfriend image I enhaced the contrast of the image, multiplying it by a constant >1 to give it more importance because it was going to be the image with the high frequencies and I realized that in this two photos the low frequency dominated. On the other hand, for my image I multiplied it by a constant <1 to reduce the contast and increase the effect of the hybrid image.
+
 - The final hybrid image
+ ![Processed images](result.jpg)
+- This is the result after take both , high and low frequencies and mixed up the images.
+
 - The pyramid
+ ![Processed images](pyramid.jpg)
+- Pyramid to see the effect of low and high frequencies.
 - The code you used (with comments)
 
+CODE:
+
+% this is the code for make hybrid images by Alejandro Pardo
+clc;clear all; close all;
+%Add path of the functions
+addpath(genpath('proj1'));
+
+%Read the images
+original_down=im2double(imread('IMG_1671.jpg'));
+original_up=im2double(imread('IMG_1669.jpg'));
+
+%Process the images before the transformation
+down=0.4*original_down;
+up=1.2*original_up;
+
+%Cutoff frequencies, parameters of the filter
+cutoff=7;
+cutoff1=7;
+
+%Filter masks, tipe gaussian, with variance as a function of the cutoff
+%frequencies, resulting by the analysis of the convolution. the scale
+%factor that multiplies the cutoff frequency is the one that set the
+%overlaping of the frequencies of the images, this factor basically
+%determines how the images are combined each other. The window size was 9x9
+h=fspecial('gaussian',cutoff*3+1,9);
+h1=fspecial('gaussian',cutoff1*3+1,9);
+
+%Get the low frequencies of the image 1
+god=imfilter(down,h);
+
+%Get the high frequencies of the image 2
+tac=imfilter(up,h1);
+tac=(up-tac);
+
+%Combine the images to generate the hybrid result
+result=god+tac;
+
+%Results visualization
+figure;
+subplot(1,2,1);imshow(original_down);title('Original Image low frequencies');
+subplot(1,2,2);imshow(original_up);title('Original Image high frequencies');
+figure;
+subplot(1,2,1);imshow(down);title('Adjusted Image low frequencies');
+subplot(1,2,2);imshow(up);title('Adjusted Image high frequencies');
+figure
+imshow(vis_hybrid_image(result));title('Pyramid')
+figure 
+imshow(result);title('Result');
+
+
 **DUE**: 3 /3 /2016 ; 10:00 a.m.
diff --git a/lab3_hybrid/result.jpg b/lab3_hybrid/result.jpg
diff --git a/lab4_segmentation/segment_by_clustering.m b/lab4_segmentation/segment_by_clustering.m
@@ -0,0 +1,98 @@
+function labels = segment_by_clustering(im,space,method,k)
+
+%This function generates an RGB image segmentation in k clusters
+%Space: color space used for segmentation. Posible entries: 'rgb' 'lab' 'hsv' 'rgb+xy' 'lab+xy' 'hsv+xy'
+%Method: method used for segmentation. Possible entries: 'kmeans' 'gmm'
+%'watershed' 'hierarchical'
+
+
+%color spaces
+scale_factor=2;
+if strcmp(method,'hierarchical')
+im=imresize(im,1/scale_factor);
+end
+
+im=im2double(im);
+[n,m,z]=size(im);
+
+%rgb
+imrgb=im./(max(im(:)));
+%lab
+cform = makecform('srgb2lab');
+imlab = applycform(im,cform);
+imlab=imlab-(min(imlab(:))).*ones(size(imlab));
+imlab=imlab./(max(imlab(:)));
+%hsv
+imhsv=rgb2hsv(im);
+imhsv=imhsv./((max(imlab(:))));
+%xy feature
+[y,x]=meshgrid(1:m,1:n);
+xm=reshape(x,n*m,1);xm=0.4*xm./max(xm(:));
+ym=reshape(y,n*m,1);ym=0.4*ym./max(ym(:));
+
+%Chose de color space
+if strcmp(space,'rgb')
+    imn=reshape(imrgb,n*m,3);
+    my=[imn];
+elseif strcmp(space,'rgb+xy')
+    imn=reshape(imrgb,n*m,3);
+    my=[imn xm ym];
+elseif strcmp(space,'lab')
+    imn=reshape(imlab,n*m,3);
+    my=[imn];
+elseif strcmp(space,'lab+xy')
+    imn=reshape(imlab,n*m,3);
+    my=[imn xm ym];
+elseif strcmp(space,'hsv')
+    imn=reshape(imhsv,n*m,3);
+    my=[imn];
+elseif strcmp(space,'hsv+xy')
+    imn=reshape(imhsv,n*m,3);
+    my=[imn xm ym];
+else 
+    error('Invalid space input')
+end
+
+%Chose the method
+if strcmp(method,'kmeans')
+
+    [idx]=kmeans(my,k);
+    labels=reshape(idx,n,m);
+
+elseif strcmp(method,'gmm')
+
+    obj = fitgmdist(my,k);
+    idx = cluster(obj,my);
+    labels=reshape(idx,n,m);
+
+elseif strcmp(method,'watershed')
+
+    im_gray = rgb2gray(im(:,:,1:3));
+
+  %gradient’s magnitude
+    hy = fspecial('sobel');
+    hx = hy';
+    Iy = imfilter(im2double(im_gray), hy, 'replicate');
+    Ix = imfilter(im2double(im_gray), hx, 'replicate');
+    grad = sqrt(Ix.^2 + Iy.^2);
+
+    %Markers for extended minima
+    marker = imextendedmin(grad, k);
+    %Impose minima
+    new_grad = imimposemin(grad, marker);
+    %Watershe calculation
+    labels = watershed(new_grad);
+
+elseif strcmp(method,'hierarchical')
+
+    idx=clusterdata(my,'distance','euclidean','linkage','ward',...
+        'savememory','on','maxclust',k);
+
+    labels=reshape(idx,n,m);
+    labels=imresize(labels,scale_factor);
+else
+    error('Invalid method input')
+end
+
+imshow(labels,[]);title('Segmented Image')
+end
diff --git a/lab8_cnn/0b52dff5-841d-4780-b807-b6542761d1d9.jpeg b/lab8_cnn/0b52dff5-841d-4780-b807-b6542761d1d9.jpeg
diff --git a/lab8_cnn/getBatchWithJitter.m b/lab8_cnn/getBatchWithJitter.m
@@ -0,0 +1,31 @@
+% --------------------------------------------------------------------
+function [im, labels] = getBatchWithJitter(imdb, batch)
+% --------------------------------------------------------------------
+im = imdb.images.data(:,:,batch) ;
+labels = imdb.images.label(1,batch) ;
+
+n = numel(batch) ;
+train = find(imdb.images.set == 1) ;
+
+sel = randperm(numel(train), n) ;
+im1 = imdb.images.data(:,:,sel) ;
+
+sel = randperm(numel(train), n) ;
+im2 = imdb.images.data(:,:,sel) ;
+
+ctx = [im1 im2] ;
+ctx(:,17:48,:) = min(ctx(:,17:48,:), im) ;
+
+dx = randi(11) - 6 ;
+im = ctx(:,(17:48)+dx,:) ;
+sx = (17:48) + dx ;
+
+dy = randi(5) - 2 ;
+sy = max(1, min(32, (1:32) + dy)) ;
+
+im = ctx(sy,sx,:) ;
+
+% Visualize the batch:
+% figure(100) ; clf ;
+
+im = 256 * reshape(im, 32, 32, 1, []) ;
diff --git a/lab8_cnn/initializeCNN.m b/lab8_cnn/initializeCNN.m
@@ -0,0 +1,73 @@
+function net = initializeCNN()
+
+f=1/100 ;
+net.layers = {} ;
+
+%Layer 1: Convolutional layer. Input size: 32x32 
+
+net.layers{end+1} = struct('type', 'conv', ...
+                           'filters', f*randn(5,5,1,20, 'single'), ...
+                           'biases', zeros(1, 20, 'single'), ...
+                           'stride', 1, ...
+                           'pad', 0) ;
+%Layer 2: Pooling layer. Input size: 28x28x20
+net.layers{end+1} = struct('type', 'pool', ...
+                           'method', 'max', ...
+                           'pool', [2 2], ...
+                           'stride', 2, ...
+                           'pad', 0) ;
+%Layer 3: Convoluting layer. Input size: 28x28x20 
+net.layers{end+1} = struct('type', 'conv', ...
+                           'filters', f*randn(4,4,50,500, 'single'),...
+                           'biases', zeros(1,500,'single'), ...
+                           'stride', 1, ...
+                           'pad', 0) ;
+%Layer 4. Input size: 24x24x20x500
+net.layers{end+1} = struct('type', 'relu') ;
+
+%Layer 5: Convolutional layer. Input: 24x240000
+net.layers{end+1} = struct('type', 'conv', ...
+                           'filters', f*randn(2,2,500,750, 'single'),...
+                           'biases', zeros(1,750,'single'), ...
+                           'stride', 1, ...
+                           'pad', 0) ;
+
+%Layer 6 Input: 20x240996x750
+net.layers{end+1} = struct('type', 'softmaxloss');
+
+
+
+% f=1/100 ;
+% net.layers = {} ;
+% net.layers{end+1} = struct('type', 'conv', ...
+%                            'filters', f*randn(5,5,1,20, 'single'), ...
+%                            'biases', zeros(1, 20, 'single'), ...
+%                            'stride', 1, ...
+%                            'pad', 0) ;
+% net.layers{end+1} = struct('type', 'pool', ...
+%                            'method', 'max', ...
+%                            'pool', [2 2], ...
+%                            'stride', 2, ...
+%                            'pad', 0) ;
+% net.layers{end+1} = struct('type', 'conv', ...
+%                            'filters', f*randn(5,5,20,50, 'single'),...
+%                            'biases', zeros(1,50,'single'), ...
+%                            'stride', 1, ...
+%                            'pad', 0) ;
+% net.layers{end+1} = struct('type', 'pool', ...
+%                            'method', 'max', ...
+%                            'pool', [2 2], ...
+%                            'stride', 2, ...
+%                            'pad', 0) ;
+% net.layers{end+1} = struct('type', 'conv', ...
+%                            'filters', f*randn(4,4,50,500, 'single'),...
+%                            'biases', zeros(1,500,'single'), ...
+%                            'stride', 1, ...
+%                            'pad', 0) ;
+% net.layers{end+1} = struct('type', 'relu') ;
+% net.layers{end+1} = struct('type', 'conv', ...
+%                            'filters', f*randn(2,2,500,26, 'single'),...
+%                            'biases', zeros(1,26,'single'), ...
+%                            'stride', 1, ...
+%                            'pad', 0) ;
+% net.layers{end+1} = struct('type', 'softmaxloss') ;