I want to save the same picture in different formats (.pdf, .jpeg, .fig) with diferent orientation.
Here is my current code:
A = readtable('RON.xlsx');
tempo_A = A{:,1:2:end};
[n,m] = size(A);
variavel_original = A{:,2:2:end};
var = {'Y1','Y2','Y3','Y4'};
guardar = {'Y1','Y2','Y3','Y4'};
guardar2 = {'YY'};
var_original = {'Y1','Y2','Y3','Y4'};
n_var = length(var);
for j=1:n_var
pdf=figure;
set(pdf,'PaperUnits','centimeters','PaperPosition',[0 0 29 21],'PaperOrientation','landscape');
plot(tempo_A(:,j),variavel_original(:,j),'-b*');
title(var(j));
grid on
xlabel('tempo');
ylabel('Y');
legend(var_original(j),'Location','best','Orientation','vertical');
saveas(pdf,fullfile('C:\Users\TiagoAlexandre\Documents\MATLAB\GALP\RON\Originais', guardar{j}), 'pdf');
end
So, in the set command I choose the option landscape, it creates a pdf file landscape of size almost A4 which is OK for the purpose.
Questions:
I wanted to save the jpeg file as 'portrait', how would I do that? (I want the jpeg file the same way as the pdf file, with the plot left to right).
I would want to save the .fig file a bit bigger, like a maximized window.
As i posted it saves a pdf landscape, to make a landscape of a jpg file the code is the following:
orient portrait
saveas(pdf,fullfile('C:\Users\TiagoAlexandre\Documents\MATLAB\GALP\RON\Originais', guardar{j}), 'jpg');
Related
circle_folder = 'C:\Users\MyPC\Documents\CR\start\circle';
name_circle = dir(fullfile(circle_folder, '*.png'));
total_circle = numel(name_circle);
rez_circle = [25 25];
m_circle = zeros(25*25, 5);
for n_circle = 1:total_circle
full_circle = fullfile(circle_folder, name_circle(n_circle).name);
images_circle = imread(full_circle);
images_circle = imresize(images_circle, rez_circle);
store_circle = imbinarize(images_circle);
store_circle = store_circle(:);
m_circle(:, n_circle) = store_circle;
figure(n_circle);
imshow(m_circle);
end
I'm trying to pull images from the folder in question, resize them to 25 by 25 pixels, then turn them into a binary matrix. The code works until the point i attempt to fit the images into said matrix. If I make the matrix bigger, so it becomes 1875-by-1, it works, however, I do need the matrix to be of this size.
What happened is that you loaded an m-by-n-by-3 image, i.e. a 3 channel image. You used imresize() to resize each channel independently, ending up with a 25-by-25-by-3 image. imbinarize() finally works on each channel separately as well.
Instead, before resizing, call rgb2gray(images_circle) to change your 3 channel image to a 1 channel image. Then you can call imresize() and imbinarize(), resulting in your desired 25-by-25 binary image.
I am reading a filename.mp4 video file in MATLAB. I want to edit the images, however, I want to keep the audio intact. Using VideoReader and VideoWriter only does the images part. I used vision.VideoFileReader and 'vision.VideoFileWriter'. I read the video and audio files, then take the image and add a picture next to it. Then write the frame and the audio associated with it. The final video shows the picture I added, but not the original image. Any help appreciated.
v = VideoReader('movie.mp4');
nfr = v.NumberofFrames;
clear v;
vR = vision.VideoFileReader('movie.mp4','AudioOutputPort',1);
fr = vR.info.VideoFrameRate;
vW = vision.VideoFileWriter('filename.avi','AudioInputPort',1,'FrameRate',fr);
pic = imread('picture.png');%read picture
[a1,b1,~] = size(pic);% get picture size to be resized.
for i = 1:nfr
[I,audio] = vR();
I = permute(I,[2,1,3]);%rotate 90 degrees
if i == 1%resize the picture
[a,b,~] = size(I);
pic = imresize(pic,[a,a/a1*b1]);
end
I = [I pic];%combine picture and movie frame
vW(I,audio);%write frame and audio
end
release(vR);
release(vW);
I figured it out.
v = VideoReader('movie.mp4');
nfr = v.NumberofFrames;
clear v;
vR = vision.VideoFileReader('movie.mp4','AudioOutputPort',1,'VideoOutDataType','uint8');
%default of VideoOutDataType is 'single', converting it to a similar format is essential
fr = vR.info.VideoFrameRate;
vW = vision.VideoFileWriter('filename.avi','AudioInputPort',1,'FrameRate',fr);
pic = imread('picture.png');%read picture
[a1,b1,~] = size(pic);% get picture size to be resized.
for i = 1:nfr
[I,audio] = vR();
I = permute(I,[2,1,3]);%rotate 90 degrees
if i == 1%resize the picture
[a,b,~] = size(I);
pic = imresize(pic,[a,a/a1*b1]);%resizing the pic to same height as movie frame %with proportional width
end
I = [I pic];%combine picture and movie frame
vW(I,audio);%write frame and audio
end
release(vR);
release(vW);
I've written a Matlab code to crop an image with respect to a mask.
function Crop_Img = Crop_Xray(Img,Mask)
% Find borders
vertical_profile = sum(Mask,2);
horizontal_profile = sum(Mask);
indexes = find(vertical_profile >0);
upper = indexes(1);
lower = indexes(end);
indexes = find(horizontal_profile > 0);
left = indexes(1);
right = indexes(end);
% Crop Img
Crop_Img = Img(upper:lower, left:right);
end
I would like to save the individual image file names (*.png) and their respective bounding box co-ordinates [upper: lower, left: right] exactly in the format I have mentioned, in adjacent columns to a .xls, .txt, and .mat file. How should I do that?
I have an image and a subimage which is cropped out of the original image.
Here's the code I have written so far:
val1 = imread(img);
val2 = imread(img_w);
gray1 = rgb2gray(val1);%grayscaling both images
gray2 = rgb2gray(val2);
matchingval = normxcorr2(gray1,gray2);%normalized cross correlation
[max_c,imax]=max(abs(matchingval(:)));
After this I am stuck. I have no idea how to change the whole image grayscale except for the sub image which should be in color.
How do I do this?
Thank you.
If you know what the coordinates are for your image, you can always just use the rgb2gray on just the section of interest.
For instance, I tried this on an image just now:
im(500:1045,500:1200,1)=rgb2gray(im(500:1045,500:1200,1:3));
im(500:1045,500:1200,2)=rgb2gray(im(500:1045,500:1200,1:3));
im(500:1045,500:1200,3)=rgb2gray(im(500:1045,500:1200,1:3));
Where I took the rows (500 to 1045), columns (500 to 1200), and the rgb depth (1 to 3) of the image and applied the rgb2gray function to just that. I did it three times as the output of rgb2gray is a 2d matrix and a color image is a 3d matrix, so I needed to change it layer by layer.
This worked for me, making only part of the image gray but leaving the rest in color.
The issue you might have though is this, a color image is 3 dimensions while a gray scale need only be 2 dimensions. Combining them means that the gray scale must be in a 3d matrix.
Depending on what you want to do, this technique may or may not help.
Judging from your code, you are reading the image and the subimage in MATLAB. What you need to know are the coordinates of where you extracted the subimage. Once you do that, simply take your original colour image, convert that to grayscale, then duplicate this image in the third dimension three times. You need to do this so that you can place colour pixels in this image.
For RGB images, grayscale images have the RGB components to all be the same. Duplicating this image in the third dimension three times creates the RGB version of the grayscale image. Once you do that, simply use the row and column coordinates of where you extracted the subimage and place that into the equivalent RGB grayscale image.
As such, given your colour image that is stored in img and your subimage stored in imgsub, and specifying the rows and columns of where you extracted the subimage in row1,col1 and row2,col2 - with row1,col1 being the top left corner of the subimage and row2,col2 is the bottom right corner, do this:
img_gray = rgb2gray(img);
img_gray = cat(3, img_gray, img_gray, img_gray);
img_gray(row1:row2, col1:col2,:) = imgsub;
To demonstrate this, let's try this with an image in MATLAB. We'll use the onion.png image that's part of the image processing toolbox in MATLAB. Therefore:
img = imread('onion.png');
Let's also define our row1,col1,row2,col2:
row1 = 50;
row2 = 90;
col1 = 80;
col2 = 150;
Let's get the subimage:
imgsub = img(row1:row2,col1:col2,:);
Running the above code, this is the image we get:
I took the same example as rayryeng's answer and tried to solve by HSV conversion.
The basic idea is to set the second layer i.e saturation layer to 0 (so that they are grayscale). then rewrite the layer with the original saturation layer only for the sub image area, so that, they alone have the saturation values.
Code:
img = imread('onion.png');
img = rgb2hsv(img);
sPlane = zeros(size(img(:,:,1)));
sPlane(50:90,80:150) = img(50:90,80:150,2);
img(:,:,2) = sPlane;
img = hsv2rgb(img);
imshow(img);
Output: (Same as rayryeng's output)
Related Answer with more details here
I have a set of mask images that I need to use everytime I recognise a previously-known scene on my camera. All the mask images are in IplImage format. There will be instances where, for example, the camera has panned to a slightly different but nearby location. this means that if I do a template matching somewhere in the middle of the current scene, I will be able to recognise the scene with some amount of shift of the template in this scene. All I need to do is use those shifts to adjust the mask image ROIs so that they can be overlayed appropriately based on the template-matching. I know that there are functions such as:
cvSetImageROI(Iplimage* img, CvRect roi)
cvResetImageROI(IplImage* img);
Which I can use to set crop/uncrop my image. However, it didn't work for me quit the way I expected. I would really appreciate if someone could suggest an alternative or what I am doing wrong, or even what I haven't thought of!
**I must also point out that I need to keep the image size same at all times. The only thing that will be different is the actual area of interest in the image. I can probably use the zero/one padding to cover the unused areas.
I believe a solution without making too many copies of the original image would be:
// Make a new IplImage
IplImage* img_src_cpy = cvCreateImage(cvGetSize(img_src), img_src->depth, img_src->nChannels);
// Crop Original Image without changing the ROI
for(int rows = roi.y; rows < roi.height; rows++) {
for(int cols = roi.x; rows < roi.width; cols++) {
img_src_cpy->imageData[(rows-roi.y)*img_src_cpy->widthStep + (cols-roi.x)] = img_src[rows*img_src + cols];
}
{
//Now copy everything to the original image OR simply return the new image if calling from a function
cvCopy(img_src_cpy, img_src); // OR return img_src_cpy;
I tried the code out on itself and it is also fast enough for me (executes in about 1 ms for 332 x 332 Greyscale image)