I am creating a GUI containing an image using the following code:
try
Imagenamehere = imread('Imagenamehere.jpg');
axes(handles.Logo)
image(Imagenamehere)
set(gca,'xtick',[],'ytick',[])
catch
msgbox('Please download all contents from the zipped file into working directory.')
end
The image shows up but for some reason is completely coloured blue as if put through a blue filter. I don't think it would be wise to upload the image but it is a simple logo coloured black and white.
Anyone know what could be causing this?
Check the size, type (probably uint8) and range of your image. It sounds like for some reason your images are being displayed with colormap as jet (the default), and possibly also that your range is not what MATLAB expects (e.g. 0 to 1 not 0 to 255), resulting in all your values being relatively low (blue on the jet colormap).
"black and white" is just one way of interpreting an image file which contains only two colors. MATLAB makes several assumptions when you pass data into a display function like image. If you don't specify colormap and image data range, it will make a guess based off things like data type.
One possibility is that your logo file is an indexed image. In these cases you need to do:
[Imagenamehere map] = imread('Imagenamehere.jpg');
colormap(map);
Related
Im 15 and a newbie trying to learn more about image storage. I wrote a script in python to create a bitmap image without any imports. Im familiar with PIL/PILLOW, im not using any imports simply to learn more, as they will not help explain images at a binary level. my issue is that when i try to draw to the image, it gets distorted. For example, the code I've attached should draw out straight rows of black and white lines, but on the image it generates (attached as a png as SO won't attach a .bmp), there are fault lines where the image goes askew.
#The header contains all the metadata of the file, so that it can be scanned and displayed correctly.
#I've attached details of this header to my question
header=[b'\x42',b'\x4d',b'\x18',b'\x31',b'\x0c',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x36',b'\x00',b'\x00',b'\x00',b'\x28',b'\x00',b'\x00',b'\x00',b'\x80',b'\x02',b'\x00',b'\x00',b'\xaa',b'\x01',b'\x00',b'\x00',b'\x01',b'\x00',b'\x18',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00',b'\x00']
#create a file to write the image to, in biinary.
#you may wish to change the file path
with open ("test.bmp","wb") as f:
#first write in the header
for i in range(len(header)):
f.write(header[i])
#now write in the pixel data
#640 is the image width
for x in range(0,640):
#426 is the image height
for y in range(0,426):
#if the row is an even number, make it a white pixel.
if x %2 ==0:
byte_arr=[255,255,255]
#else make it a black pixel.
else:
byte_arr=[0,0,0]
#write the pixel data bytes to the file
some_bytes = bytearray(byte_arr)
immutable_bytes = bytes(some_bytes)
f.write(immutable_bytes)
this article has been very helpful in clearly explaining the bitmap format.
[])
I have been able to change the number of fault lines by changing the number of rows, but i cannot get rid of them entirely. I suspect the problem is in the files meta-data, but ive checked through it and cannot find any bad data. I've attached a (slightly messy) breakdown of the header ive used, which the article also explains in more detail.
I have multiple images in the column portion of a matrix that displays the image if there is one. If there is not an image defined for the image number, the report correctly hides the image (as the BorderColor = Black is not shown) but the white space still remains.
I have tried every possible combination (except the correct one obviously) to no avail.
My objective is to only have the width of the 8 images be 2
Any Ideas?...And splitting the images into individual lines is not an option as it negates the whole premise of using the Matrix.
I have tried placing the hidden code in every possible Hidden field in the report. All postings found all refer to a SINGLE image and not MULTIPLE images.
I already made the image registration, and now I want to apply the registered image in rgb because I need to extract the countourr. As the imregister just work with grayscale images I converted my image to grayscale,but now I can´t find the intensity value of the contour to find the contour indexes. Wat kind of algorithm does imregister applies to the image, tochange the intensity value of the pixels? Or there is another way to go back to the rgb image to extract the inicial countour in the registered image? Does anyone have any sugestion?
There is my matlab code :
% Algorithm for image validation
% Open the two images which will be compared
name2=input('Image name ( automated segmentation) ','s');
img_automated=imread(name2,'png');
figure (1), imshow(img_automated), title('Image automated')
name=input('Image name ( manual segmentation) ','s');
img_manual=imread(name,'png');
img_manual_gray=rgb2gray(img_manual);
%img_manual_gray=img_manual(:,:,3);
figure (2), imshow (img_manual),title('Image manual')
img_automated_gray=rgb2gray(img_automated);
%img_automated_gray=img_automated(:,:,3);
%img_double=im2double(img_automated_gray);
figure (3), imshow (img_automated_gray), title (' Image converted to double ');
%img_automated_gray2=rgb2gray(img_automated);
% View images side by side
figure (6), imshowpair(img_manual,img_automated_eq,'diff')
title('Images overlap')
%% Configure parameters in imreconfig
[optimizer,metric]=imregconfig('Multimodal');
%% Default registration
registered=imregister(img_automated_gray,img_manual_gray,'rigid',optimizer,metric);
%tform = imregtform(img_automated,img_manual,imref2d,'affine',optimizer,metric)
figure(7), imshowpair(registered, img_manual_gray,'falsecolor'); title('Default registration');
figure(8), imshowpair(registered, img_manual_gray,'montage','Scaling','independent'); title('Default registration');
figure(9), imshow(registered);
C = imfuse(registered,img_automated);
figure(21);imshow(C);
%%%%%%%%%%%%%%% Here%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%I tried this process to recover the transformation applied in the registered image,and them aplly this in the initial automated rgb image,but B isn't the same as the registered image. Any suggestions??
tform = imregtform(img_automated_gray,img_manual_gray,'rigid',optimizer,metric);
B = imwarp(img_automated,tform);
figure(22);imshow(B);
Links to the images:
https://www.dropbox.com/s/xbanupnpjaaurj5/manual.png?dl=0 (manual- rgb)
https://www.dropbox.com/s/6fkwi3xbicwzonz/registered%20image.png?dl=0
You are on the right track with your use of imregtform. The missing piece is that imwarp, by default, chooses an output grid with the same resolution as the input grid with limits big enough to capture the entire output image.
In most registration cases, this is not what you want. What you want, is to specify the 'OutputView' Name/Value to specify the resolution and limits that you want in the output grid. In many registration use cases, this is the resolution/limits of the fixed image:
tform = imregtform(img_automated_gray,img_manual_gray,'rigid',optimizer,metric);
B = imwarp(img_automated,tform,'OutputView',imref2d(size(img_manual_gray)));
figure(22);imshow(B);
I'm having an issue with attempting to save some plots with transparent ellipsoids on them if I attempt to save them with .ps/.eps extensions.
Here's the plot saved as a .png:
If I choose to save it as a .ps/.eps here is what it looks like:
How I got around this, was to use ImageMagick to convert the original png to a ps. The only problem is that the image in png format is about 90k, and it becomes just under 4M after conversion. This is not good since I have a lot of these images, and it will take too much time to compile my latex document. Does anyone have a solution to this?
The problem is that eps does not support transparencies natively.
There are few options:
rasterize the image and embed in a eps file (like #Molly suggests) or exporting to pdf and converting with some external tool (like gs) (which usually relies as well on rasterization)
'mimic' transparency, giving a colour that looks like the transparent one on a given background.
I discussed this for sure once on the matplotlib mailing list, and I got the suggestion to rasterize, which is not feasible as you get either pixellized or huge figures. And they don't scale very nicely when put into, e.g., a publication.
I personally use the second approach, and although not ideal, I found it good enough. I wrote a small python script that implements the algorithm from this SO post to obtain a solid RGB representation of a colour with a give transparency
EDIT
In the specific case of your plot try to use the zorder keyword to order the parts plotted. Try to use zorder=10 for the blue ellipse, zorder=11 for the green and zorder=12 for the hexbins.
This way the blue should be below everything, then the green ellipse and finally the hexbins. And the plot should be readable also with solid colors. And if you like the shades of blue and green that you have in png, you can try to play with mimic_alpha.py.
EDIT 2
If you are 100% sure that you have to use eps, there are a couple of workarounds that come to my mind (and that are definitely uglier than your plot):
Just draw the ellipse borders on top of the hexbins.
Get centre and amplitude of each hexagon, (possibly discard all zero bins) and make a scatter plot using the same colour map as in hexbin and adjusting the marker size and shape as you like. You might want to redraw the ellipses borders on top of that
Another alternative would be to save them to pdf
savefig('myfigure.pdf')
That works with pdflatex, if that was the reason why you needed to use eps and not svg.
You can rasterize the figure before saving it to preserve transparency in the eps file:
ax.set_rasterized(True)
plt.savefig('rasterized_fig.eps')
I had the same problem. To avoid rasterizing, you can save the image as a pdf and then run (on unixish systems at least) in a terminal:
pdftops -eps my.pdf my.eps
Which gives a .eps file as output.
I solved this by:
1) adding a set_rasterization_zorder(1) when defining the figure area:
fxsize=16
fysize=8
f = figure(num=None, figsize=(fxsize, fysize), dpi=180, facecolor='w',
edgecolor='k')
plt.subplots_adjust(
left = (18/25.4)/fxsize,
bottom = (13/25.4)/fysize,
right = 1 - (8/25.4)/fxsize,
top = 1 - (8/25.4)/fysize)
subplots_adjust(hspace=0,wspace=0.1)
#f.suptitle('An overall title', size=20)
gs0 = gridspec.GridSpec(1, 2)
gs11 = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=gs0[0])
ax110 = plt.Subplot(f, gs11[0,0])
f.add_subplot(ax110)
ax110.set_rasterization_zorder(1)
2) a zorder=0 in each alpha=anynumber in the plot:
ax110.scatter(xs1,ys1 , marker='o', color='gray' , s=1.5,zorder=0,alpha=0.3)#, label=label_bg)
and
3) finally a rasterized=True when saving:
P.savefig(str(PLOTFILENAME)+'.eps', rasterized=True)
Note that this may not work as expected with the transparent keyword to savefig because an RGBA colour with alpha<1 on transparent background will be rendered the same as the RGB colour with alpha=1.
As mentioned above, the best and easiest choice (if you do not want to loose resolution) is to rasterized the figure
f = plt.figure()
f.set_rasterized(True)
ax = f.add_subplot(111)
ax.set_rasterized(True)
f.savefig('figure_name.eps',rasterized=True,dpi=300)
This way, you can manage the size by dpi option as well. In fact, you can also play with the zorder below you want to apply the rasterization:
ax.set_rasterization_zorder(0)
Note: It is important to keep f.set_rasterized(True) when you use plt.subplot and plt.subplot2grid functions. Otherwise, label and tick area will not appear in the .eps file
My solution is to export the plot as .eps, load it up to Inkscape for example, then Ungroup the plot, select the object that I want to set the transparency and just edit the Opacity of the Fill in the "Fill and Stroke" tab.
You can save the file as .svg if you want to tweak it later, or export the image for a publication.
If you are writing the academic paper in latex, I would recommend you export the .pdf file rather than .eps. The .pdf format supports transparency perfectly and has good compression efficiency, and most importantly, can be easily edited in Adobe Illustrator.
If you wanna further edit the graph (NOT EDITING DATA! I MEAN, FOR GOOD-LOOKING), you could open the exported graph, in Adobe Acrobat - Edit - Copy elements into Adobe Illustrator. The two software can handle everything perfectly.
I work happily with this method. Everything clear, editable and small-size. Hope can help.
I'm currently creating my figures in matlab to embed themvia latex into a pdf for later printing. I save the figures and save them via the script export_fig! Now I wonder which is the best way to go:
Which size of the matlab figure window to chose
Which -m option to take for the script? It will change the resolution and the size of the image...
I'm wondering about those points in regards to the following two points:
When chosing the figure-size bigger, there are more tickmarks shown and the single point markers are better visible
When using a small figure and using a big -m option, I still have only some tickmarks
When I generate a image which is quite huge (e.g. resolution 300 and still 2000*2000px) and than embed it into the document: Does this than look ugly? Will this be embedded in a nice scaling mode or is it the same ugliness as if you upload a 1000*1000px image onto a homepage and embed it via the widht and height tags in html -> the browser displays it quite ugly because the browser doesn't do a real resize. So it looks unsharp and ugly.
Thanks in advance!
The MATLAB plots are internally described as vector graphics, and PDF files are also described using vector graphics. Rendering the plot to a raster format is a bad idea, because you end up having to choose resolution and end up with bigger files.
Just save the plot to EPS format, which can be directly embedded into a PDF file using latex. I usually save my MATLAB plots for publication using:
saveas(gcf, 'plot.eps', 'epsc');
and embed them directly into my latex file using:
\includegraphics[width=0.7\linewidth]{plot.eps}
Then, you only need to choose the proportion of the line the image is to take (in this case, 70%).
Edit: IrfanView and others (XnView) don't display EPS very well. You can open them in Adobe Illustrator to get a better preview of what it looks like. I always insert my plots this way and they always look exactly the same in the PDF as in MATLAB.
One bonus you also get with EPS is that you can actually specify a font size so that the text is readable even when you resize the image in the document.
As for the number of ticks, you can look at the axes properties in the MATLAB documentation. In particular, the XTick and YTick properties are very useful manually controlling how many ticks appear no matter what the window resolution is.
Edit (again): If you render the image to a raster format (such as PNG), it is preferable to choose the exact same resolution as the one used in the document. Rendering a large image (by using a big window size) and making it small in the PDF will yield bad results mainly because the size of the text will scale directly with the size of the image. Rendering a small image will obviously make for a very bad effect because of stretching.
That is why you should use a vector image format. However, the default MATLAB settings for figures produce some of the same problems as raster images: text size is not specified as a font size and the number of ticks varies with the window size.
To produce optimal plots in the final render, follow the given steps:
Set the figure's font size to a decent setting (e.g. 11pt)
Render the plot
Decide on number of ticks to get a good effect and set the ticks manually
Render the image to color EPS
In MATLAB code, this should look somewhat like the following:
function [] = nice_figure ( render )
%
% invisible figure, good for batch renders.
f = figure('Visible', 'Off');
% make plots look nice in output PDF.
set(f, ...
'DefaultAxesFontSize', 11, ...
'DefaultAxesLineWidth', 0.7, ...
'DefaultLineLineWidth', 0.8, ...
'DefaultPatchLineWidth', 0.7);
% actual plot to render.
a = axes('Parent', f);
% show whatever it is we need to show.
render(a);
% save file.
saveas(f, 'plot.eps', 'epsc');
% collect garbarge.
close(f);
end
Then, you can draw some fancy plot using:
function [] = some_line_plot ( a )
%
% render data.
x = -3 : 0.001 : +3;
y = expm1(x) - x - x.^2;
plot(a, x, y, 'g:');
title('f(x)=e^x-1-x-x^2');
xlabel('x');
ylabel('f(x)');
% force use of 'n' ticks.
n = 5;
xlimit = get(a, 'XLim');
ylimit = get(a, 'YLim');
xticks = linspace(xlimit(1), xlimit(2), n);
yticks = linspace(ylimit(1), ylimit(2), n);
set(a, 'XTick', xticks);
set(a, 'YTick', yticks);
end
And render the final output using:
nice_figure(#some_line_plot);
With such code, you don't need to worry about the window size at all. Notice that I haven't even showed the window for you to play with its size. Using this code, I always get beautiful output and small EPS and PDF file sizes (much smaller than when using PNG).
The only thing this solution does not address is adding more ticks when the plot is made larger in the latex code, but that can't be done anyways.