I have an image: to which I have performed segmentation to receive a binary image. I'd like to label each of the objects in the image with different colours. I have the following code so far:
img = imread('lab5a.tif');
BW = imbinarize(img,graythresh(img));
figure; imshowpair(img,BW,'montage')
title ('Opening Operation on Image');
se = strel ('disk', 3);
rem = imclose(BW,se);
figure; imshow (rem, []);
title ('Removed Undesired Features');
CC = bwconncomp(rem);
L = labelmatrix(CC);
RGB = label2rgb(L, spring, 'c', 'shuffle');
figure; imshow(RGB, []);
The output is this image: which is not what I want. It colours the background and the objects are white. I would just like the objects to be of different colours.
Any form of help would be much appreciated!
In your example, the background and foreground of the image are reversed from what you think it should be. The default for the matlab commands is to assume that the higher-value pixels (white) are the foreground or items of interest, while the lower-value pixels (black) are the background. So when you run your example code, the object CC contains only 1 object (the "background" that is blue in your image):
CC =
struct with fields:
Connectivity: 8
ImageSize: [256 256]
NumObjects: 1
PixelIdxList: {[43341×1 double]}
Any easy way to fix this is simply to invert your cleaned up image with the imcomplement command. Add this line to your code:
% invert the image so that the background is black
rem = imcomplement(rem);
Now the CC struct contains 62 objects identified:
CC =
struct with fields:
Connectivity: 8
ImageSize: [256 256]
NumObjects: 62
PixelIdxList: {1×62 cell}
And you will get this image:
If you want to change the colors used for the items, look at the colormap property of the label2rgb command.
Related
I am trying to use gnuplot 5.0 to plot a 2D array of data with no margins or borders or axes... just a 2D image (.png or .jpg) representing some data. I would like to have each array element to correspond to exactly one pixel in the image with no scaling / interpolation etc and no extra white pixels at the edges.
So far, when I try to set the margins to 0 and even using the pixels flag, I am still left with a row of white pixels on the right and top borders of the image.
How can I get just an image file with pixel-by-pixel representation of a data array and nothing extra?
gnuplot script:
#!/usr/bin/gnuplot --persist
set terminal png size 400, 200
set size ratio -1
set lmargin at screen 0
set rmargin at screen 1
set tmargin at screen 0
set bmargin at screen 1
unset colorbox
unset tics
unset xtics
unset ytics
unset border
unset key
set output "pic.png"
plot "T.dat" binary array=400x200 format="%f" with image pixels notitle
Example data from Fortran 90:
program main
implicit none
integer, parameter :: nx = 400
integer, parameter :: ny = 200
real, dimension (:,:), allocatable :: T
allocate (T(nx,ny))
T(:,:)=0.500
T(2,2)=5.
T(nx-1,ny-1)=5.
T(2,ny-1)=5.
T(nx-1,2)=5.
open(3, file="T.dat", access="stream")
write(3) T(:,:)
close(3)
end program main
Some gnuplot terminals implement "with image" by creating a separate png file containing the image and then linking to it inside the resulting plot. Using that separate png image file directly will avoid any issues of page layout, margins, etc. Here I use the canvas terminal. The plot itself is thrown away; all we keep is the png file created with the desired content.
gnuplot> set term canvas name 'myplot'
Terminal type is now 'canvas'
Options are ' rounded size 600,400 enhanced fsize 10 lw 1 fontscale 1 standalone'
gnuplot> set output '/dev/null'
gnuplot> plot "T.dat" binary array=400x200 format="%f" with image
linking image 1 to external file myplot_image_01.png
gnuplot> quit
$identify myplot_image_01.png
myplot_image_01.png PNG 400x200 400x200+0+0 8-bit sRGB 348B 0.000u 0:00.000
Don't use gnuplot.
Instead, write a script that reads your data and converts it into one of the Portable Anymap formats. Here's an example in Python:
#!/usr/bin/env python3
import math
import struct
width = 400
height = 200
levels = 255
raw_datum_fmt = '=d' # native, binary double-precision float
raw_datum_size = struct.calcsize(raw_datum_fmt)
with open('T.dat', 'rb') as f:
print("P2")
print("{} {}".format(width, height))
print("{}".format(levels))
raw_data = f.read(width * height * raw_datum_size)
for y in range(height):
for x in range(width):
raw_datum, = struct.unpack_from(raw_datum_fmt, raw_data, (y * width + x) * raw_datum_size)
datum = math.floor(raw_datum * levels) # assume a number in the range [0, 1]
print("{:>3} ".format(datum), end='')
print()
If you can modify the program which generates the data file, you can even skip the above step and instead generate the data directly in a PNM format.
Either way, you can then use ImageMagick to convert the image to a format of your choice:
./convert.py | convert - pic.png
This should be an easy task, however, apparently it's not.
The following might be a (cumbersome) solution because all other attempts failed. My suspicion is that some graphics library has an issue which you probably cannot solve as a gnuplot user.
You mentioned that ASCII matrix data is also ok. The "trick" here is to plot data with lines where the data is "interrupted" by empty lines, basically drawing single points. Check this in case you need to get your datafile 1:1 into a datablock.
However, if it is not already strange enough, it seems to work for png and gif terminal but not for pngcairo or wxt.
I guess the workaround is probably slow and inefficient but at least it creates the desired output. I'm not sure if there is a limit on size. Tested with 100x100 pixels with Win7, gnuplot 5.2.6. Comments and improvements are welcome.
Code:
### pixel image from matrix data without strange white border
reset session
SizeX = 100
SizeY = 100
set terminal png size SizeX,SizeY
set output "tbPixelImage.png"
# generate some random matrix data
set print $Data2
do for [y=1:SizeY] {
Line = ''
do for [x=1:SizeX] {
Line = Line.sprintf(" %9d",int(rand(0)*0x01000000)) # random color
}
print Line
}
set print
# print $Data2
# convert matrix data into x y z data with empty lines inbetween
set print $Data3
do for [y=1:SizeY] {
do for [x=1:SizeX] {
print sprintf("%g %g %s", x, y, word($Data2[y],x))
print ""
}
}
set print
# print $Data3
set margins 0,0,0,0
unset colorbox
unset border
unset key
unset tics
set xrange[1:SizeX]
set yrange[1:SizeY]
plot $Data3 u 1:2:3 w l lw 1 lc rgb var notitle
set output
### end of code
Result: (100x100 pixels)
(enlarged with black background):
Image with 400x200 pixels (takes about 22 sec on my 8 year old laptop).
What I ended up actually using to get what I needed even though the question / bounty asks for a gnuplot solution:
matplotlib has a function matplotlib.pyplot.imsave which does what I was looking for... i.e. plotting 'just data pixels' and no extras like borders, margins, axes, etc. Originally I only knew about matplotlib.pyplot.imshow and had to pull a lot of tricks to eliminate all the extras from the image file and prevent any interpolation/smoothing etc (and therefore turned to gnuplot at a certain point). With imsave it's fairly easy, so I'm back to using matplotlib for an easy yet still flexible (in terms of colormap, scaling, etc) solution for 'pixel exact' plots. Here's an example:
#!/usr/bin/env python3
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
nx = 400
ny = 200
data = np.fromfile('T.dat', dtype=np.float32, count=nx*ny)
data = data.reshape((nx,ny), order='F')
matplotlib.image.imsave('T.png', np.transpose(data), origin='lower', format='png')
OK, here is another possible solution (I separated it from my first cumbersome approach). It creates the plot immediately, less than a second. No renaming necessary or creation of a useless file.
I guess key is to use term png and ps 0.1.
I don't have a proof but I think ps 1 would be ca. 6 pixels large and would create some overlap and/or white pixels at the corner. Again, for whatever reason it seems to work with term png but not with term pngcairo.
What I tested (Win7, gnuplot 5.2.6) is a binary file having the pattern 00 00 FF repeated all over (I can't display null bytes here). Since gnuplot apparently reads 4 bytes per array item (format="%d"), this leads to an alternating RGB pattern if I am plotting with lc rgb var.
In the same way (hopefully) we can figure out how to read format="%f" and use it together with a color palette. I guess that's what you are looking for, right?
Further test results, comments, improvements and explanations are welcome.
Code:
### pixel image from matrix data without strange white border
reset session
SizeX = 400
SizeY = 200
set terminal png size SizeX,SizeY
set output "tbPixelImage.png"
set margins 0,0,0,0
unset colorbox
unset border
unset key
unset tics
set xrange[0:SizeX-1]
set yrange[0:SizeY-1]
plot "tbBinary.dat" binary array=(SizeX,SizeY) format="%d" w p pt 5 ps 0.1 lc rgb var
### end of code
Result:
I have a 4-channel image (.png, .tif) like this one:
I am using OpenCV, and I would like to add padding of type BORDER_REFLECT around the flower. copyMakeBorder is not useful, since it adds padding to the edges of the image.
I can add certain padding if I split the image in bgr + alpha and apply dilate with BORDER_REFLECT option on the bgr image, but that solution spoils all the pixels of the flower.
Is there any way to perform a selective BORDER_REFLECT padding addition on a ROI defined by a binary mask?
EDIT:
The result I expect is something like (sorry I painted it very quickly with GIMP) :
I painted two black lines to delimit the old & new contour of the flower after the padding, but of course those lines should not appear in the final result. The padding region (inside the two black lines) must be composed by mirrored pixels from the flower (I painted it yellow to make it understandable).
A simple python script to resize the image and copy the original over the enlarged one will do the trick.
import cv2
img = cv2.imread('border_reflect.png', cv2.IMREAD_UNCHANGED)
pad = 20
sh = img.shape
sh_pad = (sh[0]+pad, sh[1]+pad)
imgpad = cv2.resize(img, sh_pad)
imgpad[20:20+sh[0], 20:20+sh[1], :][img[:,:,3]==255] = img[img[:,:,3]==255]
cv2.imwrite("padded_image.png", imgpad)
Here is the result
But that doesn't look very 'centered'. So I modified the code to detect and account for the offsets while copying.
import cv2
img = cv2.imread('border_reflect.png', cv2.IMREAD_UNCHANGED)
pad = 20
sh = img.shape
sh_pad = (sh[0]+pad, sh[1]+pad)
imgpad = cv2.resize(img, sh_pad)
def get_roi(img):
cimg = img[:,:,3].copy()
contours,hierarchy = cv2.findContours(cimg,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
#Remove the tiny pixel noises that get detected as contours
contours = [cnt for cnt in contours if cv2.contourArea(cnt) > 10]
x,y,w,h = cv2.boundingRect(cnt)
roi=img[y:y+h,x:x+w]
return roi
roi = get_roi(img)
roi2 = get_roi(imgpad)
sh = roi.shape
sh2 = roi2.shape
o = ((sh2[0]-sh[0])/2, (sh2[1]-sh[1])/2)
roi2[o[0]:o[0]+sh[0], o[1]:o[1]+sh[1], :][roi[:,:,3]==255] = roi[roi[:,:,3]==255]
cv2.imwrite("padded_image.png", imgpad)
Looks much better now
The issue has been already addressed and solved here:
http://answers.opencv.org/question/90229/add-padding-to-object-in-4-channel-image/
I'm trying to combine the two images based on the information from the mask. I'm using the color information from the background image if the mask is 0 and color information from foreground image if the mask is 1. Because the mask and both
Images are of the same size, I would like to use logical indexing of matrices to achieve this.
My attempt:
mask = imread('mask.png');
foreground = imread('fg.jpg');
background = imread('bg.jpg');
[r,c,~]=size(mask);
A = zeros(size(mask));
for i=1:r
for j=1:c
if mask(i,j) == 0
A(i,j,:) = background(i,j,:);
end
if mask(i,j) > 0
A(i,j,:) = foreground(i,j,:);
end
end
end
imshow(A);
The result looks like a flickering blue image, but I don't want that. Please help.
You can do this a bit more concisely:
f = double(foreground).*double(mask);
b = double(background).*double(~mask);
blend = f+b;
imshow(blend, []);
Using logical indexing you could also do
foreground(logical(mask)) = 0;
background(logical(~mask)) = 0;
blend = foreground+background;
The ISNOT operator '~' inverts your matrix in the second line, so you cut out the area you would like for background.
NOTE: This works for black and white (one channel). For coloured images see rayryeng's solution.
There are two problems with your code. The first problem is that you are trying to assign colour pixels to the output image A, yet this image is only two-dimensional. You want an image with three channels, not two. In addition, the output image type you are specifying is wrong. By default, the output image A is of type double, yet you are copying values into it that aren't double... most likely unsigned 8-bit integer.
As such, cast the image to the same type as the input images. Assuming both input images are the same type, initialize your A so that:
A = zeros(size(foreground), class(foreground));
This correctly makes a colour image with the same type as any of the inputs, assuming that they're both the same type.
Now, your for loop is fine, but it's better if you do this in one shot with logical indexing. If you want to use logical indexing, create a new image that's initially blank like what you've done, but then make sure your mask has three channels to match the number of channels the other images have. After, you simply need to index into each image and set the right locations accordingly:
mask = imread('mask.png');
foreground = imread('fg.jpg');
background = imread('bg.jpg');
[r,c,d]=size(mask); %// Change
%// If your mask isn't three channels, make it so
%// Change
if d ~= 3
mask = cat(3, mask, mask, mask);
end
A = zeros(size(foreground), class(foreground)); %// Change
A(mask) = foreground(mask); %// Assign pixels to foreground
A(~mask) = background(~mask); %// Assign pixels to background
imshow(A);
I am writing a function that generates a movie mimicking a particle in a fluid. The movie is coloured and I would like to generate a grayscaled movie for the start. Right now I am using avifile instead of videowriter. Any help on changing this code to get grayscale movie? Thanks in advance.
close all;
clear variables;
colormap('gray');
vidObj=avifile('movie.avi');
for i=1:N
[nx,ny]=coordinates(Lx,Ly,Nx,Ny,[x(i),-y(i)]);
[xf,yf]=ndgrid(nx,ny);
zf=zeros(size(xf))+z(i);
% generate a frame here
[E,H]=nfmie(an,bn,xf,yf,zf,rad,ns,nm,lambda,tf_flag,cc_flag);
Ecc=sqrt(real(E(:,:,1)).^2+real(E(:,:,2)).^2+real(E(:,:,3)).^2+imag(E(:,:,1)).^2+imag(E(:,:,2)).^2+imag(E(:,:,3)).^2);
clf
imagesc(nx/rad,ny/rad,Ecc);
writetif(Ecc,i);
if i==1
cl=caxis;
else
caxis(cl)
end
axis image;
axis off;
frame=getframe(gca);
cdata_size = size(frame.cdata);
data = uint8(zeros(ceil(cdata_size(1)/4)*4,ceil(cdata_size(2)/4)*4,3));
data(1:cdata_size(1),1:cdata_size(2),1:cdata_size(3)) = [frame.cdata];
frame.cdata = data;
vidObj = addframe(vidObj,frame);
end
vidObj = close(vidObj);
For your frame data, use rgb2gray to convert a colour frame into its grayscale counterpart. As such, change this line:
data(1:cdata_size(1),1:cdata_size(2),1:cdata_size(3)) = [frame.cdata];
To these two lines:
frameGray = rgb2gray(frame.cdata);
data(1:cdata_size(1),1:cdata_size(2),1:cdata_size(3)) = ...
cat(3,frameGray,frameGray,frameGray);
The first line of the new code will convert your colour frame into a single channel grayscale image. In colour, grayscale images have all of the same values for all of the channels, which is why for the second line, cat(3,frameGray,frameGray,frameGray); is being called. This stacks three copies of the grayscale image on top of each other as a 3D matrix and you can then write this frame to your file.
You need to do this stacking because when writing a frame to file using VideoWriter, the frame must be colour (a.k.a. a 3D matrix). As such, the only workaround you have if you want to write a grayscale frame to the file is to replicate the grayscale image into each of the red, green and blue channels to create its colour equivalent.
BTW, cdata_size(3) will always be 3, as getframe's cdata structure always returns a 3D matrix.
Good luck!
I am modifying images in matlab and I have a problem.
I need to separate the 3 channels of color and modify them separately.
I use this to obtain the three channels:
a = imread('./images/penguins.png');
colorlist = {'R','G','B'};
subplot(2,2,1);
imshow(a);
for k=1:3
subplot(2,2,k+1);
imshow( a(:,:,k));
title(colorlist{k});
end
a(:,:,k) is one color of the three. The problem is when I add the three vectors in one, to obtain the color image. I do this:
A=a(:,:,1)+a(:,:,2)+a(:,:,3)
figure; imshow(A);
But it dont works, it only show me a very highlight image, no a color image.
Anyone knows how can I recover the color image? Thanks for yout help^^
You are adding the values of the three layers instead of concatenating them in a 3D array.
Try this:
A= cat(3, a(:,:,1), a(:,:,2), a(:,:,3));
I should also note that you can edit the layers simply by indexing, say you want to switch the red and green components:
I1 = imread('http://i.stack.imgur.com/1KyJA.jpg');
I2=I1;
I2(:,:,1)=I1(:,:,2);
I2(:,:,2)=I1(:,:,1);
imshowpair(I1,I2, 'montage');
Now if I take your title literally, let's say you do want to add the three layers and display the result with a colormap, you can do:
A=a(:,:,1)+a(:,:,2)+a(:,:,3)
imagesc(A); axis image;
colorbar;
Results: