I have a series of RGB values I'm working with in Ruby, and I'd like to take those and output an image from them. I've done the processing with RMagick, but it consumes a ton of memory so I was hoping to profile that against other alternatives. Right now I'm just getting the image pixels using the ImageMagick command line convert option to get the pixel data, but I can't seem to figure out how to write the data back out to a new image. How do I take an array of RGB values and write them into a png or jpg image on the filesystem?
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Im trying to learn a segmentation network using CNN, my network is producing very poor results. I looked at the images and I'm wondering if this is the reason. My input images are stack of images in a .tif file. In Windows image viewer below is what I get:
I am trying to detect and segment the bright spots shown above
But when I open the same in Matlab using imshow() I get
All the information is basically lost. However when I use imagesc() I get the following:
Which is much better, but why are my images not working with my network? I am getting very very unpredictable losses and accuracy even with tried and tested networks.
Is it because my image is reading in the version shown in imshow()?
In MATLAB, the following convention is used for images:
uint8: pixels are in the range [0,255].
double: pixels are in the range [0,1].
When using imshow on a double image, values between 0 and 1 are mapped to a color scale (typically black to white). Any value above 1 is also mapped to white. This is what is happening to you: most of your pixels are shown as white.
It is likely that the CNN you are using makes the same assumptions and therefore clips your data.
The solution is to properly scale your images when you read them in. See for example im2double.
Neither imshow nor imagesc is designed to handle tiff stacks. They are for viewing, not reading image data. You may see a warning along the lines of the following, also:
"Can only display one frame from this multiframe file"
You can use imread to read in each of the frames in the file separately, as per this answer, or tiff which is a Matlab gateway to LibTiff library routines and provides more detailed control of how you read in your images if imread doesn't hack it.
I have a 16bit voxel data set from which I need to extract the integer values for each voxel. The data set can be downloaded from here, it is the 'Head Aneuyrism 16Bits' data set (You need to click on the blood vessels image to download the 16bit version). Its size is 512x512x512, but I don't know whether it is greyscale or color, nor if that matters. Looking at the image on the website I'd guess that it is color, but I am not sure whether the image should be taken literally.
A related question on SO is the following: How can I read in a RAW image in MATLAB?
and the following on mathworks: http://www.mathworks.com/matlabcentral/answers/63311-how-to-read-an-n-dimensioned-matrix-from-a-binary-file
Thanks to the information in the answers to these questions I managed to extract some information from the file with matlab as follows:
fileID=fopen('vertebra16.raw','r');
A=fread(fileID,512*512*512,'int16');
B=reshape(A,[512 512 512]);
I don't need to visualise the image, I only need to have the integer values for each voxel, but I am not sure whether I am reading the information in the correct way with my script.
The only way I found to try and check whether I have the correct voxel values is to visualise B using the following:
implay(B)
Now, with the code above, and then using implay(B) I get a black and white movie with a white disc in the center and black background and some black pixels moving in the disc (I tried to upload a frame of the movie, but it didn't work). Looking at the image on the website from which I downloaded the file, the movie frames I get seem quite different from that image, so I'd conclude that I do not have the correct voxel values.
Here are some questions related to my problem:
Do I need to know whether the image is in grey scale or color to read the voxel values correctly?
On the data set website there is only written that the data set is in 16bit format, so how do I know whether I am dealing with signed or unsigned integers?
In the SO question linked to above they use 'uint8=>uint8'. I could not find this in the matlab manual, so I wonder whether 'uint8=>uint8' is an obsolete matlab notation for 'uint8' or if it does something different. I suspect that it does something different since if I use 'int16=>int16' instead of 'int16' in my code above I get a completely black movie with implay.
It looks like you read the data correctly.
The problem when displaying it is the scale of the values. implay seems to assume the values to be in [0,1] and therefore clamps all values to be in that range, where are your data range is [0,3000].
Simply doing
B = B / max(B(:))
will rescale your data to [0,1] and looking at the data again with
implay(B)
shows you something much more sensible.
I am trying to convert an array of RGB values into an array of HSV values in Matlab. I am running the following code:
pic = imread('ColoradoMountains.jpg');
pic = rgb2hsv(pic);
imwrite(pic,'pic.jpg')
But the image that gets written has completely different colors. I've been trying to set the color map to hsv, but I'm not sure if that even makes sense. Nothing on the internet comes up with my keywords, can someone please point me in the right direction?
You can specify the colormap that imwrite is supposed to use. Try this:
imwrite(pic,colormap('HSV'),'pic.png');
Here's the documentation for imwrite: http://www.mathworks.com/help/matlab/ref/imwrite.html
In Matlab you have to distinguish between an indexed image and an 3-channel image. An indexed image is a n*m*1 image where each value of the [0,1] range is associated to a colour. This association is called colour map, which could be for example a unit circle in HSV or RGB. This can be written using imwrite with the map parameter, but this is not what you want.
What you obviously want is an HSV-encoded image, which means the three rgb-channels are converted to three hsv channels. This is (as far as I know) not possible. If you take a look into the documentation of imwrite, you can see how CMYK-Encoded images are written, this is done implicit passing a n*m*4 image. Is there any of the standard file formats which supports HSV? If so I'll take a closer look at this format.
I tried to change some pixel values of a Grayscale image and save it using imwrite in matlab.
no problem with saving.
the problem is when I read it back, some pixel values have been changed. not exactly the same values I assigned to pixels before saving it.
I'm trying to hash images so 1unit difference will effect the hash numbers.
As mentioned by mmgp, JPG can be lossy. That means that some of the information in your image will be lost in favor of storage efficiency.
The rationale behind JPG is somewhat like that behind MP3 -- changes in hues etc. that the human eye is not particularly well-adapted to distinguish will be simplified or removed altogether, thus decreasing the amount of information in the image. The information in a JPG represents a similar-looking, but in fact very different image. This is probably what you're experiencing.
In Matlab, have a look at the output of help imwrite. You can give a parameter to the jpg write called 'Quality', which is a number between 0 and 100, 100 meaning (near-)lossless compression.
Although the JPEG standard does allow for (near-)lossless compression, it is not often used in practice (at least, in my field). More popular lossless image formats are PNG, JPEG2000 and TIFF. Read more about it here.
All of these are also available in Matlab's imwrite function.
I'm trying to encode geometric data in an image file to decode in-browser using Canvas. Beyond what I learned from reading the about the GIF, PNG and BMP formats today, I don't know much about image files (or binary files in general! I grok binary math conversions, but I've never had to interrogate or write binary data without something abstracting it for me).
This Mozilla tutorial (https://developer.mozilla.org/En/HTML/Canvas/Pixel_manipulation_with_canvas) indicates that Canvas reads the image as an array of 8-bit values, every four representing RGBA.
This leads me to believe I want to encode my data as an array of 8-bit values, and put it between an image header and an image footer.
What's the simplest way to do this?