I want to reduce the depth of an RGB image (24bit) to one byte by reducing the color space and using a color map where each 3-byte triple R/G/B is mapped to a one-byte color map value.
I am therefore looking for a performant way to create a a single-channel Mat (CV8UC1) out of a 3-channel Mat (CV8UC3) using a lookup table. This step is time-critical, as it is done for each frame of a video stream.
The LUT function would be great, but as far as I understand, the resulting Mat will contain was much channels as the input mat had.
Do you have any idea how this could be accomplished?
Related
I wrote a code for watershed segmentation in C API. Now I am converting all those into C++. so, cvsaveimage becomes imwrite. But when I use imwrite ,all i get is a black image.
this is the code:-
Mat img8bit;
Mat img0;
img0 = imread("source.png", 1);
Mat wshed(img0.size(), CV_32S);
wshed.setTo(cv::Scalar::all(0));
////after performing watershed segmentation and
// displaying the watershed image from wshed//
wshed.convertTo(img8bit, CV_32FC3, 255.0);
imwrite("Watershed.png", img8bit);
The original image that I want to save is in wshed. I saw suggestions from the net that we need to convert it to 16 bit or higher so that the imwrite saves it right. Like you see,I tried that. But the wshed image is being displayed correctly when using imshow.The img0 is grey image/black and white while the wshed image is coloured. any help on this?
Edit- I changed the 4th line to
Mat wshed(img0.size(), CV_32FC3);
When calling Mat::convertTo() with a scalar (255 in your case), the values of every matrix item will be multiplied by this scalar value. This will cause all most every result pixel values exceed 255 (i.e. white pixels) except those of 0s where they remain 0 (i.e. black pixels). This is why you will get the black-white pixel in the end.
To make it work, simply change it to:
wshed.convertTo(img8bit, CV_32FC3);
You said:
The original image that I want to save is in wshed. I saw suggestions
from the net that we need to convert it to 16 bit or higher so that
the imwrite saves it right.
If saving the image does not work you should keep in mind that the image data has to be either 8-Bits or 16-Bit unsigned when using the imwrite Function, not 16-Bits or higher.
This is stated in the documentation:
The function imwrite saves the image to the specified file. The image
format is chosen based on the filename extension (see imread() for the
list of extensions). Only 8-bit (or 16-bit unsigned (CV_16U) in case
of PNG, JPEG 2000, and TIFF) single-channel or 3-channel (with ‘BGR’
channel order) images can be saved using this function. If the format,
depth or channel order is different, use Mat::convertTo() , and
cvtColor() to convert it before saving. Or, use the universal
FileStorage I/O functions to save the image to XML or YAML format.
I need to be able to work with images where some regions are grayscale while others are kept on the RGB format. I don't want to convert an image into a grayscale since it will lose the channels and will become simply one channeled, is there a way to keep the RGB channels of some pixels on the picture and turn the others into a grayscale?
NO.
I see two solutions to this:
Have both a gray (Mat1b) and a rgb (Mat3b) image, and work on the image you need.
Have a single rgb (Mat3b) image, and set r,g,b channels to the same gray value where you need. In this way you can mimic to have a mixed gray/rgb image.
I was wondering how to determine the equivalent of RGB values for a grayscale image. The original image is grayscale and everything I have found online is converting an RGB image pixel values to the grayscale pixel values. I already can read in the image. Ideally, this would be for xCode.
I was wondering if there was a class which would do this for me. If so, and you could point me to it, that would be great. I will read on it.
Any help is greatly appreciated.
NOTE: I am a beginner in C++ and do not have time to learn everything formally; I have to learn all of my programming on the fly.
You need more information to transform from a simple Greyscale to RGB, when you do reverse operation, the color information is "lost", as the three channels are set to same value(depending on the algorithm each channel will have a different/same weight in the final color computation).
Digital cameras, usually store more information per pixel, 12 bits per channel in 35mm and 14 bits per channel in medium format (those bits number are the average, some products offer less or even more quality).
Thanks to those additional bits per channel, the camera can compute the "real" color, or what it thinks is the real color based on some parameters.
TL;DR: You can't without more data from your source, in this case the image.
You can convert a gray value to RGB by setting each component of the RGB value to the gray value:
ColorRGB myColorRGB = ColorRGBMake(myGrayValue, myGrayValue, myGrayValue);
I have an array of pixel data in RGBA format. Although I have already converted this data to grayscale using the GPU (thus all 4 channels are identical).
I now want to use this grayscale data in OpenCV, and I don't want to store 4 copies of the same data. Is it possible to create a cv::Mat structure from this pixel array by specifying a stride. (i.e. only read out every 4th byte)
I am currently using
GLubyte* Img = stuff from GPU;
cv::Mat tmp(height, width, CV_8UC4, Img);
But this copies all the data, or does it wrap the existing pointer into a cv::Mat without copying it? If it wraps without copy then I will be happy to use standard c++ routines to copy only the data I want from Img into a new section of memory and then wrap this as cv::Mat.
Otherwise how would you suggest doing this to reduce the amount of data being copied.
Thanks
The code that you are using
cv::Mat tmp(rows, cols, CV_8UC4, dataPointer);
does not perform any copy but only assign the data field of the Mat instance.
If it's ok for you to work with a matrix of 4 channels, then just go on.
Otherwise, if you prefer working with a 1-channel matrix, then just use the function cv::cvtColor() to create a new image with a single channel (but then you will get one additional image in memory and pay the CPU cycles for the conversion):
cv::Mat grey;
cv::cvtColor(tmp, grey, CV_BGR2GRAY);
Finally, one last thing: if you can deinterlace the colorplanes beforehand (for example on the GPU) and get some image with [blue plane, green plane, red plane], then you can pass CV_8UC1 as image type in the construction of tmp and you get a single channel grey image without any data copy.
I have an image which has 4 channels and is in 4 * UINT8 format.
I am trying to convert it to 3 channel float and I am using this code:
images.convertTo(images,CV_32FC3,1/255.0);
After the conversion, the image is in a float format but still has 4 channels. How can I get rid of 4th (alpha) channel in OpenCV?
As #AldurDisciple said, Mat::convertTo() is intended to be used for changing the data type of a Mat, not for changing the number of channels.
To work out, you should split it into two steps:
cvtColor(image, image, CV_BGRA2BGR); // 1. change the number of channels
image.convertTo(image, CV_32FC3, 1/255.0); // 2. change type to float and scale
The function convertTo is intended to be used to change the data type of a Mat, exclusively. As mentionned in the documentation (link), the number of channels of the output image is always the same as the input image.
If you want to change the datatype and reduce the number of channels, you should use a combination of split, merge, and convertTo:
cv::Mat img_8UC4;
cv::Mat chans[4];
cv::split(img_8UC4,chans);
cv::Mat img_8UC3;
cv::merge(chans,3,img_8UC3);
cv::Mat img_32FC3;
img_8UC3.convertTo(img_32FC3);
Another approach may be to recode the algorithm yourself, which is quite easy and probably more efficient.
OpenCV's cvtColor function allows you to convert the type and number of channels of a Mat.
void cvtColor(InputArray src, OutputArray dst, int code, int dstCn=0 )
So something like this would convert a colored 4 channel to a colored 3 channel:
cvtColor(image, image, CV_BGRA2BGR, 3);
Or it is probably more efficient to use the mixChannels function, if you check the documentation its example shows how to split a channel out.
Then if you really want to change it to a specific type:
image.convertTo(image,CV_32F);