I am trying to copy one image to another pixel by pixel (I know there are sophisticated methods available. I am trying to solve another problem and answer to this will be useful).
This is my code:
int main()
{
Mat Img;
Img = imread("../../../stereo_images/left01.jpg");
Mat copyImg = Mat::zeros(Img.size(), CV_8U);
for(int i=0; i<Img.rows; i++){
for(int j=0; j<Img.cols; j++){
copyImg.at<uchar>(j,i) = Img.at<uchar>(j,i);
}}
namedWindow("Image", CV_WINDOW_AUTOSIZE );
imshow("Image", Img);
namedWindow("copyImage", CV_WINDOW_AUTOSIZE );
imshow("copyImage", copyImg);
waitKey(0);
return 0;
}
When I run this code in visual studio I get the following error
OpenCV Error: Assertion failed (dims <= 2 && data && (unsigned)i0 < (unsigned)si
ze.p[0] && (unsigned)(i1*DataType<_Tp>::channels) < (unsigned)(size.p[1]*channel
s()) && ((((sizeof(size_t)<<28)|0x8442211) >> ((DataType<_Tp>::depth) & ((1 << 3
) - 1))*4) & 15) == elemSize1()) in cv::Mat::at, file c:\opencv\opencv-2.4.9\ope
ncv\build\include\opencv2\core\mat.hpp, line 537
I know for fact that Img's type is CV_8U. Why does this happen ?
Thanks!
// will read in a rgb image , no matter what the content is
Img = imread("../../../stereo_images/left01.jpg");
to make it read grayscale images use:
Img = imread("../../../stereo_images/left01.jpg", CV_LOAD_IMAGE_GRAYSCALE);
then, you don't need to copy per pixel (and you should even avoid that), just use:
Mat im2 = Img.clone();
if you do per-pixel loops, watch out to get the indices right. it's row-col world here, not x,y, so it should be:
copyImg.at<uchar>(i,j) = Img.at<uchar>(i,j);
in your case
I know for fact that Img's type is CV_8U.
But CV_8U is just the image depth (8-bit U-nsigned). The type also specifies the number of channels, which is usually three. One for blue, one for green and one for red in this order as default for OpenCV. The type would be CV_8UC3 (C-hannels = 3). imread will convert even a black and white image to a 3-channel image by default. imread(filename, CV_LOAD_IMAGE_GRAYSCALE) will load a 1-channel image (CV_8UC1). But if you're not sure the easiest solution is
Mat copyImg = Mat::zeros(Img.size(), Img.type());
To access the array elements you have to know the size of it. Using .at<uchar>() on a 3-channel image will only access the first channel because you have 3*8 bit per pixel. So on a 3-channel image you have to use
copyImg.at<Vec3b>(i,j) = Img.at<Vec3b>(i,j);
where Vec3b is a cv::Vec<uchar, 3>. You should also note that the first argument of at<>(,) is the index along dim 0 which are the rows and second argument cols. Or in other words in classic 2d-xy-chart order you access a pixel with .at<>(y,x) == .at<>(Point(x,y)).
your problem is with this line :
copyImg.at<uchar>(j,i) = Img.at<uchar>(j,i);
It should be :
copyImg.at<uchar>(i,j) = Img.at<uchar>(i,j);
Note that if you want to copy image you can simply do this :
Mat copyImg = Img.clone();
Related
I'm attempting to read the pixels in an image and convert them into another format by iterating through the pixels.
After my conversion I only seem to be getting 1/3rd of the image and I'm certain it's because of the way I'm accessing the pixels using the .at() function.
I'm reading in the following image:
Mat image = imread("cameraman.jpg");
I then iterate through the images rows and columns:
for (int i = 0; i < image.rows; i++)
{
for (int j = 0; j < image.cols; j++)
{
placeGrayValue((double)image.at<uchar>(i, j));
}
}
Note: placedGrayValue() is just a placeholder here so that I can share only the code that is relevant.
The resulting image is only the first third of the image:
You're loading your image with cv::imread, which with default value (cv::IMREAD_COLOR) will load it as a 3 channel image of type CV_8UC3 (aka cv::Mat3b).
If your original image is grayscale, when loading as a 3 channel image you have the same intensity value for each channel.
So when you scan the image you should access pixels with .at<cv::Vec3b>(...).
If you want to copy only the first channel to the placeGrayValue matrix you should do it as:
placeGrayValue((double)image.at<cv::Vec3b>(i, j)[0]);
^^^^^^^^^ ^^^
3 channel first channel
If your input is not a grayscale image, then you shouldn't just copy the first channel, since the grayscale value is a linear combination of the three R,G,B channels.
So it's better to first convert to grayscale, and then copy:
cv::Mat grayscale;
cv::cvtColor(image, grayscale, cv::COLOR_BGR2GRAY);
...
placeGrayValue((double)grayscale.at<uchar>(i, j));
^^^^^
1 channel
Or you can load the image already as a grayscale image:
Mat grayscale = imread("cameraman.jpg", cv::IMREAD_GRAYSCALE);
At the end, you want to have placeGrayValue with the grayscale values as double.
You should not scan the image for this kind of easy operations. You can just:
cv::Mat placeGrayValue;
grayscale.convertTo(placeGrayValue, CV_64F);
^^^^^^
to double type
Summing up:
cv::Mat grayscale = cv::imread("cameraman.jpg", cv::IMREAD_GRAYSCALE);
cv::Mat placeGrayValue;
grayscale.convertTo(placeGrayValue, CV_64F);
I'll post what ended up working as an answer, though it makes little sense to me and I'd still like to understand why.
The image has 3 channels. When iterate through an image using a for loop and extract pixel data with (double)image.at<uchar>(i, j) it goes through each channel as if they were individual pixels.
The solution (at least with this grayscale image) is to iterate and multiply by 3. In other words, (double)image.at<uchar>(i*3, j) ended up giving me the full image.
I'm using an STMap to map a .jpg image using remap().
I loaded my STMap, split the channels and converted each channel matrix to CV_32FC1.
I checked them and it worked - each matrix displays correctly and all of its values are between 0.0 and 1.0.
However, when i try to use the remap() function:
Mat dst;
remap(image4, dst,map_x,map_y,INTER_LINEAR,BORDER_CONSTANT,Scalar(0,0,0));
imshow( "Result", dst );
It just displays a black image.
image4 = my .jpg image
map_x = grayscale CV_32FC1 (red channel
of the original STMap)
map_y = grayscale CV_32FC1 (green channel
of the original STMap)
What could be the problem?
Thanks!
Black image when using cv::remap is due to using offsets instead of absolute locations in the passed map(s).
Optical flow algorithms usually export motion vectors, not absolute positions, whereas cv::remap expects the absolute coordinate (subpixel) to sample from.
To convert between the two, starting with a CV_32FC2 flow matrix we can do something like this:
// Convert from offsets to absolute locations.
Mat mapx(flow.size(), CV_32FC1);
Mat mapy(flow.size(), CV_32FC1);
for (int row = 0; row < flow.rows; row++)
{
for (int col = 0; col < flow.cols; col++)
{
Point2f f = flow.at<Point2f>(row, col);
mapx.at<float>(row, col) = col + f.x;
mapy.at<float>(row, col) = row + f.y;
}
}
Then mapx and mapy can be used in remap.
I want to ask if it is possible to access single channel matrix using img.at<T>(y, x) instead using img.ptr<T>(y, x)[0]
In the example below, I create a simple program to copy an image to another
cv::Mat inpImg = cv::imread("test.png");
cv::Mat img;
inpImg.convertTo(img, CV_8UC1); // single channel image
cv::Mat outImg(img.rows, img.cols, CV_8UC1);
for(int a = 0; a < img.cols; a++)
for(int b = 0; b < img.rows; b++)
outImg.at<uchar>(b, a) = img.at<uchar>(b, a); // This is wrong
cv::imshow("Test", outImg);
The shown result was wrong, but if I change it to
outImg.ptr<uchar>(b, a)[0] = img.ptr<uchar>(b, a)[0];
The result was correct.
I'm quite puzzled since using img.at<T>(y, x) should also be okay. I also tried with 32FC1 and float, the result is similar.
Although I know you already found it, the real reason - buried nicely in the documentation - is that cv::convertTo ignores the number of channels implied by the output type, so when you do this:
inpImg.convertTo(img, CV_8UC1);
And, assuming your input image has three channels, you actually end up with a CV_8UC3 format, which explains why your initial workaround was successful - effectively, you only took a single channel by doing this:
outImg.ptr<uchar>(b, a)[0] // takes the first channel of a CV_8UC3
This only worked by accident as the pixel should have been accessed like this:
outImg.ptr<Vec3b>(b, a)[0] // takes the blue channel of a CV_8UC3
As the data is still packed uchar in both cases, the effective reinterpretation happened to work.
As you noted, you can either convert to greyscale on loading:
cv::imread("test.png", CV_LOAD_IMAGE_GRAYSCALE)
Or, you can convert explicitly:
cv::cvtColor(inpImg, inpImg, CV_BGR2GRAY);
I just want to get my concept clear that - is accessing all the matrix elements of cv::Mat means I am actually accessing all the pixel values of an image (grayscale - 1 channel and for colour - 3 channels)? Like suppose my code for printing the values of matrix of gray scale that is 1 channel image loaded and type CV_32FC1, is as shown below, then does that mean that I am accessing only the members of the cv::mat or I am accessing the pixel values of the image (with 1 channel - grayscale and type CV_32FC1) also?
cv::Mat img = cv::imread("lenna.png");
for(int j=0;j<img.rows;j++)
{
for (int i=0;i<img.cols;i++)
{
std::cout << "Matrix of image loaded is: " << img.at<uchar>(i,j);
}
}
I am quite new to image processing with OpenCV and want to clear my idea. If I am wrong, then how can I access each pixel value of an image?
You are accessing the elements of the matrix and you are accessing the image itself also. In your code, after you do this:
cv::Mat img = cv::imread("lenna.png");
the matrix img represents the image lenna.png. ( if it is successfully opened )
Why don't you experiment yourself by changing some of the pixel values:
cv::Mat img = cv::imread("lenna.png");
//Before changing
cv::imshow("Before",img);
//change some pixel value
for(int j=0;j<img.rows;j++)
{
for (int i=0;i<img.cols;i++)
{
if( i== j)
img.at<uchar>(j,i) = 255; //white
}
}
//After changing
cv::imshow("After",img);
Note: this only changes the image values in volatile memory, that is where the mat img is currently loaded. Modifying the values of the mat img, not going to change value in your actual image "lenna.png",which is stored in your disk, (unless you do imwrite)
But in case of 1-channel grayscale image it is CV_8UC1 not CV_32FC1
In order to get the pixel value of the grayscale image (an integer between 0 and 255), the answer also needs to be typecasted.
int pixelValue = (int)img.at<uchar>(i,j);
I am using Ubuntu 12.04 and OpenCV 2
I have written the following code :
IplImage* img =0;
img = cvLoadImage("nature.jpg");
if(img != 0)
{
Mat Img_mat(img);
std::vector<Mat> RGB;
split(Img_mat, RGB);
int data = (RGB[0]).at<int>(i,j)); /*Where i, j are inside the bounds of the matrix size .. i have checked this*/
}
The problem is I am getting negative values and very large values in the data variable. I think I have made some mistake somewhere. Can you please point it out.
I have been reading the documentation (I have not finished it fully.. it is quite large. ) But from what I have read, this should work. But it isnt. What is going wrong here?
Img_mat is a 3 channeled image. Each channel consists of pixel values uchar in data type.
So with split(Img_mat, BGR) the Img_mat is split into 3 planes of blue, green and red which are collectively stored in a vector BGR. So BGR[0] is the first (blue) plane with uchar data type pixels...hence it will be
int dataB = (int)BGR[0].at<uchar>(i,j);
int dataG = (int)BGR[1].at<uchar>(i,j);
so on...
You have to specify the correct type for cv::Mat::at(i,j). You are accessing the pixel as int, while it should be a vector of uchar. Your code should look something like this:
IplImage* img = 0;
img = cvLoadImage("nature.jpg");
if(img != 0)
{
Mat Img_mat(img);
std::vector<Mat> BGR;
split(Img_mat, BGR);
Vec3b data = BGR[0].at<Vec3b>(i,j);
// data[0] -> blue
// data[1] -> green
// data[2] -> red
}
Why are you loading an IplImage first? You are mixing the C and C++ interfaces.
Loading a cv::Mat with imread directly would be more straight-forward.
This way you can also specify the type and use the according type in your at call.