My kmeans() function is failing with the error:
OpenCV Error: Assertion failed (N >= K) in cv::kmeans, file C:\builds\master_Pac
kSlave-win32-vc12-shared\opencv\modules\core\src\kmeans.cpp, line 231
Whats my error? 'N >= K' must mean its checking whether the Mat rows*cols(length) is > clusters - which mine is (I think). My Mat has 1 row with around 80k columns. Is my Mat that I am passing as the first parameter (for kmeans) empty of pixel/voxel data? I have confirmed that this parameter is a 'collapsed' image (1 row, 80K columns). So its not quite empty but it could all that it's all black pixels which may be the error?
Mat image = imread("images/jp.png", CV_32F); // The Jurassic Park movie logo
cvtColor(image, image, CV_BGR2RGB);
Mat collapsedImage = image.reshape(1, 1);
collapsedImage.convertTo(collapsedImage, CV_32F);
int clusterCount = 2;
Mat labels, centres;
// Assertion error thrown here
kmeans(collapsedImage, clusterCount, labels,
TermCriteria(TermCriteria::EPS + TermCriteria::COUNT, 10, 1.0),
3, KMEANS_PP_CENTERS, centres);
imshow("flat", collapsedImage); // shows long flat with all black pixels
imshow("image", image);
Ok looks like the problem was my reshaping. It should be:
Mat collapsedImage = image.reshape(1, image.rows * image.cols);
Related
Problem : Watershed algorithm
I started app project, for image processing, using OpenCv 4.5.3 and Swift ( with C++ ). I'm fighting with watershaded alg. for a really long time... And i have no clue what did i do wrong. Just don't know...
Error :
libc++abi.dylib: terminating with uncaught exception of type cv::Exception: OpenCV(4.5.3)
/Volumes/build-storage/build/master_iOS-mac/opencv/modules/imgproc/src/segmentation.cpp:161:
error: (-215:Assertion failed) src.type()
== CV_8UC3 && dst.type() == CV_32SC1 in function 'watershed'
terminating with uncaught exception of type cv::Exception: OpenCV(4.5.3)
/Volumes/build-storage/build/master_iOS-mac/opencv/modules/imgproc/src/segmentation.cpp:161: error:
(-215:Assertion failed) src.type()
== CV_8UC3 && dst.type() == CV_32SC1 in function 'watershed'
In the definition of openCv's watershed we can find :
#param image Input 8-bit 3-channel image.
#param markers Input/output 32-bit single-channel image (map) of markers. It should have the same size as image .
Code
+(UIImage *) watershed:(UIImage *)src{
cv::Mat img, mask;
UIImageToMat(src, img);
// Change the background from white to black, since that will help later to extract
// better results during the use of Distance Transform
cv::inRange(img, cv::Scalar(255,255,255), cv::Scalar(255,255,255), mask);
img.setTo(cv::Scalar(0,0,0), mask);
// Create a kernel that we will use to sharpen our image
// an approximation of second derivative, a quite strong kernel
cv::Mat kernel = (cv::Mat_<float>(3,3) <<
1, 1, 1,
1, -8, 1,
1, 1, 1);
// do the laplacian filtering as it is
// well, we need to convert everything in something more deeper then CV_8U
// because the kernel has some negative values,
// and we can expect in general to have a Laplacian image with negative values
// BUT a 8bits unsigned int (the one we are working with) can contain values from 0 to 255
// so the possible negative number will be truncated
cv::Mat lapl;
cv::filter2D(img, lapl, CV_32F, kernel);
cv::Mat sharp;
img.convertTo(sharp, CV_32F);
cv::Mat result = sharp - lapl;
// convert back to 8bits gray scale
result.convertTo(result, CV_8UC3);
lapl.convertTo(lapl, CV_8UC3);
cv::Mat bw;
cv::cvtColor(result, bw, cv::COLOR_BGR2GRAY);
cv::threshold(bw, bw, 40, 255, cv::THRESH_BINARY | cv::THRESH_OTSU);
// Perform the distance transform algorithm
cv::Mat dist;
cv::distanceTransform(bw, dist, cv::DIST_L2, cv::DIST_MASK_3);
// Normalize the distance image for range = {0.0, 1.0}
// so we can visualize and threshold it
cv::normalize(dist, dist, 0, 1.0, cv::NORM_MINMAX);
// Threshold to obtain the peaks
// This will be the markers for the foreground objects
cv::threshold(dist, dist, 0.4, 1.0, cv::THRESH_BINARY);
// Dilate a bit the dist image
cv::Mat kernel1 = cv::Mat::ones(3, 3, CV_8U);
dilate(dist, dist, kernel1);
// Create the CV_8U version of the distance image
// It is needed for findContours()
cv::Mat dist_8u;
dist.convertTo(dist_8u, CV_8U);
// Find total markers
std::vector<std::vector<cv::Point> > contours;
findContours(dist_8u, contours, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_SIMPLE);
// Create the marker image for the watershed algorithm
cv::Mat markers = cv::Mat::zeros(dist.size(), CV_32S);
// Draw the foreground markers
for (size_t i = 0; i < contours.size(); i++)
{
drawContours(markers, contours, static_cast<int>(i), cv::Scalar(static_cast<int>(i)+1), -1);
}
// Draw the background marker
circle(markers, cv::Point(5,5), 3, cv::Scalar(255), -1);
cv::Mat markers8u;
markers.convertTo(markers8u, CV_8U, 10);
// Perform the watershed algorithm
watershed(result, markers);
return MatToUIImage(result);
}
You can clearly see, that variables has proper type, as in descr. of function:
result.convertTo(result, CV_8UC3);
cv::Mat markers = cv::Mat::zeros(dist.size(), CV_32S);
The convertTo can not add channels as well can not reduce/convert image to image with smaller amount of channels.
The key in this case is to use :
cvtColor(src, src, COLOR_BGRA2BGR); // change 4 to 3 channels
Here's how I call my image and define my button :
img = imread("lena.jpg");
createButton("Show histogram", showHistCallback, NULL, QT_PUSH_BUTTON, 0);
createButton("Equalize histogram", equalizeCallback, NULL, QT_PUSH_BUTTON, 0);
createButton("Cartoonize", cartoonCallback, NULL, QT_PUSH_BUTTON, 0);
imshow("Input", img);
waitKey(0);
return 0;
I can call and show my image properly. Function Show histogram and equalize histogram also work properly. But when I tried to call Cartoonize, I got this error :
[ WARN:0] global /home/hiro/Documents/OpenCV/opencv-4.3.0-source/modules/core/src/matrix_expressions.cpp (1334)
assign OpenCV/MatExpr: processing of multi-channel arrays might be changed in the future: https://github.com/opencv/opencv/issues/16739
terminate called after throwing an instance of 'cv::Exception'
what():OpenCV(4.3.0) /home/hiro/Documents/OpenCV/opencv-4.3.0-source/modules/core/src/arithm.cpp:669:
error: (-209:Sizes of input arguments do not match)
The operation is neither 'array op array' (where arrays have the same size and the same number of channels), nor 'array op scalar', nor 'scalar op array' in function 'arithm_op'
So I'm guessing my error comes from CartoonCallback function, channel error. I have made sure that my mutiplication is between image of same channels, I converted everything back to 3 channels, yet I can't seem to figure out where the error comes from. Here's the code :
void cartoonCallback(int state, void* userdata){
Mat imgMedian;
medianBlur(img, imgMedian, 7);
Mat imgCanny;
Canny(imgMedian, imgCanny, 50, 150); //Detect edges with canny
Mat kernel = getStructuringElement (MORPH_RECT, Size(2,2));
dilate(imgCanny, imgCanny, kernel); //Dilate image
imgCanny = imgCanny/255;
imgCanny = 1 - imgCanny;
Mat imgCannyf; //use float values to allow multiply between 0 and 1
imgCanny.convertTo(imgCannyf, CV_32FC3);
blur(imgCannyf, imgCannyf, Size(5,5));
Mat imgBF;
bilateralFilter(img, imgBF, 9, 150.0, 150.0); //apply bilateral filter
Mat result = imgBF/25; //truncate color
result = result*25;
Mat imgCanny3c; //Create 3 channels for edges
Mat cannyChannels[] = {imgCannyf, imgCannyf, imgCannyf};
merge(cannyChannels, 3, imgCanny3c);
Mat resultFloat;
result.convertTo(imgCanny3c, CV_32FC3); //convert result to float
multiply(resultFloat, imgCanny3c, resultFloat);
resultFloat.convertTo(result, CV_8UC3); //convert back to 8 bit
imshow("Cartoonize", result);
}
Any suggestion ?
The problem is within this snippet:
cv::Mat resultFloat; // You prepare an output mat... with no dimensions nor type
result.convertTo(imgCanny3c, CV_32FC3); //convert result to float..ok
cv::multiply(resultFloat, imgCanny3c, resultFloat); //resultFloat is empty and has no dimensions!
As you can see, you pass resultFloat to cv::multiply(operand1, operand2, output), but resultFloat is empty, without dimensions nor type and then attempt to multiply it with imgCanny3c. This seems the cause of the error.
I'm new to image processing and development. I need to take the inside triangle pixels of the image. In order to do it I used the following code. Unfortunately I obtain unwanted black pixels. get rid of that problem i tried to remove background[0] pixels by giving alfa value.(tranparent background) But it gives following Error. Any help is appreciated.
My code:
Mat img = cv::imread("/home/fabio/code/lena.jpg", cv::IMREAD_GRAYSCALE);
Mat alpha(img.size(), CV_8UC1, Scalar(0));
//triangle definition (example points)
vector<Point> points;
points.push_back(Point(200, 70));
points.push_back(Point(60, 150));
points.push_back(Point(500, 500));
//apply triangle to mask
fillConvexPoly(alpha, points, Scalar(255));
cv::Mat finalImage = cv::Mat::zeros(img.size(), img.type());
img.copyTo(finalImage, alpha);
imshow("image", finalImage);
Mat dst;
Mat rgb[1];
split(finalImage, rgb);
Mat rgba[2] = { finalImage, alpha };
merge(rgba, 2, dst);
imshow("dst", dst);
Error: OpenCV Error: Bad number of channels (Source image must have 1, 3 or 4 channels) in cvConvertImage, file C:\builds\2_4_PackSlave-win64-vc12-shared\opencv\modules\highgui\src\utils.cpp, line 611
use this instead of your last block:
std::vector<cv::Mat> channels;
cv::split(finalImage,m channels);
if(channels.size() == 0)
{
std::cout << "unexpected error" << std::endl;
return 1;
}
// fill up to reach 3 channels
while(channels,size() < 3)
{
channels.push_back(channels[0]);
}
// add alpha channel
channels.push_back(alpha);
cv::merge(channels, dst);
I didn't test it but this should be what you want?
I'm trying to find corners in my image by Harris Detector, but I have a problem when i run this code:
int blockSize = 2;
int apertureSize = 3;
double k = 0.04;
IplImage* binMaxMatchContourImage = cvCreateImage( cvGetSize(maxMatchContourImage), 8, 1);
IplImage* afterHarrisImage = cvCreateImage( cvGetSize(maxMatchContourImage), 8, 1);
cvCanny(maxMatchContourImage, binMaxMatchContourImage, 50, 200);
cvCornerHarris( binMaxMatchContourImage, afterHarrisImage, blockSize, apertureSize, k);
But my program failed:
OpenCV Error: Bad argument (Unknown array type) in unknown function, file ..\..\..\src\opencv\modules\core\src\matrix.cpp, line 698
Please, explain me, where is my problem?
Check whether maxMatchContourImage is of the same type and size as maxMatchContourImage. Both should be single channel images for Canny edge detection to work.
If this condition is met, cvCornerHarris should work.
I am trying to run kmeans on a 3 channel color image, but every time I try to run the function it seems to crash with the following error:
OpenCV Error: Assertion failed (data.dims <= 2 && type == CV_32F && K > 0) in unknown function, file ..\..\..\OpenCV-2.3.0\modules\core\src\matrix.cpp, line 2271
I've included the code below with some comments to help specify what is being passed in. Any help is greatly appreciated.
// Load in an image
// Depth: 8, Channels: 3
IplImage* iplImage = cvLoadImage("C:/TestImages/rainbox_box.jpg");
// Create a matrix to the image
cv::Mat mImage = cv::Mat(iplImage);
// Create a single channel image to create our labels needed
IplImage* iplLabels = cvCreateImage(cvGetSize(iplImage), iplImage->depth, 1);
// Convert the image to grayscale
cvCvtColor(iplImage, iplLabels, CV_RGB2GRAY);
// Create the matrix for the labels
cv::Mat mLabels = cv::Mat(iplLabels);
// Create the labels
int rows = mLabels.total();
int cols = 1;
cv::Mat list(rows, cols, mLabels .type());
uchar* src;
uchar* dest = list.ptr(0);
for(int i=0; i<mLabels.size().height; i++)
{
src = mLabels.ptr(i);
memcpy(dest, src, mLabels.step);
dest += mLabels.step;
}
list.convertTo(list, CV_32F);
// Run the algorithm
cv::Mat labellist(list.size(), CV_8UC1);
cv::Mat centers(6, 1, mImage.type());
cv::TermCriteria termcrit(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 10, 1.0);
kmeans(mImage, 6, labellist, termcrit, 3, cv::KMEANS_PP_CENTERS, centers);
The error says all: Assertion failed (data.dims <= 2 && type == CV_32F && K > 0)
These are very simple rules to understand, the function will work only if:
mImage.depth() is CV_32F
if mImage.dims is <= 2
and if K > 0. In this case, you define K as 6.
From what you stated on the question, it seems that:
IplImage* iplImage = cvLoadImage("C:/TestImages/rainbox_box.jpg");`
is loading the image as IPL_DEPTH_8U by default and not IPL_DEPTH_32F. This means that mImage is also IPL_DEPTH_8U, which is why your code is not working.