My aim is to generate a histogram for a gray-scale image. The code I used is :
Mat img = imread("leeds-castle.jpg",IMREAD_GRAYSCALE);
Mat hst;
int hstsize = 256;
float ranges[] = { 0,256 };
float *hstrange = { ranges };
calcHist( img, 1,0, Mat(), hst, 1, &hstsize,&hstrange,true,false);
int hst_w = 512, hst_h = 400;
int bin_w = cvRound((double)hst_w / 256);
Mat histimg(hst_w, hst_h, CV_8U);
normalize(hst, hst, 0, histimg.rows, NORM_MINMAX, -1, Mat());
for (int i = 1; i < 256; i++)
{
line(histimg, Point(bin_w*(i - 1), hst_h - cvRound(hst.at<float>(i - 1))), Point(bin_w*i, hst_h - cvRound(hst.at<float>(i))), 2, 8, 0);
}
imshow("Histogram", histimg);
The only error is the usage of calcHist() function. Is there anything wrong with it?
See the comment above calcHist to identify the correct usage:
// original image
Mat img = imread("leeds-castle.jpg",IMREAD_GRAYSCALE);
// NOTE: check if img.channels is equal to 1
// histogram
Mat hst;
// number of bins
int hstsize = 256;
float ranges[] = { 0,256 };
float *hstrange = { ranges };
// parameters for histogram calculation
bool uniform = true;
bool accumulate = false;
// calculate histogram
// the '&' was missing here
calcHist( &img, 1,0, Mat(), hst, 1, &hstsize,&hstrange,true,false);
Related
I use a FLIR Camera (Grasshopper3) and the SDK (Spinnaker) to take an image (Mono8). After converting the image, I wuold like to compute the Histogram and display it in my GUI in a picturebox (C++ CLR/CLI .net environment). For this, I need to convert it, but I guess there is a mistake in the color conversion or the BitMap creation.
Here is the code:
Spinnaker::ImagePtr convertedImage_MONO = Grasshopper3.pResultImage_MONO->Convert(Spinnaker::PixelFormat_Mono8, Spinnaker::NO_COLOR_PROCESSING); // Raw image is converted to Mono8
unsigned int XPadding = convertedImage_MONO->GetXPadding();
unsigned int YPadding = convertedImage_MONO->GetYPadding();
unsigned int rowsize = convertedImage_MONO->GetWidth();
unsigned int colsize = convertedImage_MONO->GetHeight();
//image data contains padding. When allocating Mat container size, you need to account for the X,Y image data padding.
cv::Mat cvimg_Mono = cv::Mat(colsize + YPadding, rowsize + XPadding, CV_8UC1, convertedImage_MONO->GetData(), convertedImage_MONO->GetStride());
cvtColor(cvimg_Mono, cvimg_Mono, cv::COLOR_BGR2BGRA);
// Histogram
int bins = 256;
int histSize[] = { bins };
// Set ranges for histogram bins
float lranges[] = { 0, 256 };
const float* ranges[] = { lranges };
// create matrix for histogram
cv::Mat hist;
int channels[] = { 0 };
// create matrix for histogram visualization
int const hist_height = 256;
cv::Mat3b hist_image = cv::Mat3b::zeros(hist_height, bins);
cv::calcHist(&cvimg_Mono, 1, channels, cv::Mat(), hist, 1, histSize, ranges, true, false);
double max_val = 0;
minMaxLoc(hist, 0, &max_val);
// visualize each bin
for (int b = 0; b < bins; b++)
{
float const binVal = hist.at<float>(b);
int const height = cvRound(binVal*hist_height / max_val);
cv::line(hist_image, cv::Point(b, hist_height - height), cv::Point(b, hist_height), cv::Scalar::all(255));
}
cv::Mat Histogram_Mono = hist_image;
cv::resize(Histogram_Mono, Histogram_Mono, cv::Size(pictureBox_Mono->Width, pictureBox_Mono->Height), cv::INTER_AREA);
hBit_Mono = CreateBitmap(Histogram_Mono.cols, Histogram_Mono.rows, 1, 32, Histogram_Mono.data); // hBit_Mono was created global
bmp_Mono = Bitmap::FromHbitmap((IntPtr)hBit_Mono); // bmp_Mono was created as a global Bitmap
pictureBox_Mono->Image = bmp_Mono;
Overall goal is to be able to read the histogram from binary image in order to crop the image.
My code works, but for my binary image, histogram is not showing properly (the histogram is blank)
Can anybody tell me whats wrong with my code?
Histogram is working for RGB image as well as Grey image
I would like to be able to get the histogram of the binary image
#include <opencv2/highgui/highgui.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<iostream>
using namespace std;
using namespace cv;
void show_histogram(std::string const& name, cv::Mat1b const& image)
{
// Set histogram bins count
int bins = 255;
int histSize[] = { bins };
// Set ranges for histogram bins
float lranges[] = { 0, 255 };
const float* ranges[] = { lranges };
// create matrix for histogram
cv::Mat hist;
int channels[] = { 0 };
// create matrix for histogram visualization
int const hist_height = 255;
cv::Mat1b hist_image = cv::Mat1b::zeros(hist_height, bins);
cv::calcHist(&image, 1, channels, cv::Mat(), hist, 1, histSize, ranges, true, false);
double max_val = 0;
minMaxLoc(hist, 0, &max_val);
// visualize each bin
for (int b = 0; b < bins; b++) {
float const binVal = hist.at<float>(b);
int const height = cvRound(binVal*hist_height / max_val);
cv::line
(hist_image
, cv::Point(b, hist_height - height), cv::Point(b, hist_height)
, cv::Scalar::all(255)
);
}
cv::imshow(name, hist_image);
}
int main()
{
Mat Rgb;
Mat Grey;
Mat Binary;
//Mat Histogram;
Rgb = imread("license.jpg", WINDOW_AUTOSIZE);
cvtColor(Rgb, Grey, cv::COLOR_BGR2GRAY);
threshold(Grey, Binary, 150, 250, THRESH_BINARY);
//namedWindow("RGB");
//namedWindow("Grey");
namedWindow("Binary");
//imshow("RGB", Rgb);
imshow("Gray", Grey);
imshow("Binary", Binary);
show_histogram("Histogram1", Grey);
show_histogram("Histogram2", Binary);
waitKey(0);
cv::destroyAllWindows();
return 0;
}
I'm struggling with taking the histogram of floating point data in OpenCV:
cv::ocl::setUseOpenCL(true);
auto rows = 2048;
auto cols = 2064;
auto input_d = cv::UMat(rows, cols, CV_32F, cv::USAGE_ALLOCATE_DEVICE_MEMORY);
cv::UMat hist_d;
cv::randn(input_d, 0, 0.5);
std::vector<int> channels = { 0 };
std::vector<int> histSize = { 256 };
std::vector<float> ranges = { 0, 1 };//run the histogram to track values 0 to 1
cv::calcHist(input_d, channels, cv::UMat(), hist_d, histSize, ranges, false);
I'm getting an error like:
OpenCV Error: Assertion failed (0 <= _rowRange.start && _rowRange.start <= _rowRange.end && _rowRange.end <= m.rows) in cv::Mat::Mat, file src\matrix.cpp, line 452
Anybody know how to use this function?
The following code works, but the computation doesn't happen on the GPU
auto rows = 2048;
auto cols = 2064;
auto input_d = cv::Mat(rows, cols, CV_32F);
cv::MatND hist_d;
cv::randn(input_d, 0, 0.5);
int histSize[1] = { 256 };
float hranges[2] = { 0.0, 256.0 };
const float* range[1] = { hranges };
int channels[1] = { 0 };
cv::calcHist(&input_d, 1, channels, cv::Mat(), hist_d, 1, histSize, range);
I suspect that foo should not be size zero, but I don't understand whats going on.
cv::InputArray& foo = input_d;
cv::calcHist(foo, channels, cv::UMat(), hist_d, histSize, ranges, false);
Looks like it needs to be wrapped.
std::vector<cv::UMat> foo = { input_d };// should ref count, and avoid a deep copy?
cv::calcHist(foo, channels, cv::UMat(), hist_d, histSize, ranges, false);
Here's how I've been able to do it with cv::UMat:
std::vector<int> channels = { 0 };
std::vector<int> histSize = { 256 };
std::vector<float> range = { 0, 256 };
std::vector<cv::UMat> foo = { oInputMat };
cv::calcHist(foo, channels, cv::UMat(), oHistogram, histSize, range, false);
I am trying to plot Histogram of lenna here the 8 bit single ch. gray scale image.
But it is not displaying the output correctly, as can be seen in the following output:
void show_histogram_image(Mat img1)
{
int sbins = 256;
int histSize[] = {sbins};
float sranges[] = { 0, 256 };
const float* ranges[] = { sranges };
cv::MatND hist;
int channels[] = {0};
cv::calcHist( &img1, 1, channels, cv::Mat(), // do not use mask
hist, 1, histSize, ranges,
true, // the histogram is uniform
false );
double maxVal=0;
minMaxLoc(hist, 0, &maxVal, 0, 0);
int xscale = 10;
int yscale = 10;
cv::Mat hist_image;
hist_image = cv::Mat::zeros(256, sbins*xscale, CV_8UC1);
for( int s = 0; s < sbins; s++ )
{
float binVal = hist.at<float>(s, 0);
int intensity = cvRound(binVal*255/maxVal);
rectangle( hist_image, cv::Point(s*xscale, 0),
cv::Point( (s+1)*xscale - 1, intensity),
cv::Scalar::all(255),
CV_FILLED );
}
imshow("Image1",hist_image);
waitKey(0);
}
Here is my main();
int main()
{
Mat img1 = imread("lena512.bmp", CV_8UC1);
if (img1.empty()) //check whether the image is valid or not
{
cout << "Error : Image cannot be read..!!" << endl;
system("pause"); //wait for a key press
return -1;
}
show_histogram_image(img1);
}
And here is the output Histogram image:
I tried changing the xscale even then it is not coming correctly.
Update
I made the following changes:
rectangle( hist_image, cv::Point(s*xscale, hist_image.rows),
cv::Point( (s+1)*xscale - 1, hist_image.rows - intensity),
cv::Scalar::all(255), CV_FILLED );
And now the output is:
It is much better , but I need lines and clearly visible bins. And it looks like some part is hidden on the right side.
Update 2
I changed CV_FILLED to '1' and now I have:
since the image origin in opencv is (0,0), and thus the y-axis is pointing downwards,
you will have to invert the y-values for your histogram-drawing:
rectangle( hist_image, cv::Point(s*xscale, hist_image.rows),
cv::Point( (s+1)*xscale - 1, hist_image.rows - intensity),
cv::Scalar::all(255),
CV_FILLED );
I am a beginner in openCV.
I want to plot the intensity profile for R, G and B for the image given below.
I am like to plot R, G and B values w.r.t to pixel location in three different graphs.
So far I have learnt how to read an Image and display. for example using imread();
Mat img = imread("Apple.bmp");
and then showing it on the screen using imshow(" Window", img);.
Now I would like to put all R , G and B values in 3 separate buffers; buf1, buf2, buf3 and plot these values.
Kindly provide me some hint or a sample code snippet to help me understand this.
You can separate R, G and B into separate Mats using cv::split()
std::vector<Mat> planes(3);
cv::split(img, planes);
cv::Mat R = planes[2];
cv::Mat G = planes[1];
cv::Mat B = planes[0];
But you only need to separate them like this if you have code that is expecting a Mat with a single color channnel.
Don't use at<>() as the supposed duplicate suggest - it is really slow if you are sequentially scanning an image (but it is good for random access).
You can scan the image efficiently like this
for(int i = 0; i < img.rows; ++i)
{
// get pointers to each row
cv::Vec3b* row = img.ptr<cv::Vec3b>(i);
// now scan the row
for(int j = 0; j < img.cols; ++j)
{
cv::Vec3b pixel = row[j];
uchar r = pixel[2];
uchar g = pixel[1];
uchar b = pixel[0];
process(r, g, b);
}
}
Lastly if you do want to make a histogram, you can use this code. It is fairly old so I suppose it still works.
void show_histogram_image(cv::Mat src, cv::Mat &hist_image)
{ // based on http://docs.opencv.org/2.4.4/modules/imgproc/doc/histograms.html?highlight=histogram#calchist
int sbins = 256;
int histSize[] = {sbins};
float sranges[] = { 0, 256 };
const float* ranges[] = { sranges };
cv::MatND hist;
int channels[] = {0};
cv::calcHist( &src, 1, channels, cv::Mat(), // do not use mask
hist, 1, histSize, ranges,
true, // the histogram is uniform
false );
double maxVal=0;
minMaxLoc(hist, 0, &maxVal, 0, 0);
int xscale = 10;
int yscale = 10;
//hist_image.create(
hist_image = cv::Mat::zeros(256, sbins*xscale, CV_8UC3);
for( int s = 0; s < sbins; s++ )
{
float binVal = hist.at<float>(s, 0);
int intensity = cvRound(binVal*255/maxVal);
rectangle( hist_image, cv::Point(s*xscale, 0),
cv::Point( (s+1)*xscale - 1, intensity),
cv::Scalar::all(255),
CV_FILLED );
}
}