I am new in learning OpenCV. While I was searching for good algorithm to remove noise I found this Function but I have no idea how to use it, so is this function available in OpenCV libraries? If yes, how can I use it.
void fastNlMeansDenoisingColored(InputArray src, OutputArray dst, float h=3, float hColor=3, int templateWindowSize=7, int searchWindowSize=21 )
This is from the opencv documentation. Therefore try using that function.
A snippet of code I found online may be able to help you:
#include <iostream>
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace std;
using namespace cv;
int main() {
Mat img = imread("a.jpg");
if (!img.data) {
cout << "No image found" << endl;
return -1;
}
// first copy the image
Mat img_gray = img.clone();
cvtColor(img, img_gray, CV_RGB2GRAY);
Mat img1;
cv::fastNlMeansDenoising(img_gray, img1, 3.0, 7, 21);
imshow("img1", img1);
waitKey();
return 0;
}
Hope it helps!
Related
trying to apply the Otsu threshold to single component "L" of LAB color space. But I can not figure out, how to specify it in OpenCV syntactically.
C++ code splits the Lab image into the separate channels.
#include <iostream>
using namespace std;
#include <opencv2/opencv.hpp>
using namespace cv;
#pragma comment(lib, "opencv_world340.lib")
int main(void)
{
Mat img = imread("star.png", 1);
if (img.empty())
{
cout << "Could not read image file." << endl;
return 1;
}
Mat Lab;
Mat Lab_channels[3];
cvtColor(img, Lab, COLOR_BGR2Lab);
split(Lab, Lab_channels);
threshold(Lab_channels[0], Lab_channels[0], 127, 255, THRESH_OTSU);
return 0;
}
This C++ code uses extract channel to get just the first channel (channel 0).
#include <iostream>
using namespace std;
#include <opencv2/opencv.hpp>
using namespace cv;
#pragma comment(lib, "opencv_world340.lib")
int main(void)
{
Mat img = imread("star.png", 1);
if (img.empty())
{
cout << "Could not read image file." << endl;
return 1;
}
Mat Lab;
Mat Lab_channel_0;
cvtColor(img, Lab, COLOR_BGR2Lab);
extractChannel(Lab, Lab_channel_0, 0);
threshold(Lab_channel_0, Lab_channel_0, 127, 255, THRESH_OTSU);
return 0;
}
Try this.
I am using opencv 3.3.0
my code is
#include <stdio.h>
#include <iostream>
#include "opencv2/core.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/features2d.hpp"
#include "opencv2/xfeatures2d.hpp"
#include <fstream>
#include <string>
#include <vector>
using namespace cv;
using namespace std;
using namespace cv::xfeatures2d;
int main(int argc, char** argv)
{
Mat img1;
img1 = imread("img/img1.jpg", IMREAD_GRAYSCALE);
if (img1.empty())
{
cout << "Could not open or find the image" << endl;
return -1;
}
Ptr<SurfFeatureDetector> detector = SurfFeatureDetector::create(400);
vector<KeyPoint> keypoints;
detector->detect(img1, keypoints);
imshow("img1", img1);
waitKey(0);
return 0;
}
I am new to C++ and opencv. The code work well without surf part.
error
OpenCV Error: Assertion failed (TlsSetValue(tlsKey, pData) == TRUE) in cv::TlsAbstraction::SetData, file C:\Users\Darshana\Documents\opencv\opencv-3.3.0\modules\core\src\system.cpp, line 1270
I have tried with Ptr<SURF> detector = SURF::create(400); as well.
UPDATE
I couldn't figure out a solution for this. Maybe a setup issue or library issue. So I just move to opencv 2.4.13 and now everything works fine. I had to change the above code to work with v2.4.13 though.
You haven't set parameter for SurfFeatureDetector. I think you should try this instead:
int minHessian = 400;
SurfFeatureDetector detector(minHessian);
vector<KeyPoint> keypoints;
detector.detect(img1, keypoints);
Im working on a simple face detector using Visual Studio 2017 with OpenCV 3.2.0 and haarcascades.
Whenever i run this, i get an error saying there's an exception thrown right after i create the first point. Access violation error. Any help would be greatly appreciated as I do not see any error in the code.
#include <opencv2/opencv.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <iostream>
#include <stdio.h>
#include <vector>
using namespace std;
using namespace cv;
int main()
{
CascadeClassifier face_cascade;
CascadeClassifier eye_cascade;
face_cascade.load("haarcascade_frontalface_alt.xml");
eye_cascade.load("haarcascade_eye_tree_eyeglasses.xml");
VideoCapture cap(0);
Mat frame;
while (cap.read(frame))
{
Mat frame_gray;
std::vector <Rect> faces;
cvtColor(frame, frame_gray, COLOR_BGR2GRAY);
equalizeHist(frame_gray, frame_gray);
face_cascade.detectMultiScale(frame_gray,faces, 1.1, 2,0,Size(30,30),Size(300,300));
for (size_t i = 0; i < faces.size();i++)
{
Point first(faces[i].x, faces[i].y);
Point second(faces[i].x + faces[i].width, faces[i].y + faces[i].height);
rectangle(frame,second,first, cvScalar(255, 0, 0), 1, 8, 0);
}
imshow("Test", frame_gray);
waitKey(30);
}
return 0;
}
I have found a program which can binarize an image and make the image monochrome
OpenCV Adaptive Threshold OCR
I have copy/pasted the code
#include <iostream>
#include <vector>
#include <stdio.h>
#include <stdarg.h>
#include "/usr/include/opencv2/opencv.hpp"
#include "fstream"
#include "iostream"
using namespace std;
using namespace cv;
void CalcBlockMeanVariance(Mat& Img,Mat& Res,float blockSide=21) // blockSide - the parameter (set greater for larger font on image)
{
Mat I;
Img.convertTo(I,CV_32FC1);
Res=Mat::zeros(Img.rows/blockSide,Img.cols/blockSide,CV_32FC1);
Mat inpaintmask;
Mat patch;
Mat smallImg;
Scalar m,s;
for(int i=0;i<Img.rows-blockSide;i+=blockSide)
{
for (int j=0;j<Img.cols-blockSide;j+=blockSide)
{
patch=I(Range(i,i+blockSide+1),Range(j,j+blockSide+1));
cv::meanStdDev(patch,m,s);
if(s[0]>0.01) // Thresholding parameter (set smaller for lower contrast image)
{
Res.at<float>(i/blockSide,j/blockSide)=m[0];
}else
{
Res.at<float>(i/blockSide,j/blockSide)=0;
}
}
}
cv::resize(I,smallImg,Res.size());
cv::threshold(Res,inpaintmask,0.02,1.0,cv::THRESH_BINARY);
Mat inpainted;
smallImg.convertTo(smallImg,CV_8UC1,255);
inpaintmask.convertTo(inpaintmask,CV_8UC1);
inpaint(smallImg, inpaintmask, inpainted, 5, INPAINT_TELEA);
cv::resize(inpainted,Res,Img.size());
Res.convertTo(Res,CV_32FC1,1.0/255.0);
}
int main( int argc, char** argv )
{
namedWindow("Img");
namedWindow("Edges");
//Mat Img=imread("D:\\ImagesForTest\\BookPage.JPG",0);
Mat Img=imread("Test2.JPG",0);
Mat res;
Img.convertTo(Img,CV_32FC1,1.0/255.0);
CalcBlockMeanVariance(Img,res);
res=1.0-res;
res=Img+res;
imshow("Img",Img);
cv::threshold(res,res,0.85,1,cv::THRESH_BINARY);
cv::resize(res,res,cv::Size(res.cols/2,res.rows/2));
imwrite("result.jpg",res*255);
imshow("Edges",res);
waitKey(0);
return 0;
}
compile
g++ binarize.cpp `pkg-config opencv --cflags --libs`
run
./a.out
error
(Img:27277): Gtk-WARNING **: cannot open display:
update
int main( int argc, char** argv )
{
namedWindow("Img");
namedWindow("Edges");
//Mat Img=imread("D:\\ImagesForTest\\BookPage.JPG",0);
Mat Img=imread("Test2.JPG",0);
Mat res;
Img.convertTo(Img,CV_32FC1,1.0/255.0);
CalcBlockMeanVariance(Img,res);
res=1.0-res;
res=Img+res;
imshow("Img",Img);
cv::threshold(res,res,0.85,1,cv::THRESH_BINARY);
cv::resize(res,res,cv::Size(res.cols/2,res.rows/2));
imwrite("result.tif",res*255);
imshow("Edges",res);
waitKey(0);
return 0;
}
Just built this code on ubuntu 14.03 x64, using the same command line as you used, no any messages, runs fine.
I think warning related to your system environment.
I have an IplImage and I want to binarize (without using cvThreshold function) it using this following code:
#include <opencv2/highgui/highgui.hpp>
#include <iostream>
using namespace cv;
using namespace std;
int main()
{
static IplImage* img ;
img = cvLoadImage ("c:\\Mytest.jpg");
for(int i=0;i<img->height;i++)
{
for(int j=0;j<img->width;j++)
{
if (img->imageData[i*img->widthStep+j]<=10)
((uchar *)img->imageData)[i*img->widthStep+j]=255;
else
((uchar *)img->imageData)[i*img->widthStep+j]=0;
}
}
cvShowImage("After",img);
waitKey(0);
};
but this code affected only part of the image, like this:
see, it's a breeze with c++:
Mat img = imread("c:\\Mytest.jpg", 0); // load grayscale
Mat thresh = ( im <= 10 ); // that's it already!
imshow("After",img);
waitKey(0);
also look at threshold()