How do i implement background subtraction(background model obtained by averaging first..say 50 frames..) in opencv
I tried looking for some codes but found they were in python..im working in c++(visual studio 2013)
A small working code snippet will help..thanks!
OpenCV provide background subtraction capabilities. See BackgroundSubtractorMOG2, that models the background with a Mixture of Gaussians, and is therefore quite robust to background changes.
The parameters history is the numbers of frame used to build the background model.
#include <opencv2\opencv.hpp>
using namespace cv;
int main(int argc, char *argv[])
{
int history = 50;
float varThreshold = 16.f; // default value
BackgroundSubtractorMOG2 bg = BackgroundSubtractorMOG2(history, varThreshold);
VideoCapture cap(0);
Mat3b frame;
Mat1b fmask;
for (;;)
{
cap >> frame;
bg(frame, fmask, -1);
imshow("frame", frame);
imshow("mask", fmask);
if (cv::waitKey(30) >= 0) break;
}
return 0;
}
Related
I am working on a university project where we have a table with glass surface, a webcam, and IR spots underneath.
We want to detect certain gestures such as:
1, 2, 3 fingers
3 fingertips
This is how a hand looks through the camera:
When the camera initialise it learns the background and subtracts it, going from
to this:
The hand, however, is also "learned" and disappears rather quickly.
We want to the program to learn the background, but will not store the hand as part of the background as it will be static.
Any suggestions on how to do this?
What we have tried: playing with the learning rate, blurring, morphology.
Code included below.
#include <opencv2/core/core.hpp>
#include "opencv2/opencv.hpp"
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/video/background_segm.hpp>
#include <opencv\cv.h>
#include <iostream>
#include <sstream>
using namespace cv;
using namespace std;
int main(int, char)
{
Mat frame; //current frame
Mat fgMaskMOG; //fg mask generated by MOG method
int frameNum = 0;
Ptr<BackgroundSubtractor> pMOG2; //MOG2 Background subtractor
//pMOG = new BackgroundSubtractorMOG(); //MOG approach
pMOG2 = createBackgroundSubtractorMOG2(20, 16, false); //MOG2 approach
VideoCapture cap(1); // open the default camera
if (!cap.isOpened()) // check if we succeeded
return -1;
for (;;)
{
cap >> frame; // get a new frame from camera
if (!cap.read(frame)) {
cerr << "Unable to read next frame." << endl;
continue;
}
imshow("orig", frame);
++frameNum;
pMOG2->apply(frame, fgMaskMOG, -1);
imshow("frame", fgMaskMOG);
if (waitKey(30) >= 0)
break;
}
// the camera will be deinitialized automatically in VideoCapture destructor
return 0;
}
http://inside.mines.edu/~whoff/courses/EENG512/lectures/HoughInOpenCV.pdf
Hi, i am going through the pdf tutorial in the link above.
I encounter problem on page 6 of the slides.
As we seee that the output of the code after inserting the canny edge detector, it should trace out all the edges on a photo.
I cannot get what is shown at page 6.
#include <opencv2/opencv.hpp>
#include <iostream>
using namespace std;
using namespace cv;
int main(int argc, char* argv[])
{
printf("Hello world\n");
// read an image
Mat imgInput = imread("a.png");
// create image window named "My Image"
namedWindow("My Image");
// Convert to gray if necessary
if (imgInput.channels() == 3)
cv::cvtColor(imgInput, imgInput, CV_BGR2GRAY);
// Apply Canny edge detector
Mat imgContours;
double thresh = 105; // try different values to see effect
Canny(imgInput, imgContours, 0.4*thresh, thresh); // low, high threshold
// show the image on window
imshow("My Image", imgInput);
// wait for xx ms (0 means wait until keypress)
waitKey(5000);
return 0;
}
And also, there is a line double thresh = xxx;//try different values
What values should i put? and what are the values mean?
Thank you
Just replace your imshow function with ,
imshow("My Image", imgContours);
and you can use thresh value approximately around 200.
Change threshold value and see effect of it and according to that you can select your threshold value.
The imgContours is your output map with all the edges. You should use imshow with imgContours.
#include <opencv2/opencv.hpp>
#include <iostream>
using namespace std;
using namespace cv;
int main(int argc, char* argv[])
{
printf("Hello world\n");
// read an image
Mat imgInput = imread("a.png");
// create image window named "My Image"
namedWindow("My Image");
// Convert to gray if necessary
if (imgInput.channels() == 3)
cv::cvtColor(imgInput, imgInput, CV_BGR2GRAY);
// Apply Canny edge detector
Mat imgContours;
double thresh = 105; // try different values to see effect
Canny(imgInput, imgContours, 0.4*thresh, thresh); // low, high threshold
// show the image on window
imshow("My Image", imgContours);
// wait for xx ms (0 means wait until keypress)
waitKey(5000);
return 0;
}
Reference:
http://docs.opencv.org/modules/imgproc/doc/feature_detection.html?highlight=canny#canny
I'm pretty new to OpenCV, so bear with me. I'm running a Mac Mini with OSX 10.8. I have a program that recognizes colors and displays them in binary picture (black and white). However, I want to store the number of white pixels as an integer (or float, etc.) to compare with other number of pixels. How can I do this? Here is my current code-
#include <iostream>
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/core/core.hpp"
using namespace cv;
using namespace std;
int main( int argc, char** argv )
{
VideoCapture cap(0); //capture the video from webcam
if ( !cap.isOpened() ) // if not success, exit program
{
cout << "Cannot open the web cam" << endl;
return -1;
}
namedWindow("HSVLeftRed", CV_WINDOW_AUTOSIZE);
namedWindow("HSVLeftGreen", CV_WINDOW_AUTOSIZE);
while (true) {
Mat image;
cap.read(image);
Mat HSV;
Mat leftgreen;
Mat leftred;
//Left Cropping
Mat leftimg = image(Rect(0, 0, 640, 720));
//Left Red Detection
cvtColor(leftimg,HSV,CV_BGR2HSV);
inRange(HSV,Scalar(0,0,150),Scalar(0,0,255), leftgreen);
//imshow("HSVLeftRed", leftgreen);
//print pixel type
//Left Green Detection
cvtColor(leftimg,HSV,CV_BGR2HSV);
inRange(HSV,Scalar(still need to find proper min values),Scalar(still need to find proper max values), leftgreen);
//imshow("HSVLeftGreen", leftgreen);
//compare pixel types
}
return 0;
}
Thanks in advance!
To count the non-zero pixels, OpenCV has this function cv::countNonZero. It takes input the image, whose number of non-zero pixels, we want to calculate and output is number of non-zero pixels(int). Here is the documentation.
In your case, since all the pixels are either black or white, all the non zero pixels will be white pixels.
This is how to use it,
int cal = countNonZero(image);
Change image, as per your code.
i'm working on a project using OpenCV243, I need to get the foreground during a stream, my Problem is that I use the cv::absdiff to get it doesn't really help, here is my code and the result .
#include <iostream>
#include<opencv2\opencv.hpp>
#include<opencv2\calib3d\calib3d.hpp>
#include<opencv2\core\core.hpp>
#include <opencv2\highgui\highgui.hpp>
int main (){
cv::VideoCapture cap(0);
cv::Mat frame,frame1,frame2;
cap >> frame;
frame.copyTo(frame1);
cv::imwrite("background.jpeg",frame1);
int key = 0;
while(key!=27){
cap >> frame;
cv::absdiff(frame, frame1, frame2); // frame2 = frame -frame1
cv::imshow("foreground", frame2);
if(key=='c'){
//frame.copyTo(frame2);
cv::imwrite("foreground.jpeg", frame2);
key = 0;
}
cv::imshow("frame",frame);
key = cv::waitKey(10);
}
cap.release();
return 0;
}
as you can see the subtraction work but what I want to get is only the values of that changed for example if have a Pixel in the background with [130,130,130] and the same pixel has [200,200,200] in the frame I want to get exactly the last values and not [70,70,70]
I've already seen this tutorial : http://mateuszstankiewicz.eu/?p=189
but I can't understand the code and I have problems setting cv::BackgroundSubtractorMOG2 with my openCV version
thanks in advance for you help
BackgroundSubtractorMOG2 should work with #include "opencv2/video/background_segm.hpp"
The samples with OpenCV have two nice c++ examples (in the samples\cpp directory).
bgfg_segm.cpp shows how to use the BackgroundSubtractorMOG2
bgfg_gmg.cpp uses BackgroundSubtractorGMG
To get the last values (and asuming you meant to get the foreground pixel values) you could copy the frame using the foreground mask. This is also done in the first example, in the following snippet:
bg_model(img, fgmask, update_bg_model ? -1 : 0);
fgimg = Scalar::all(0);
img.copyTo(fgimg, fgmask);
Good day everyone! So currently I'm working on a project with video processing, so I decided to give a try to OpenCV. As I'm new to it, I decided to find few sample codes and test them out. First one, is C OpenCV and looks like this:
#include <opencv/cv.h>
#include <opencv/highgui.h>
#include <stdio.h>
int main( void ) {
CvCapture* capture = 0;
IplImage *frame = 0;
if (!(capture = cvCaptureFromCAM(0)))
printf("Cannot initialize camera\n");
cvNamedWindow("Capture", CV_WINDOW_AUTOSIZE);
while (1) {
frame = cvQueryFrame(capture);
if (!frame)
break;
IplImage *temp = cvCreateImage(cvSize(frame->width/2, frame->height/2), frame->depth, frame->nChannels); // A new Image half size
cvResize(frame, temp, CV_INTER_CUBIC); // Resize
cvSaveImage("test.jpg", temp, 0); // Save this image
cvShowImage("Capture", frame); // Display the frame
cvReleaseImage(&temp);
if (cvWaitKey(5000) == 27) // Escape key and wait, 5 sec per capture
break;
}
cvReleaseImage(&frame);
cvReleaseCapture(&capture);
return 0;
}
So, this one works perfectly well and stores image to hard drive nicely. But problems begin with next sample, which uses C++ OpenCV:
#include "opencv2/opencv.hpp"
#include <string>
using namespace cv;
int main(int, char**)
{
VideoCapture cap(0); // open the default camera
if(!cap.isOpened()) // check if we succeeded
return -1;
Mat edges;
//namedWindow("edges",1);
for(;;)
{
Mat frame;
cap >> frame; // get a new frame from camera
cvtColor(frame, edges, CV_RGB2XYZ);
imshow("edges", edges);
//imshow("edges2", frame);
//imwrite("test1.jpg", frame);
if(waitKey(1000) >= 0) break;
}
// the camera will be deinitialized automatically in VideoCapture destructor
return 0;
}
So, yeah, generally, in terms of showing video (image frames) there is practically no changes, but when it comes to using im** functions, some problems arise.
Using cvSaveImage() works out nicely, but the moment I try to use imwrite(), unhandled exception arises in regards of 'access violation reading location'. Same goes for imread(), when I'm trying to load image.
So, the thing I wanted to ask, is it possible to use most of the functionality with C OpenCV? Or is it necessary to use C++ OpenCV. If yes, is there any solution for the problem I described earlier.
Also as stated here, images initially are in BGR-format, so conversion needed. But doing BGR2XYZ conversion seems to invert colors, while RGB2XYZ preserve them. Examples:
images
Or is it necessary to use C++ OpenCV?
No, there is no necessity whatsoever. You can use any interface you like and you think you are good with it (OpenCV offers C, C++, Python interfaces).
For your problem about imwrite() and imread() :
For color images the order channel is normally Blue, Green, Red , this
is what imshow() , imread() and imwrite() expect
Quoted from there