I'm working on a project to detect motion on a camera.
I need to start recording video when motion is detected for example:
Record while motion is being detected
Continue recording for 10 seconds after the motion detection is stopped
I have a working example that only detects the motion and draw rectangles on the moving parts.
I searched for examples on how to record when motion is detected but no good results.
Here is my working code:
#include <iostream>
#include <sstream>
#include <opencv4/opencv2/imgproc.hpp>
#include <opencv4/opencv2/videoio.hpp>
#include <opencv4/opencv2/highgui.hpp>
#include <opencv4/opencv2/video.hpp>
#include <unistd.h>
using namespace cv;
using namespace std;
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
int main(int argc, char* argv[])
{
//create Background Subtractor objects
Ptr<BackgroundSubtractor> pBackSub;
pBackSub = createBackgroundSubtractorMOG2();
VideoCapture capture(0);
if (!capture.isOpened()){
//error in opening the video input
cerr << "Unable to open: " << endl;
return 0;
}
Mat frame, fgMask;
sleep(3);
while (true) {
capture >> frame;
if (frame.empty())
break;
//update the background model
pBackSub->apply(frame, fgMask);
imshow("FG Mask", fgMask);
RNG rng(12345);
findContours(fgMask, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE,Point(0, 0));
vector<Rect>boundRect (contours.size());
vector<vector<Point> > contours_poly( contours.size() );
for (int i = 0; i < contours.size();i++) {
if( contourArea(contours[i])< 500)
{
continue;
}
putText(frame, "Motion Detected", Point(10,20), FONT_HERSHEY_SIMPLEX, 0.75, Scalar(0,0,255),2);
approxPolyDP( contours[i], contours_poly[i], 3, true );
boundRect[i] = boundingRect( contours_poly[i] );
Scalar color = Scalar( rng.uniform(0, 256), rng.uniform(0,256), rng.uniform(0,256) );
rectangle( frame, boundRect[i].tl(), boundRect[i].br(), color, 2 );
}
imshow("Frame", frame);
int keyboard = waitKey(30);
if (keyboard == 'q' || keyboard == 27)
break;
}
return 0;
}
I tried adding this to the code:
int frameWidth = 320;
int frameHeight = 240;
cv::Size frameSize = cv::Size(frameWidth, frameHeight);
/* Output file */
int codec = cv::VideoWriter::fourcc('M', 'P', '4', 'V');
cv::VideoWriter outputVideo;
outputVideo.open("rr.mp4", codec, capture.get(cv::CAP_PROP_FPS), frameSize, true);
and after drawing the rectangle I write the frame to the video:
outputVideo.write(frame);
but after that, the video is empty and crashes.
I already took a look at Motion but I didn't find an example.
How can I achieve this?
Thanks,
Talel
I resolved the issue,
I was opening the output video with a specific dimensions (320,240) and I was saving the captured frame which is bigger.
So the solution is to resize the captured frame to fit into the output video.
Here is the final solution if anyone is interesting:
Turn the laptop camera into an IP camera with: cam2ip
Here is the source code:
#include <iostream>
#include <sstream>
#include <opencv4/opencv2/imgproc.hpp>
#include <opencv4/opencv2/videoio.hpp>
#include <opencv4/opencv2/highgui.hpp>
#include <opencv4/opencv2/video.hpp>
#include <unistd.h>
using namespace cv;
using namespace std;
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
int main(int argc, char* argv[])
{
//create Background Subtractor objects
Ptr<BackgroundSubtractor> pBackSub;
pBackSub = createBackgroundSubtractorMOG2();
const std::string videoStreamAddress = "http://192.168.20.100:56000/mjpeg";
cv::VideoCapture vcap;
if(!vcap.open(videoStreamAddress)) {
std::cout << "Error opening video stream or file" << std::endl;
return -1;
}
Mat frame, fgMask;
int frameWidth = 320;
int frameHeight = 240;
cv::Size frameSize = cv::Size(frameWidth, frameHeight);
/* Output file */
int codec = cv::VideoWriter::fourcc('M', 'P', '4', 'V');
cv::VideoWriter outputVideo;
outputVideo.open("rr.mp4", codec, vcap.get(cv::CAP_PROP_FPS), frameSize, true);
sleep(3);
while (true) {
vcap >> frame;
if (frame.empty())
break;
//update the background model
pBackSub->apply(frame, fgMask);
imshow("FG Mask", fgMask);
RNG rng(12345);
findContours(fgMask, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE,Point(0, 0));
vector<Rect>boundRect (contours.size());
vector<vector<Point> > contours_poly( contours.size() );
for (int i = 0; i < contours.size();i++) {
if( contourArea(contours[i])< 500)
{
continue;
}
putText(frame, "Motion Detected", Point(10,20), FONT_HERSHEY_SIMPLEX, 0.75, Scalar(0,0,255),2);
approxPolyDP( contours[i], contours_poly[i], 3, true );
boundRect[i] = boundingRect( contours_poly[i] );
Scalar color = Scalar( rng.uniform(0, 256), rng.uniform(0,256), rng.uniform(0,256) );
rectangle( frame, boundRect[i].tl(), boundRect[i].br(), color, 2 );
resize(frame, frame, frameSize);
outputVideo.write(frame);
}
imshow("Frame", frame);
int keyboard = waitKey(30);
if (keyboard == 'q' || keyboard == 27)
break;
}
outputVideo.release();
return 0;
}
Further enhancement suggestions:
Make sure that the light is not part of the motion detection
Open an output video with the same capture's dimensions
Related
I am working on opencv and qt project.it 's working very quickly on linux but it is working very slow on windows.Linux OS is 64 bit ,windows 64 bit too.I didnt understand the problem.Thanks (sorry for my english)
following code:
#include <opencv2/core/base.hpp>
#include <opencv2/core/mat.hpp>
#include <opencv2/core/types.hpp>
#include <opencv2/highgui/highgui_c.h>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/objdetect/objdetect_c.h>
#include <opencv2/objdetect.hpp>
#include <opencv2/videoio.hpp>
#include <iostream>
#include <vector>
using namespace cv;
using namespace std;
int main(int argc, char* argv[])
{
VideoCapture cap(0); // open the video camera no. 0
namedWindow("MyVideo",CV_WINDOW_AUTOSIZE); //create a window called "MyVideo"
// Load Face cascade (.xml file)
CascadeClassifier face_cascade;
face_cascade.load( "xml/haarcascade_frontalface_alt.xml" );
while (1)
{
Mat frame;
bool bSuccess = cap.read(frame); // read a new frame from video
if (!bSuccess) //if not success, break loop
{
cout << "Cannot read a frame from video stream" << endl;
break;
}
// Detect faces
std::vector<Rect> faces;
face_cascade.detectMultiScale( frame, faces, 1.1, 2, 0|CV_HAAR_SCALE_IMAGE, Size(30, 30) );
// Draw circles on the detected faces
for( int i = 0; i < faces.size(); i++ )
{
Point center( faces[i].x + faces[i].width*0.5, faces[i].y + faces[i].height*0.5 );
ellipse( frame, center, Size( faces[i].width*0.5, faces[i].height*0.5), 0, 0, 360, Scalar( 255, 0, 255 ), 4, 8, 0 );
imshow( "Detected Face", frame );
}
//rectangle( frame, center, Size( faces[i].width*2, faces[i].height*2), Scalar( 255, 0, 255 ) );
if (waitKey(30) == 27) //wait for 'esc' key press for 30ms. If 'esc' key is pressed, break loop
{
cout << "esc key is pressed by user" << endl;
break;
}
}
return 0;
}
I have a problem with video speed, when I just run a video file in opencv it plays in normal speed.
The problem starts when I apply face and eye detection to the video it plays very slowly. I have tried to change waitKey() values , but the problem still exists.
Why is this happening?
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
using namespace std;
using namespace cv;
// Function Headers
void detectAndDisplay(Mat frame);
// Global variables
// Copy this file from opencv/data/haarscascades to target folder
string face_cascade_name = "haarcascade_frontalface_alt.xml";
string eye_cascade_name = "haarcascade_mcs_eyepair_big.xml";
CascadeClassifier face_cascade;
CascadeClassifier eye_cascade;
string window_name = "Capture - Face detection";
int filenumber; // Number of file to be saved
string filename;
int main(void)
{
VideoCapture capture("m.mp4");
if (!capture.isOpened()) // check if we succeeded
return -1;
// Load the cascade
if (!face_cascade.load(face_cascade_name))
{
printf("--(!)Error loading\n");
return (-1);
}
if (!eye_cascade.load(eye_cascade_name))
{
printf("--(!)Error loading\n eye ");
return (-1);
}
// Read the video stream
Mat frame;
for (;;)
{
capture >> frame;
// Apply the classifier to the frame
if (!frame.empty())
{
detectAndDisplay(frame);
}
else
{
printf(" --(!) No captured frame -- Break!");
break;
}
waitKey(40);
return 0;
}
}
void detectAndDisplay(Mat frame)
{
std::vector<Rect> faces;
std::vector<Rect> eyes;
Mat frame_gray;
Mat crop;
Mat res;
Mat gray;
string text;
stringstream sstm;
cvtColor(frame, frame_gray, COLOR_BGR2GRAY);
equalizeHist(frame_gray, frame_gray);
// Detect faces
face_cascade.detectMultiScale(frame_gray, faces, 1.1, 4, CASCADE_SCALE_IMAGE, Size(20, 20));
// Set Region of Interest
size_t i = 0; // ic is index of current element
for (i = 0; i < faces.size(); i++) // Iterate through all current elements (detected faces)
{
Point pt1(faces[i].x, faces[i].y); // Display detected faces on main window - live stream from camera
Point pt2((faces[i].x + faces[i].height), (faces[i].y + faces[i].width));
rectangle(frame, pt1, pt2, Scalar(0, 255, 0), 2, 8, 0);
// set ROI for the eyes
Rect Roi = faces[i];
Roi.height = Roi.height / 4;
Roi.y = Roi.y + Roi.height;
cv::Mat crop = frame(Roi);
cvtColor(crop, gray, CV_BGR2GRAY);
imshow("ROI", gray);
eye_cascade.detectMultiScale(gray, eyes, 1.1, 2, 0 | CV_HAAR_SCALE_IMAGE, Size(20, 20));
for (size_t j = 0; j < eyes.size(); j++)
{
Rect r(Roi.x + eyes[j].x, Roi.y + eyes[j].y, eyes[j].width, eyes[j].height);
rectangle(frame, r, Scalar(255, 0, 0), 3, 1, 0);
// convert roi to ychannel
Mat eye_region = frame(eyes[j]).clone();
Mat eye_region_YCbCr;
cvtColor(eye_region, eye_region_YCbCr, CV_BGR2YCrCb);
vector<Mat> channels;
split(eye_region_YCbCr, channels);
Mat eye_region_Ychannel = channels[0].clone();
imshow("Y", eye_region_Ychannel);
// end of convert
}
}
// Show image
imshow("original", frame);
if (!crop.empty())
{
imshow("detected", crop);
}
else
{
destroyWindow("detected");
}
}
I am using OpenCV 2.4.6.
I am trying to get all the convexity defect depth_points of the biggest contour. But i am getting the bellow exception
Assertion failed (mtype == type0 || (CV_MAT_CN(mtype) == CV_MAT_CN(type0) && ((1 << type0) & fixedDepthMask) != 0)) in unknown function
the current code is pasted bellow
Thank you for any help
vector<vector<Point> >hulls( 1 );
vector<Point> hull;
std::vector<Vec4i> defects;
if(contours.size()>1){
convexHull( Mat(contours[largest_contour_index]), hulls[0], false );
convexityDefects(contours[largest_contour_index], hulls[0], defects);
drawContours(sourceVideo,contours,largest_contour_index,Scalar(255, 0, 0));
drawContours(sourceVideo,hulls,0,Scalar(0, 255, 0));
}
the error is in this line
convexityDefects(contours[largest_contour_index], hulls[0], defects);
Try this it works for me:
#include <stdlib.h>
#include <stdio.h>
#include <iostream>
#include <ctype.h>
#include <time.h>
#include <opencv2/opencv.hpp>
using namespace cv;
using namespace std;
String window_name = "Hand_HSV";
Mat frame,copyFrame;
// Detect Skin from YCrCb
Mat DetectYCrCb(Mat img,Scalar min, Scalar max){
Mat skin;
cvtColor(img, skin, cv::COLOR_RGB2YCrCb);
inRange(skin, min, max, skin);
Mat rect_12 = getStructuringElement(cv::MORPH_RECT, Size(12,12) , Point(6,6));
erode(skin, skin, rect_12,Point(),1);
Mat rect_6 = getStructuringElement(cv::MORPH_RECT, Size(6,6) , Point(3,3));
dilate(skin,skin,rect_6,Point(),2);
return skin;
}
void DetectContour(Mat img){
Mat drawing = Mat::zeros( img.size(), CV_8UC3 );
vector<vector<Point> > contours;
vector<vector<Point> > bigContours;
vector<Vec4i> hierarchy;
findContours(img,contours, hierarchy, cv::RETR_LIST, cv::CHAIN_APPROX_SIMPLE, Point());
if(contours.size()>0)
{
vector<vector<int> >hull( contours.size() );
vector<vector<Vec4i>> convDef(contours.size() );
vector<vector<Point>> hull_points(contours.size());
vector<vector<Point>> defect_points(contours.size());
for( int i = 0; i < contours.size(); i++ )
{
if(contourArea(contours[i])>5000)
{
convexHull( contours[i], hull[i], false );
convexityDefects( contours[i],hull[i], convDef[i]);
// start_index, end_index, farthest_pt_index, fixpt_depth
for(int k=0;k<hull[i].size();k++)
{
int ind=hull[i][k];
hull_points[i].push_back(contours[i][ind]);
}
for(int k=0;k<convDef[i].size();k++)
{
if(convDef[i][k][3]>20*256)
{
int ind_0=convDef[i][k][0];
int ind_1=convDef[i][k][1];
int ind_2=convDef[i][k][2];
defect_points[i].push_back(contours[i][ind_2]);
cv::circle(drawing,contours[i][ind_0],5,Scalar(0,255,0),-1);
cv::circle(drawing,contours[i][ind_1],5,Scalar(0,255,0),-1);
cv::circle(drawing,contours[i][ind_2],5,Scalar(0,0,255),-1);
cv::line(drawing,contours[i][ind_2],contours[i][ind_0],Scalar(0,0,255),1);
cv::line(drawing,contours[i][ind_2],contours[i][ind_1],Scalar(0,0,255),1);
}
}
drawContours( drawing, contours, i, Scalar(0,255,0), 1, 8, vector<Vec4i>(), 0, Point() );
drawContours( drawing, hull_points, i, Scalar(255,0,0), 1, 8, vector<Vec4i>(), 0, Point() );
}
}
}
namedWindow( "Hull demo",cv::WINDOW_AUTOSIZE );
imshow( "Hull demo", drawing );
}
int main( int argc, char** argv )
{
VideoCapture capture(0);
//VideoCapture capture("Video_Hand.MPG");
namedWindow( window_name, cv::WINDOW_AUTOSIZE );
if (capture.isOpened()){
while(true)
{
capture >> frame;
imshow( window_name, frame);
Mat skinYCrCb = DetectYCrCb(frame,Scalar(0, 100, 80), Scalar(255, 185, 135));
imshow("Result",skinYCrCb);
DetectContour(skinYCrCb);
int c = waitKey(10);
if( (char)c == 27 )
{
break;
}
}
}
return 0;
}
Are you sure vector<vector<Point> >hulls is correct? The documentation (docs.opencv.org) mentions, for the 2nd parameter of convexityDefects:
convexhull – Convex hull obtained using convexHull() that should contain indices of the contour points that make the hull.
So i think it should be rather vector<vector<int> >hulls
I already had an optical flow code implemented using C++ in OpenCV. However, i would like to detect optical flow in half of the image frame. Which part should i edit? is it from this function below?
cvCalcOpticalFlowPyrLK(
frame1_1C, frame2_1C,
pyramid1, pyramid2,
frame1_features,
frame2_features,
number_of_features,
optical_flow_window,
5,
optical_flow_found_feature,
optical_flow_feature_error,
optical_flow_termination_criteria,
0 );
No. There are no changes necessary in the function itself. All you need to do is pass only the part of image on which you want to calculate optical flow to the function.
You can define the range of the image that you want to carry out the optical flow calculations on. using
wanted_image=image(Range(x1,y1), Range(x2,y2))
The following is a working code based on the lkdemo.cpp in the samples folder. THe only worthwhile change is
gray = gray(Range(1,480), Range(1,320));
//Gives the left half of the image
which defines the region of interest.
#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <iostream>
#include <ctype.h>
using namespace cv;
using namespace std;
static void help()
{
cout << "*** Using OpenCV version " << CV_VERSION <<" ***"<< endl;
cout << "\n\nUsage: \n"
"\tESC - quit the program\n"
"\tr - auto-initialize tracking\n"
"\tc - delete all the points\n"
"\tn - switch the \"night\" mode on/off\n"<< endl;
}
int main( int argc, char** argv )
{
help();
//Termination of the algo after 20 iterations or accuracy going under 0.03
TermCriteria termcrit(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 20, 0.3);
Size subPixWinSize(10,10), winSize(31,31);
const int MAX_COUNT = 500;
bool needToInit = false;
bool nightMode = false;
//Video capture is from the default device i.e. the webcam
VideoCapture cap(0);
if( !cap.isOpened() )
{
cout << "Could not initialize capturing...\n";
return 0;
}
namedWindow( "Half screen Optical flow Demo!", 1 );
Mat gray, prevGray, image;
vector<Point2f> points[2];
for(;;)
{
Mat frame;
//Output from the Videocapture is piped to 'frame'
cap >> frame;
if( frame.empty() )
break;
frame.copyTo(image);
cvtColor(image, gray, COLOR_BGR2GRAY);
// Night mode not disabled
if( nightMode )
image = Scalar::all(0);
gray = gray(Range(1,480), Range(1,320));
if( needToInit || points[0].size()<=5)
{
goodFeaturesToTrack(gray, points[1], MAX_COUNT, 0.01, 10, Mat(), 3, 0, 0.4);
cornerSubPix(gray, points[1], subPixWinSize, Size(-1,-1), termcrit);
}
else if( !points[0].empty() )
{
vector<uchar> status;
vector<float> err;
if(prevGray.empty())
gray.copyTo(prevGray);
calcOpticalFlowPyrLK(prevGray, gray, points[0], points[1], status, err, winSize, 3, termcrit, 0, 0.001);
size_t i, k;
for( i = k = 0; i < points[1].size(); i++ )
{
if( !status[i] )
continue;
points[1][k++] = points[1][i];
circle(image, points[1][i], 3, Scalar(0,255,0), -1, 8);
}
points[1].resize(k);
}
needToInit = false;
imshow("Half screen Optical flow Demo!", image);
char c = (char)waitKey(10);
if( c == 27 )
break;
switch( c )
{
case 'r':
needToInit = true;
break;
case 'c':
points[0].clear();
points[1].clear();
break;
case 'n':
nightMode = !nightMode;
break;
}
std::swap(points[1], points[0]);
cv::swap(prevGray, gray);
}
cap.release();
return 0;
}
if you want to detect optical flow only in the half of the image, then you can simply give halves of the images (frame1_1C, frame2_1C) as parameters. For example, following code initializes a matrix belonging to the left half of frame1_1C:
cv::Mat frame1_1C_half(frame1_1C, cv::Range(0, frame1_1C.rows), cv::Range(0, frame1_1C.cols/2));
I wrote a short routine in openCV and C++ to track objects with a webcam. The webcam formulation was speedy with no lag, but before leaving work for the weekend, I recorded a typical sequence to use as a test template while I work until Monday. This and the corresponding change in code somehow make the video play back in really slow motion. Here is the code, opening "Test.avi", ~20 seconds long instead of running a constant stream off of the webcam:
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <iostream>
#include <vector>
using namespace cv;
using namespace std;
Mat drawBoundingBoxes (Mat canvasImage, vector<vector<Point>> contours);
int main(int argc, char** argv[])
{
Mat frame;
Mat back;
Mat fGround;
BackgroundSubtractorMOG2 bGround;
bGround.nmixtures = 3;
//bGround.nShadowDetection = 0;
bGround.fTau = .5;
VideoCapture cap;
cap.open("Test.avi");
if (!cap.isOpened())
{
cout << "Can't open video" << endl;
return -1;
}
vector<vector<Point>> contours;
namedWindow("video", CV_WINDOW_AUTOSIZE);
while (true)
{
static int count = 1;
cap >> frame;
if (frame.empty())
break;
bGround.operator()(frame, fGround);
bGround.getBackgroundImage(back);
erode(fGround, fGround, Mat(), Point(-1,-1), 2, BORDER_DEFAULT);
dilate(fGround, fGround, Mat(), Point(-1,-1), 10, BORDER_DEFAULT);
if (count > 50)
{
findContours(fGround, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
drawContours(frame, contours, -1, Scalar(239,255,0), 2);
drawBoundingBoxes(frame, contours);
}
imshow("video", frame);
if(waitKey(30) >= 0)
break;
count++;
}
return 0;
}
Mat drawBoundingBoxes (Mat canvasImage, vector<vector<Point>> contours)
{
vector<Rect> boundRect(contours.size());
for (int i=0; i<contours.size(); i++)
{
boundRect[i] = boundingRect(contours[i]);
rectangle(canvasImage, boundRect[i], Scalar(153,0,76), 2, 8, 0);
}
return canvasImage;
}
Any ideas? Memory Leak somewhere? Thanks,
-Tony
I believe your recorded video has a higher framerate than that your PC can process real time. It's not a problem with a webcam as it just drops the frames. You could try to decrease the delay in the waitKey() procedure and see if that helps.