Hello,
I want to detect faces with OpenCV and apply an optical flow to follow the face. My code works but it is expensive for the CPU (the CPU runs at 20%).
I capture an image at with "capture >> frame" (which gives a new image at each 30ms). Running only this requires 5% of the CPU. However, if I add the code for optical flow "cv::calcOpticalFlowPyrLK(prevGray, gray, prevPoints, currPoints, status, err, winSize, 3, termcrit, 0, 0.001);", running the program leads to a constant CPU usage of 20% for the program. I would very much like to reduce this CPU usage even if my program takes more time to operate.
cv::setNumThreads(2) helps a lot (CPU 10%) but I would like to see other possible methods to optimize.
Here is the code I use (the feature points for the optical flow are pre-generated to simplify the code):
Thank you so much !
Alex
int main(int argc, char *argv[]) { //cv::setNumThreads(2);
cv::Mat frame;
cv::Mat frametemp;
cv::Mat gray;
cv::Mat prevGray;
cv::vector<cv::Point2f> prevPoints;
cv::vector<uchar> status;
cv::vector<float> err;
cv::VideoCapture capture(0);
float landmarks[68][2];
while (true)
{
capture >> frame;
if (!frame.empty())
{
for (int i = 0; i < 68; i++)
{
landmarks[i][0] = i*5;
landmarks[i][1] = i*5;
}
frame.copyTo(frametemp);
cvtColor(frametemp, gray, cv::COLOR_BGR2GRAY);
if (prevGray.empty())
{
gray.copyTo(prevGray);
}
cv::vector<cv::Point2f> currPoints;
for (int k = 0; k < 68; k++)
{
currPoints.push_back(cv::Point2f(landmarks[k][0], landmarks[k][1]));
}
if (!prevPoints.empty())
{
cv::calcOpticalFlowPyrLK(prevGray, gray, prevPoints, currPoints, status, err, winSize, 3, termcrit, 0, 0.01);
//cv::calcOpticalFlowPyrLK(prevGray, gray, prevPoints, currPoints, status, err, winSize, 3, termcrit, 0, 0.001);
}
std::swap(currPoints, prevPoints);
cv::swap(prevGray, gray);
}
else
{
printf(" --(!) No captured frame -- Break!"); break;
}
//Sleep(3);
}
return 0;
}
Blockquote
