Why the video is performing very slow in deep learning opencv - c++

Question

This is HandKeypoint Detection using caffe deep learning on opencv the problem is When i run the code it is performing very slow untill the video is freezing for sometime but when i tried by using a static image it is performing as normal. I have declare the Net class outside of the while loop too but it is still the same the video does not run smothly. How to make the video to run smoothly?
#include <opencv2/opencv.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/dnn.hpp>
#include <iostream>
using namespace std;
using namespace cv;
using namespace cv::dnn;
const int POSE_PAIRS[20][2] =
{
{0,1}, {1,2}, {2,3}, {3,4}, // thumb
{0,5}, {5,6}, {6,7}, {7,8}, // index
{0,9}, {9,10}, {10,11}, {11,12}, // middle
{0,13}, {13,14}, {14,15}, {15,16}, // ring
{0,17}, {17,18}, {18,19}, {19,20} // small
};
string protoFile = "/home/hanish/Test_Opencv/HandKeyPoint/Models/pose_deploy.prototxt";
string weightsFile = "/home/hanish/Test_Opencv/HandKeyPoint/Models/pose_iter_102000.caffemodel";
int nPoints = 22;
int main(int argc, char **argv)
{
float thresh = 0.01;
VideoCapture cap(0);
Mat frame, frameCopy;
int frameWidth = cap.get(CAP_PROP_FRAME_WIDTH);
int frameHeight = cap.get(CAP_PROP_FRAME_HEIGHT);
float aspect_ratio = frameWidth/(float)frameHeight;
int inHeight = 368;
int inWidth = (int(aspect_ratio*inHeight) * 8) / 8;
cout << "inWidth = " << inWidth << " ; inHeight = " << inHeight << endl;
Net net = readNetFromCaffe(protoFile, weightsFile);
net.setPreferableBackend(DNN_TARGET_CPU);
while(1)
{
cap >> frame;
frameCopy = frame.clone();
Mat inpBlob = blobFromImage(frame, 1.0 / 255, Size(inWidth, inHeight), Scalar(0, 0, 0), false, false);
net.setInput(inpBlob);
Mat output = net.forward();
int H = output.size[2];
int W = output.size[3];
// find the position of the body parts
vector<Point> points(nPoints);
for (int n=0; n < nPoints; n++)
{
// Probability map of corresponding body's part.
Mat probMap(H, W, CV_32F, output.ptr(0,n));
resize(probMap, probMap, Size(frameWidth, frameHeight));
Point maxLoc;
double prob;
minMaxLoc(probMap, 0, &prob, 0, &maxLoc);
if (prob > thresh)
{
circle(frameCopy, cv::Point((int)maxLoc.x, (int)maxLoc.y), 8, Scalar(0,255,255), -1);
putText(frameCopy, cv::format("%d", n), cv::Point((int)maxLoc.x, (int)maxLoc.y), cv::FONT_HERSHEY_COMPLEX, 1, cv::Scalar(0, 0, 255), 2);
}
points[n] = maxLoc;
}
int nPairs = sizeof(POSE_PAIRS)/sizeof(POSE_PAIRS[0]);
for (int n = 0; n < nPairs; n++)
{
// lookup 2 connected body/hand parts
Point2f partA = points[POSE_PAIRS[n][0]];
Point2f partB = points[POSE_PAIRS[n][1]];
if (partA.x<=0 || partA.y<=0 || partB.x<=0 || partB.y<=0)
continue;
line(frame, partA, partB, Scalar(0,255,255), 8);
circle(frame, partA, 8, Scalar(0,0,255), -1);
circle(frame, partB, 8, Scalar(0,0,255), -1);
}
// imshow("Output-Keypoints", frameCopy);
imshow("Output-Skeleton", frame);
waitKey(1);
}
return 0;
}