learnopencv/HandPose/handPoseImage.cpp

#include <opencv2/dnn.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.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 = "hand/pose_deploy.prototxt";
string weightsFile = "hand/pose_iter_102000.caffemodel";

int nPoints = 22;

int main(int argc, char **argv)
{

    cout << "USAGE : ./handPoseImage <imageFile> " << endl;

    string imageFile = "right-frontal.jpg";
    // Take arguments from commmand line
    if (argc == 2)
    {
      imageFile = argv[1];
    }

    float thresh = 0.01;

    Mat frame = imread(imageFile);
    Mat frameCopy = frame.clone();
    int frameWidth = frame.cols;
    int frameHeight = frame.rows;

    float aspect_ratio = frameWidth/(float)frameHeight;
    int inHeight = 368;
    int inWidth = (int(aspect_ratio*inHeight) * 8) / 8;

    cout << "inWidth = " << inWidth << " ; inHeight = " << inHeight << endl;

    double t = (double) cv::getTickCount();
    Net net = readNetFromCaffe(protoFile, weightsFile);

    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);
            cv::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);
    }

    t = ((double)cv::getTickCount() - t)/cv::getTickFrequency();
    cout << "Time Taken = " << t << endl;
    imshow("Output-Keypoints", frameCopy);
    imshow("Output-Skeleton", frame);
    imwrite("Output-Skeleton.jpg", frame);

    waitKey();

    return 0;
}