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hackassin
GitHub Repository: hackassin/learnopencv
Path: blob/master/HandPose/handPoseImage.cpp
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#include <opencv2/dnn.hpp>
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#include <opencv2/imgproc.hpp>
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#include <opencv2/highgui.hpp>
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#include <iostream>
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using namespace std;
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using namespace cv;
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using namespace cv::dnn;
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const int POSE_PAIRS[20][2] =
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{
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{0,1}, {1,2}, {2,3}, {3,4}, // thumb
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{0,5}, {5,6}, {6,7}, {7,8}, // index
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{0,9}, {9,10}, {10,11}, {11,12}, // middle
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{0,13}, {13,14}, {14,15}, {15,16}, // ring
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{0,17}, {17,18}, {18,19}, {19,20} // small
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};
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string protoFile = "hand/pose_deploy.prototxt";
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string weightsFile = "hand/pose_iter_102000.caffemodel";
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int nPoints = 22;
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int main(int argc, char **argv)
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{
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cout << "USAGE : ./handPoseImage <imageFile> " << endl;
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string imageFile = "right-frontal.jpg";
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// Take arguments from commmand line
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if (argc == 2)
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{
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imageFile = argv[1];
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}
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float thresh = 0.01;
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Mat frame = imread(imageFile);
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Mat frameCopy = frame.clone();
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int frameWidth = frame.cols;
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int frameHeight = frame.rows;
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float aspect_ratio = frameWidth/(float)frameHeight;
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int inHeight = 368;
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int inWidth = (int(aspect_ratio*inHeight) * 8) / 8;
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cout << "inWidth = " << inWidth << " ; inHeight = " << inHeight << endl;
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double t = (double) cv::getTickCount();
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Net net = readNetFromCaffe(protoFile, weightsFile);
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Mat inpBlob = blobFromImage(frame, 1.0 / 255, Size(inWidth, inHeight), Scalar(0, 0, 0), false, false);
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net.setInput(inpBlob);
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Mat output = net.forward();
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int H = output.size[2];
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int W = output.size[3];
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// find the position of the body parts
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vector<Point> points(nPoints);
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for (int n=0; n < nPoints; n++)
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{
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// Probability map of corresponding body's part.
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Mat probMap(H, W, CV_32F, output.ptr(0,n));
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resize(probMap, probMap, Size(frameWidth, frameHeight));
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Point maxLoc;
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double prob;
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minMaxLoc(probMap, 0, &prob, 0, &maxLoc);
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if (prob > thresh)
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{
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circle(frameCopy, cv::Point((int)maxLoc.x, (int)maxLoc.y), 8, Scalar(0,255,255), -1);
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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);
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}
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points[n] = maxLoc;
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}
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int nPairs = sizeof(POSE_PAIRS)/sizeof(POSE_PAIRS[0]);
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for (int n = 0; n < nPairs; n++)
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{
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// lookup 2 connected body/hand parts
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Point2f partA = points[POSE_PAIRS[n][0]];
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Point2f partB = points[POSE_PAIRS[n][1]];
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if (partA.x<=0 || partA.y<=0 || partB.x<=0 || partB.y<=0)
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continue;
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line(frame, partA, partB, Scalar(0,255,255), 8);
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circle(frame, partA, 8, Scalar(0,0,255), -1);
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circle(frame, partB, 8, Scalar(0,0,255), -1);
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}
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t = ((double)cv::getTickCount() - t)/cv::getTickFrequency();
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cout << "Time Taken = " << t << endl;
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imshow("Output-Keypoints", frameCopy);
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imshow("Output-Skeleton", frame);
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imwrite("Output-Skeleton.jpg", frame);
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waitKey();
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return 0;
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}
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