#include <iostream>
using namespace std;
const int POSE_PAIRS[3][20][2] = {
{
{1,2}, {1,5}, {2,3},
{3,4}, {5,6}, {6,7},
{1,8}, {8,9}, {9,10},
{1,11}, {11,12}, {12,13},
{1,0}, {0,14},
{14,16}, {0,15}, {15,17}
},
{
{0,1}, {1,2}, {2,3},
{3,4}, {1,5}, {5,6},
{6,7}, {1,14}, {14,8}, {8,9},
{9,10}, {14,11}, {11,12}, {12,13}
},
{
{0,1}, {1,2}, {2,3}, {3,4},
{0,5}, {5,6}, {6,7}, {7,8},
{0,9}, {9,10}, {10,11}, {11,12},
{0,13}, {13,14}, {14,15}, {15,16},
{0,17}, {17,18}, {18,19}, {19,20}
}};
int main(
int argc,
char **argv)
{
"{ h help | false | print this help message }"
"{ p proto | | (required) model configuration, e.g. hand/pose.prototxt }"
"{ m model | | (required) model weights, e.g. hand/pose_iter_102000.caffemodel }"
"{ i image | | (required) path to image file (containing a single person, or hand) }"
"{ d dataset | | specify what kind of model was trained. It could be (COCO, MPI, HAND) depends on dataset. }"
"{ width | 368 | Preprocess input image by resizing to a specific width. }"
"{ height | 368 | Preprocess input image by resizing to a specific height. }"
"{ t threshold | 0.1 | threshold or confidence value for the heatmap }"
"{ s scale | 0.003922 | scale for blob }"
);
String modelTxt = samples::findFile(parser.get<
string>(
"proto"));
String modelBin = samples::findFile(parser.get<
string>(
"model"));
String imageFile = samples::findFile(parser.get<
String>(
"image"));
int W_in = parser.get<int>("width");
int H_in = parser.get<int>("height");
float thresh = parser.get<float>("threshold");
float scale = parser.get<float>("scale");
if (parser.get<bool>("help") || modelTxt.empty() || modelBin.empty() || imageFile.empty())
{
cout << "A sample app to demonstrate human or hand pose detection with a pretrained OpenPose dnn." << endl;
parser.printMessage();
return 0;
}
int midx, npairs, nparts;
if (!dataset.compare("COCO")) { midx = 0; npairs = 17; nparts = 18; }
else if (!dataset.compare("MPI")) { midx = 1; npairs = 14; nparts = 16; }
else if (!dataset.compare("HAND")) { midx = 2; npairs = 20; nparts = 22; }
else
{
std::cerr << "Can't interpret dataset parameter: " << dataset << std::endl;
exit(-1);
}
{
std::cerr << "Can't read image from the file: " << imageFile << std::endl;
exit(-1);
}
vector<Point> points(22);
for (int n=0; n<nparts; n++)
{
double conf;
if (conf > thresh)
p = pm;
points[n] = p;
}
float SX = float(img.
cols) / W;
float SY = float(img.
rows) / H;
for (int n=0; n<npairs; n++)
{
Point2f a = points[POSE_PAIRS[midx][n][0]];
Point2f b = points[POSE_PAIRS[midx][n][1]];
if (a.
x<=0 || a.
y<=0 || b.
x<=0 || b.
y<=0)
continue;
}
return 0;
}
Designed for command line parsing.
Definition utility.hpp:890
n-dimensional dense array class
Definition mat.hpp:950
MatSize size
Definition mat.hpp:2447
uchar * ptr(int i0=0)
Returns a pointer to the specified matrix row.
int cols
Definition mat.hpp:2424
bool empty() const
Returns true if the array has no elements.
int rows
the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions
Definition mat.hpp:2424
_Tp y
y coordinate of the point
Definition types.hpp:202
_Tp x
x coordinate of the point
Definition types.hpp:201
Template class for specifying the size of an image or rectangle.
Definition types.hpp:338
This class allows to create and manipulate comprehensive artificial neural networks.
Definition dnn.hpp:535
void setInput(CV_ND InputArray blob, const String &name="", double scalefactor=1.0, const Scalar &mean=Scalar())
Sets the new input value for the network.
Mat forward(const String &outputName=String())
Runs forward pass to compute output of layer with name outputName.
void minMaxLoc(InputArray src, double *minVal, double *maxVal=0, Point *minLoc=0, Point *maxLoc=0, InputArray mask=noArray())
Finds the global minimum and maximum in an array.
std::string String
Definition cvstd.hpp:151
#define CV_32F
Definition interface.h:81
@ circle
Definition gr_skig.hpp:62
Mat blobFromImage(InputArray image, double scalefactor=1.0, const Size &size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false, int ddepth=CV_32F)
Creates 4-dimensional blob from image. Optionally resizes and crops image from center,...
Net readNet(CV_WRAP_FILE_PATH const String &model, CV_WRAP_FILE_PATH const String &config="", const String &framework="", int engine=ENGINE_AUTO)
Read deep learning network represented in one of the supported formats.
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
int waitKey(int delay=0)
Waits for a pressed key.
CV_EXPORTS_W Mat imread(const String &filename, int flags=IMREAD_COLOR_BGR)
Loads an image from a file.
void line(InputOutputArray img, Point pt1, Point pt2, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
Draws a line segment connecting two points.
int main(int argc, char *argv[])
Definition highgui_qt.cpp:3
Definition all_layers.hpp:47