public void Clamp(SWIGTYPE_p_cv__Mat_T_float_t params_local, SWIGTYPE_p_cv__Vec6d params_global, FaceModelParameters arg2)
{
LandmarkDetectorPINVOKE.PDM_Clamp(swigCPtr, SWIGTYPE_p_cv__Mat_T_float_t.getCPtr(params_local), SWIGTYPE_p_cv__Vec6d.getCPtr(params_global), FaceModelParameters.getCPtr(arg2));
if (LandmarkDetectorPINVOKE.SWIGPendingException.Pending)
{
throw LandmarkDetectorPINVOKE.SWIGPendingException.Retrieve();
}
}
public override int Run()
{
int device = 0;
var argument = new StringList {
"./"
};
FaceModelParameters det_parameters = new FaceModelParameters(argument);
//vector<string> files, depth_directories, output_video_files, out_dummy;
StringList files = new StringList(), output_video_files = new StringList(), out_dummy = new StringList();
bool u;
string output_codec;
LandmarkDetector.get_video_input_output_params(files, out_dummy, output_video_files, out u, out output_codec, argument);
CLNF clnf_model = new CLNF(det_parameters.model_location);
float fx = 0, fy = 0, cx = 0, cy = 0;
LandmarkDetector.get_camera_params(out device, out fx, out fy, out cx, out cy, argument);
// If cx (optical axis centre) is undefined will use the image size/2 as an estimate
bool cx_undefined = false;
bool fx_undefined = false;
if (cx == 0 || cy == 0)
{
cx_undefined = true;
}
if (fx == 0 || fy == 0)
{
fx_undefined = true;
}
//// Do some grabbing
INFO_STREAM("Attempting to capture from device: " + device);
using (VideoCapture video_capture = new VideoCapture(device))
{
using (Mat dummy = new Mat())
video_capture.Read(dummy);
if (!video_capture.IsOpened())
{
FATAL_STREAM("Failed to open video source");
return(1);
}
else
{
INFO_STREAM("Device or file opened");
}
int frame_count = 0;
Mat captured_image = new Mat();
video_capture.Read(captured_image);
Size = new Size(captured_image.Width / SizeFactor, captured_image.Height / SizeFactor);
using (var resized_image = captured_image.Resize(Size))
{
// If optical centers are not defined just use center of image
if (cx_undefined)
{
cx = resized_image.Cols / 2.0f;
cy = resized_image.Rows / 2.0f;
}
// Use a rough guess-timate of focal length
if (fx_undefined)
{
fx = (float)(500 * (resized_image.Cols / 640.0));
fy = (float)(500 * (resized_image.Rows / 480.0));
fx = (float)((fx + fy) / 2.0);
fy = fx;
}
}
// Use for timestamping if using a webcam
long t_initial = Cv2.GetTickCount();
INFO_STREAM("Starting tracking");
while (video_capture.Read(captured_image))
{
using (var resized_image = captured_image.Resize(Size))
{
// Reading the images
MatOfByte grayscale_image = new MatOfByte();
if (resized_image.Channels() == 3)
{
Cv2.CvtColor(resized_image, grayscale_image, ColorConversionCodes.BGR2GRAY);
}
else
{
grayscale_image = (MatOfByte)resized_image.Clone();
}
// The actual facial landmark detection / tracking
bool detection_success = LandmarkDetector.DetectLandmarksInVideo(new SWIGTYPE_p_cv__Mat_T_uchar_t(grayscale_image.CvPtr), new SWIGTYPE_p_CLNF(CLNF.getCPtr(clnf_model)), new SWIGTYPE_p_FaceModelParameters(FaceModelParameters.getCPtr(det_parameters)));
// Visualising the results
// Drawing the facial landmarks on the face and the bounding box around it if tracking is successful and initialised
double detection_certainty = clnf_model.detection_certainty;
visualise_tracking(resized_image, ref clnf_model, ref det_parameters, frame_count, fx, fy, cx, cy);
// detect key presses
char character_press = (char)Cv2.WaitKey(15);
switch (character_press)
{
case 'r':
clnf_model.Reset();
break;
case 'q':
return(0);
}
// Update the frame count
frame_count++;
grayscale_image.Dispose();
grayscale_image = null;
}
}
}
return(0);
}