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Merge pull request #4073 from MSOpenTech:video-sample-face

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This commit is contained in:
Vadim Pisarevsky 2015-05-28 14:41:40 +00:00
commit 176dd96698
1 changed files with 77 additions and 23 deletions
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100
samples/winrt_universal/VideoCaptureXAML/video_capture_xaml/video_capture_xaml.Shared/main.cpp
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@ -28,22 +28,42 @@
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/objdetect.hpp>
#include <opencv2/features2d.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/videoio/cap_winrt.hpp>
// Switch definitions below to apply different filters
// TODO: add UX controls to manipulate filters at runtime
//#define COLOR
#define CANNY
//#define FACES
using namespace cv;
namespace video_capture_xaml {
// forward declaration
void cvFilterColor(Mat &frame);
void cvFilterCanny(Mat &frame);
void cvDetectFaces(Mat &frame);
CascadeClassifier face_cascade;
String face_cascade_name = "Assets/haarcascade_frontalface_alt.xml";
void cvMain()
{
VideoCapture cam;
//initializing frame counter used by face detection logic
long frameCounter = 0;
// loading classifier for face detection
face_cascade.load(face_cascade_name);
// open the default camera
VideoCapture cam;
cam.open(0);
Mat edges;
Mat frame;
// process frames
@ -51,37 +71,71 @@ namespace video_capture_xaml {
{
// get a new frame from camera - this is non-blocking per spec
cam >> frame;
frameCounter++;
// don't reprocess the same frame again
// nb if commented then flashing may occur
// if commented then flashing may occur
if (!cam.grab()) continue;
// image processing calculations here
// nb Mat frame is in RGB24 format (8UC3)
// Mat frame is in RGB24 format (8UC3)
// select processing type 1 or 2
#if 0
// image manipulation example #1
// write color bar at row 100 for 200 rows
auto ar = frame.ptr(100);
int bytesPerPixel = 3;
int adjust = (int)(((float)30 / 100.0f) * 255.0);
for (int i = 0; i < 640 * 100 * bytesPerPixel;)
{
ar[i++] = adjust; // R
i++; // G
ar[i++] = 255 - adjust; // B
// select processing type
#if defined COLOR
cvFilterColor(frame);
#elif defined CANNY
cvFilterCanny(frame);
#elif defined FACES
// processing every other frame to reduce the load
if (frameCounter % 2 == 0) {
cvDetectFaces(frame);
}
#else
// image processing example #2
// apply 'canny' filter
cvtColor(frame, edges, COLOR_RGB2GRAY);
GaussianBlur(edges, edges, Size(7, 7), 1.5, 1.5);
Canny(edges, edges, 0, 30, 3);
cvtColor(edges, frame, COLOR_GRAY2RGB);
#endif
// important step to get XAML image component updated
winrt_imshow();
}
}
// image processing example #1
// write color bar at row 100 for 200 rows
void cvFilterColor(Mat &frame)
{
auto ar = frame.ptr(100);
int bytesPerPixel = 3;
int adjust = (int)(((float)30 / 100.0f) * 255.0);
for (int i = 0; i < 640 * 100 * bytesPerPixel;)
{
ar[i++] = adjust; // R
i++; // G
ar[i++] = 255 - adjust; // B
}
}
// image processing example #2
// apply edge detection aka 'canny' filter
void cvFilterCanny(Mat &frame)
{
Mat edges;
cvtColor(frame, edges, COLOR_RGB2GRAY);
GaussianBlur(edges, edges, Size(7, 7), 1.5, 1.5);
Canny(edges, edges, 0, 30, 3);
cvtColor(edges, frame, COLOR_GRAY2RGB);
}
// image processing example #3
// detect human faces
void cvDetectFaces(Mat &frame)
{
Mat faces;
std::vector<cv::Rect> facesColl;
cvtColor(frame, faces, COLOR_RGB2GRAY);
equalizeHist(faces, faces);
face_cascade.detectMultiScale(faces, facesColl, 1.1, 2, 0 | CV_HAAR_SCALE_IMAGE, cv::Size(1, 1));
for (unsigned int i = 0; i < facesColl.size(); i++)
{
auto face = facesColl[i];
cv::rectangle(frame, face, cv::Scalar(0, 255, 255), 3);
}
}
}