Mat skinDetector::detect(Mat captureframe, bool verboseSelect, Mat *skinMask)
{
verboseOutput=verboseSelect;
//if (argc>=1) frame = argv[1]);
//if (argc>=2) singleRegionChoice = int(argv[2]);
int step = 0;
Mat3b frame;
// Forcing resize to 640x480 -> all thresholds / pixel filters configured for this size.....
// Note returned to original size at end...
Size s = captureframe.size();
resize(captureframe,captureframe,Size(640,480));
// CHANGED HERE TO BGR
//cvtColor(captureframe, captureframe, CV_RGB2BGR);
if (verboseOutput) imshow("Raw Image (A)",captureframe);
/* THRESHOLD ON HSV*/
// HSV data -> used to find skin
cvtColor(captureframe, frame, CV_BGR2HSV);
//cvtColor(captureframe, frame, CV_BGR2HLS);
GaussianBlur(frame, frame, Size(imgBlurPixels,imgBlurPixels), 1, 1);
//medianBlur(frame, frame, 15);
for(int r=0; r<frame.rows; ++r){
for(int c=0; c<frame.cols; ++c)
// 0<H<0.25 - 0.15<S<0.9 - 0.2<V<0.95
if( (frame(r,c)[0]>5) && (frame(r,c)[0] < 17) && (frame(r,c)[1]>38) && (frame(r,c)[1]<250) && (frame(r,c)[2]>51) && (frame(r,c)[2]<242) ); // do nothing
else for(int i=0; i<3; ++i) frame(r,c)[i] = 0;
}
if (verboseOutput) imshow("Skin HSV (B)",frame);
/* BGR CONVERSION AND THRESHOLD */
Mat1b frame_gray;
cvtColor(frame, frame, CV_HSV2BGR);
cvtColor(frame, frame_gray, CV_BGR2GRAY);
// Adaptive thresholding technique
// 1. Threshold data to find main areas of skin
adaptiveThreshold(frame_gray,frame_gray,255,ADAPTIVE_THRESH_GAUSSIAN_C,THRESH_BINARY_INV,9,1);
if (verboseOutput) imshow("Adaptive_threshold (D1)",frame_gray);
// 2. Fill in thresholded areas
morphologyEx(frame_gray, frame_gray, CV_MOP_CLOSE, Mat1b(imgMorphPixels,imgMorphPixels,1), Point(-1, -1), 2);
//GaussianBlur(frame_gray, frame_gray, Size((imgBlurPixels*2)+1,(imgBlurPixels*2)+1), 1, 1);
GaussianBlur(frame_gray, frame_gray, Size(imgBlurPixels,imgBlurPixels), 1, 1);
// Select single largest region from image, if singleRegionChoice is selected (1)
if (singleRegionChoice)
{
*skinMask = cannySegmentation(frame_gray, -1);
}
else // Detect each separate block and remove blobs smaller than a few pixels
{
*skinMask = cannySegmentation(frame_gray, minPixelSize);
}
// Just return skin
Mat frame_skin;
captureframe.copyTo(frame_skin,*skinMask); // Copy captureframe data to frame_skin, using mask from frame_ttt
// Resize image to original before return
resize(frame_skin,frame_skin,s);
if (verboseOutput) imshow("Skin segmented",frame_skin);
return frame_skin;
waitKey(1);
}
Mat visionUtils::skinDetect(Mat captureframe, Mat3b *skinDetectHSV, Mat *skinMask, std::vector<int> adaptiveHSV, int minPixelSize, int imgBlurPixels, int imgMorphPixels, int singleRegionChoice, bool displayFaces)
{
if (adaptiveHSV.size()!=6 || adaptiveHSV.empty())
{
adaptiveHSV.clear();
adaptiveHSV.push_back(5);
adaptiveHSV.push_back(38);
adaptiveHSV.push_back(51);
adaptiveHSV.push_back(17);
adaptiveHSV.push_back(250);
adaptiveHSV.push_back(242);
}
//int step = 0;
Mat3b frameTemp;
Mat3b frame;
// Forcing resize to 640x480 -> all thresholds / pixel filters configured for this size.....
// Note returned to original size at end...
Size s = captureframe.size();
cv::resize(captureframe,captureframe,Size(640,480));
if (useGPU)
{
GpuMat imgGPU, imgGPUHSV;
imgGPU.upload(captureframe);
cv::cvtColor(imgGPU, imgGPUHSV, CV_BGR2HSV);
GaussianBlur(imgGPUHSV, imgGPUHSV, Size(imgBlurPixels,imgBlurPixels), 1, 1);
imgGPUHSV.download(frameTemp);
}
else
{
cv::cvtColor(captureframe, frameTemp, CV_BGR2HSV);
GaussianBlur(frameTemp, frameTemp, Size(imgBlurPixels,imgBlurPixels), 1, 1);
}
// Potential FASTER VERSION using inRange
Mat frameThreshold = Mat::zeros(frameTemp.rows,frameTemp.cols, CV_8UC1);
Mat hsvMin = (Mat_<int>(1,3) << adaptiveHSV[0], adaptiveHSV[1],adaptiveHSV[2] );
Mat hsvMax = (Mat_<int>(1,3) << adaptiveHSV[3], adaptiveHSV[4],adaptiveHSV[5] );
inRange(frameTemp,hsvMin ,hsvMax, frameThreshold);
frameTemp.copyTo(frame,frameThreshold);
/* BGR CONVERSION AND THRESHOLD */
Mat1b frame_gray;
// send HSV to skinDetectHSV for return
*skinDetectHSV=frame.clone();
cv::cvtColor(frame, frame_gray, CV_BGR2GRAY);
// Adaptive thresholding technique
// 1. Threshold data to find main areas of skin
adaptiveThreshold(frame_gray,frame_gray,255,ADAPTIVE_THRESH_GAUSSIAN_C,THRESH_BINARY_INV,9,1);
if (useGPU)
{
GpuMat imgGPU;
imgGPU.upload(frame_gray);
// 2. Fill in thresholded areas
#if CV_MAJOR_VERSION == 2
gpu::morphologyEx(imgGPU, imgGPU, CV_MOP_CLOSE, Mat1b(imgMorphPixels,imgMorphPixels,1), Point(-1, -1), 2);
gpu::GaussianBlur(imgGPU, imgGPU, Size(imgBlurPixels,imgBlurPixels), 1, 1);
#elif CV_MAJOR_VERSION == 3
//TODO: Check if that's correct
Mat element = getStructuringElement(MORPH_RECT, Size(imgMorphPixels, imgMorphPixels), Point(-1, -1));
Ptr<cuda::Filter> closeFilter = cuda::createMorphologyFilter(MORPH_CLOSE, imgGPU.type(), element, Point(-1, -1), 2);
closeFilter->apply(imgGPU, imgGPU);
cv::Ptr<cv::cuda::Filter> gaussianFilter = cv::cuda::createGaussianFilter(imgGPU.type(), imgGPU.type(), Size(imgMorphPixels, imgMorphPixels), 1, 1);
gaussianFilter->apply(imgGPU, imgGPU);
#endif
imgGPU.download(frame_gray);
}
else
{
// 2. Fill in thresholded areas
morphologyEx(frame_gray, frame_gray, CV_MOP_CLOSE, Mat1b(imgMorphPixels,imgMorphPixels,1), Point(-1, -1), 2);
GaussianBlur(frame_gray, frame_gray, Size(imgBlurPixels,imgBlurPixels), 1, 1);
// Select single largest region from image, if singleRegionChoice is selected (1)
}
if (singleRegionChoice)
{
*skinMask = cannySegmentation(frame_gray, -1, displayFaces);
}
else // Detect each separate block and remove blobs smaller than a few pixels
{
*skinMask = cannySegmentation(frame_gray, minPixelSize, displayFaces);
}
// Just return skin
Mat frame_skin;
captureframe.copyTo(frame_skin,*skinMask); // Copy captureframe data to frame_skin, using mask from frame_ttt
// Resize image to original before return
cv::resize(frame_skin,frame_skin,s);
if (displayFaces)
{
imshow("Skin HSV (B)",frame);
imshow("Adaptive_threshold (D1)",frame_gray);
imshow("Skin segmented",frame_skin);
}
return frame_skin;
waitKey(1);
}
