def _detectSkin(self, bgrimg):
hsvimg = imgproc.bgr2hsv(bgrimg) # Trasform BGR to HSV
h,s,v = imgproc.split3(bgrimg) # Calculate H,S,V 3 Channels
skin_mask = cv.CreateImage(imgproc.size(hsvimg), cv.IPL_DEPTH_8U, 1)
h_mask = cv.CreateImage(imgproc.size(hsvimg), cv.IPL_DEPTH_8U, 1)
v_mask = cv.CreateImage(imgproc.size(hsvimg), cv.IPL_DEPTH_8U, 1)
v_mask = self.checkRange(v, self.v_low, self.v_high)
h_mask = self.checkRange(h, self.h_low, self.h_high)
cv.And(h_mask, v_mask, skin_mask)
return skin_mask
def checkRange(self, src, lowBound, highBound): size = imgproc.size(src) mask = cv.CreateImage(size, cv.IPL_DEPTH_8U, 1) gt_low = cv.CreateImage(size, cv.IPL_DEPTH_8U, 1) cv.CmpS(src, lowBound, gt_low, cv.CV_CMP_GT) lt_high = cv.CreateImage(size, cv.IPL_DEPTH_8U, 1) cv.CmpS(src, highBound, lt_high, cv.CV_CMP_LT) # CmpS Performs the per-element comparison of 2 arrays/1 array and scalar value. cv.And(gt_low, lt_high, mask) return mask
def detectSkin(self, bgrimg):
img_temp = cv.CreateImage(imgproc.size(bgrimg), bgrimg.depth, bgrimg.nChannels)
#cv.SaveImage("test.png", bgrimg)
cv.Smooth(bgrimg, img_temp, cv.CV_MEDIAN, 15)#, 0, 20, 20)
#cv.SaveImage("smooth.png", img_temp)
# cv.ShowImage("Obtain From Input", img_temp)
# cv.WaitKey(0)
#skin_o = self._detectSkin(bgrimg)
#cv.SaveImage("skin_o.png", skin_o)
skin = self._detectSkin(img_temp)
#cv.SaveImage("skin_s.png", skin)
return skin
def segment(self, bgrimg): segmented = cv.CreateImage(imgproc.size(bgrimg), bgrimg.depth, bgrimg.nChannels) cv.PyrSegmentation(bgrimg, segmented, self.storage, 3, 188, 60) return segmented
def detectSkin(self, bgrimg): img_temp = cv.CreateImage(imgproc.size(bgrimg), bgrimg.depth, bgrimg.nChannels) cv.Smooth(bgrimg, img_temp, cv.CV_MEDIAN, 15)#, 0, 20, 20) skin = self._detectSkin(img_temp) return skin
