def getIris(frame): iris = [] copyImg = cv.CloneImage(frame) resImg = cv.CloneImage(frame) grayImg = cv.CreateImage(cv.GetSize(frame), 8, 1) mask = cv.CreateImage(cv.GetSize(frame), 8, 1) storage = cv.CreateMat(frame.width, 1, cv.CV_32FC3) cv.CvtColor(frame,grayImg,cv.CV_BGR2GRAY) cv.Canny(grayImg, grayImg, 5, 70, 3) cv.Smooth(grayImg,grayImg,cv.CV_GAUSSIAN, 7, 7) circles = getCircles(grayImg) iris.append(resImg) for circle in circles: rad = int(circle[0][2]) global radius radius = rad cv.Circle(mask, centroid, rad, cv.CV_RGB(255,255,255), cv.CV_FILLED) cv.Not(mask,mask) cv.Sub(frame,copyImg,resImg,mask) x = int(centroid[0] - rad) y = int(centroid[1] - rad) w = int(rad * 2) h = w cv.SetImageROI(resImg, (x,y,w,h)) cropImg = cv.CreateImage((w,h), 8, 3) cv.Copy(resImg,cropImg) cv.ResetImageROI(resImg) return(cropImg) return (resImg)
def lighting_quality(img):
try:
img2, out_dict = region_of_interest(img)
img3 = cv2.GetSubRect(img,GetImageROI(img2))
img4 = cv2.cvtColor(img2, cv2.COLOR_BGR2LAB)
roi = cv2.cvtColor(img3, cv2.COLOR_BGR2LAB)
background = cv2.Sub(img2,roi) # There may be an issue with the arrays not being of the same size.
b_background = np.mean(background[:,:,0]) # Mean might not be completely correct, mean of an array with many 0s in it, which are counted in the mean.
b_roi = np.mean(ROI[:,:,0])
lighting_measure = abs(np.log(b_roi/b_background))
out_dict = {"name" : "lighting_quality", "value" : lighting_measure}
except:
out_dict = {}
raise
return out_dict
def simplicity(img, gamma=0.1):
#NOTE Probably f****d up.
try:
img2, out_dict = region_of_interest(img)
img3 = cv2.GetSubRect(img,cv2.GetImageROI(img2))
background = cv2.Sub(img2,ROI) # There may be an issue with the arrays not being of the same size.
# Need to quantize the image into 16 channels.
hist,_binedges = np.histogram(background, bins=4096)
max_bound = max(list(hist))
color_div = 0.0
for item in list(hist):
if item >= gamma*max_bound:
color_div += item*item
simplicity_measure = np.sqrt(color_div)/4.096
out_dict = {"name" : "simplicity", "value" : simplicity_measure}
except:
out_dict = {}
raise
return out_dict
def process(self, img, ctx):
tmp = ctx[self.name]
sub = cv2.Sub(img, tmp)
return sub