def measure(im, debug=False):
gray = image.rgb2gray(im)
_, s, v = image.split(image.rgb2hsv(im))
h = GrayscaleHist(bins=64).use_image(v)
s = GrayscaleHist(bins=64).use_image(s)
scores = [score_hist(h)]
if debug:
image.show(v, "1. Value")
image.show(h.to_img(), "2. Value Histogram")
image.show(s.to_img(), "2. Saturation Histogram")
print score_hist(s)
return (None, scores[0]) # h.to_img(),
def measure(im, debug=False):
gray = image.rgb2gray(im)
_, s, v = image.split(image.rgb2hsv(im))
h = GrayscaleHist(bins=64).use_image(v)
s = GrayscaleHist(bins=64).use_image(s)
scores = [score_hist(h)]
if debug:
image.show(v, "1. Value")
image.show(h.to_img(), "2. Value Histogram")
image.show(s.to_img(), "2. Saturation Histogram")
print score_hist(s)
return (
None, #h.to_img(),
scores[0],
)
def measure_color_roi(im, roi, area, focused_regions, debug=False):
im = cv.CloneImage(im)
g = Grid(cv.GetSize(im))
"""
contours = Contours(image.threshold(focused_regions, threshold=1)).approx_poly()
if debug:
test = image.new_from(im)
cv.Set(test, 0)
for c in contours:
i = 1
while c:
cv.FillPoly(test, [[c[x] for x in range(len(c))]], cv.RGB(0,64*i,0))
c = c.v_next()
i += 1
#contours.draw(test, levels=9)
image.show(test, "Test")
"""
#mask = image.And(image.threshold(focused_regions, threshold=1), roi)
#
#canvas = image.new_from(im, nChannels=1)
#cv.Set(canvas, 0)
#if cv.CountNonZero(mask) <= 1:
# return 0, 0
#contours = Contours(image.dilate(mask)).approx_poly()
#for c in contours:
# i = 1
# while c:
# cv.FillPoly(canvas, [[c[x] for x in range(len(c))]], 255)
# c = c.v_next()
# i += 1
#mask = image.Or(mask, canvas)
#if debug:
# image.show(mask, "MASK")
#
#cv.Set(im, 0, image.invert(mask))
cv.Set(im, 0, image.invert(roi))
#area = cv.CountNonZero(image.threshold(im, threshold=1))
if debug:
image.show(g.draw(im,thickness=2), "Image + ROI + Focus point mask")
scores = []
im = image.rgb2gray(im)
#canvas = image.And(plane, roi)
quadrants = g.split_in_four(im)
hist = []
for q,quad in enumerate(quadrants):
#scores.append(cv.Sum(quad)[0] / float(area/4))
h = GrayscaleHist(value_range=(1,255)).use_image(quad)
#image.show(h.to_img(), ['gray', 'red','green','blue'][i] + ' in ' + str(q))
hist.append(h.to_array())
scores = []
excluded_points = set([(2, 1), (3, 0)])
for i,h1 in enumerate(hist):
for j,h2 in enumerate(hist):
if i <= j or (i,j) in excluded_points:
continue
h = abs(h2-h1)
ht = GrayscaleHist(value_range=(0,255)).use_array_as_hist(h)
scores.append((h[5:].mean(), h[5:].std()))
means = max([x[0] for x in scores])
stddevs = max([x[1] for x in scores])
return means/255.0, stddevs/255.0
def measure_contrast(im, debug=False):
h = GrayscaleHist(bins=64).use_image(image.rgb2gray(im))
return h.stddev()