def test_divider(self):
image = cv.LoadImage(
os.path.abspath(os.environ['BORG'] +
'/Brain/data/hog_test/noface.jpg'))
subRect = (0, 0, 250, 187)
subimage = self.divider.crop(image, subRect)
subimage1 = image
result = self.divider.divide(image, 2, 2)
if cv.GetSize(subimage) != cv.GetSize(result[0]):
self.fail(
"The subimage sizes are not correct. Either correctly crop the image manually or check divider function"
)
dif = cv.CreateImage(cv.GetSize(subimage), cv.IPL_DEPTH_8U, 3)
dif2 = cv.CreateImage(cv.GetSize(subimage), cv.IPL_DEPTH_8U, 3)
cv.AbsDiff(subimage, result[0], dif)
cv.Threshold(dif, dif2, 50, 255, cv.CV_THRESH_TOZERO)
for i in range(3):
cv.SetImageCOI(dif2, i + 1)
n_nonzero = cv.CountNonZero(dif2)
if n_nonzero < 400:
threshold = 0
else:
threshold = 1
self.assertEqual(threshold, 0, "The subimages are different")
result = self.divider.divide(image, 4, 4, option="pro")
print len(result)
print result
dif = cv.CreateImage(cv.GetSize(subimage1), cv.IPL_DEPTH_8U, 3)
dif2 = cv.CreateImage(cv.GetSize(subimage1), cv.IPL_DEPTH_8U, 3)
cv.AbsDiff(subimage1, result[0], dif)
cv.Threshold(dif, dif2, 50, 255, cv.CV_THRESH_TOZERO)
for i in range(3):
cv.SetImageCOI(dif2, i + 1)
n_nonzero = cv.CountNonZero(dif2)
if n_nonzero < 400:
threshold = 0
else:
threshold = 1
self.assertEqual(threshold, 0, "The subimages are different")
result = self.divider.divide(image, 4, 4, option="pro", overlap=10)
def test_0_Create(self):
image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
cnt = cv.CountNonZero(image)
self.assertEqual(cnt,
0,
msg="Created image is not black. CountNonZero=%i" %
cnt)
def somethingHasMoved(self):
nb = 0 #Will hold the number of black pixels
min_threshold = (
self.nb_pixels /
100) * self.threshold #Number of pixels for current threshold
nb = self.nb_pixels - cv.CountNonZero(self.res)
if (nb) > min_threshold:
return True
else:
return False
def test_2_CreateRepeat(self):
cnt = 0
for i in range(self.repeat):
image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
cnt += cv.CountNonZero(image)
self.assertEqual(
cnt,
0,
msg="Created images are not black. Mean CountNonZero=%.3f" %
(1. * cnt / self.repeat))
def test_40_tostringRepeat(self):
cnt = 0
image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
cv.Set(image, cv.Scalar(0, 0, 0, 0))
for i in range(self.repeat * 100):
image.tostring()
cnt = cv.CountNonZero(image)
self.assertEqual(cnt,
0,
msg="Repeating tostring(): Mean CountNonZero=%.3f" %
(1. * cnt / self.repeat))
def test_2a_MemCreated(self):
cnt = 0
v = []
for i in range(self.repeat):
image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
cv.FillPoly(image, [[(0, 0), (0, 100), (100, 0)]], 0)
cnt += cv.CountNonZero(image)
v.append(image)
self.assertEqual(
cnt,
0,
msg="Memorized images are not black. Mean CountNonZero=%.3f" %
(1. * cnt / self.repeat))
def test_4a_MemCreatedToString(self):
cnt = 0
v = []
for i in range(self.repeat):
image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
cv.Set(image, cv.Scalar(0, 0, 0, 0))
image.tostring()
cnt += cv.CountNonZero(image)
v.append(image)
self.assertEqual(
cnt,
0,
msg=
"Repeating and memorizing after tostring(): Mean CountNonZero=%.3f"
% (1. * cnt / self.repeat))
def test_3_tostirng(self):
image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
image.tostring()
cnt = cv.CountNonZero(image)
self.assertEqual(cnt, 0, msg="After tostring(): CountNonZero=%i" % cnt)