def scale_u_and_v(u, v, level, pyr):
"""Scales up U and V arrays to match the image dimensions assigned
to the first pyramid level: pyr[0].
You will use this method in part 3. In this section you are asked
to select a level in the gaussian pyramid which contains images
that are smaller than the one located in pyr[0]. This function
should take the U and V arrays computed from this lower level and
expand them to match a the size of pyr[0].
This function consists of a sequence of ps4.expand_image operations
based on the pyramid level used to obtain both U and V. Multiply
the result of expand_image by 2 to scale the vector values. After
each expand_image operation you should adjust the resulting arrays
to match the current level shape
i.e. U.shape == pyr[current_level].shape and
V.shape == pyr[current_level].shape. In case they don't, adjust
the U and V arrays by removing the extra rows and columns.
Hint: create a for loop from level-1 to 0 inclusive.
Both resulting arrays' shapes should match pyr[0].shape.
Args:
u: U array obtained from ps4.optic_flow_lk
v: V array obtained from ps4.optic_flow_lk
level: level value used in the gaussian pyramid to obtain U
and V (see part_3)
pyr: gaussian pyramid used to verify the shapes of U and V at
each iteration until the level 0 has been met.
Returns:
tuple: two-element tuple containing:
u (numpy.array): scaled U array of shape equal to
pyr[0].shape
v (numpy.array): scaled V array of shape equal to
pyr[0].shape
"""
i = level
while i != 0:
h, w = pyr[i - 1].shape
u = 2 * ps4.expand_image(u)
v = 2 * ps4.expand_image(v)
h_, w_ = u.shape
if h != h_:
u = u[:-1, :]
v = v[:-1, :]
if w % 2 != 0:
u = u[:, :-1]
v = v[:, :-1]
i = i - 1
# TODO: Your code here
return (u, v)
raise NotImplementedError
def scale_u_and_v(u, v, level, pyr):
"""Scales up U and V arrays to match the image dimensions assigned
to the first pyramid level: pyr[0].
You will use this method in part 3. In this section you are asked
to select a level in the gaussian pyramid which contains images
that are smaller than the one located in pyr[0]. This function
should take the U and V arrays computed from this lower level and
expand them to match a the size of pyr[0].
This function consists of a sequence of ps4.expand_image operations
based on the pyramid level used to obtain both U and V. Multiply
the result of expand_image by 2 to scale the vector values. After
each expand_image operation you should adjust the resulting arrays
to match the current level shape
i.e. U.shape == pyr[current_level].shape and
V.shape == pyr[current_level].shape. In case they don't, adjust
the U and V arrays by removing the extra rows and columns.
Hint: create a for loop from level-1 to 0 inclusive.
Both resulting arrays' shapes should match pyr[0].shape.
Args:
u: U array obtained from ps4.optic_flow_lk
v: V array obtained from ps4.optic_flow_lk
level: level value used in the gaussian pyramid to obtain U
and V (see part_3)
pyr: gaussian pyramid used to verify the shapes of U and V at
each iteration until the level 0 has been met.
Returns:
tuple: two-element tuple containing:
u (numpy.array): scaled U array of shape equal to
pyr[0].shape
v (numpy.array): scaled V array of shape equal to
pyr[0].shape
"""
U = u.copy()
V = v.copy()
for cur_level in range(level - 1, -1, -1):
U = ps4.expand_image(U) * 2
V = ps4.expand_image(V) * 2
h, w = pyr[cur_level].shape
V = V[:h, :w]
U = U[:h, :w]
return U, V
def test_expand(self):
input_imgs = [
'test_expand1_img.npy', 'test_expand2_img.npy',
'test_expand3_img.npy'
]
ref_imgs = [
'test_expand1_ref.npy', 'test_expand2_ref.npy',
'test_expand3_ref.npy'
]
for i in range(3):
f1 = input_imgs[i]
f2 = ref_imgs[i]
test_array = np.load(INPUT_DIR + f1)
expanded = ps4.expand_image(test_array.copy())
ref_expanded = np.load(INPUT_DIR + f2)
#print test_array.shape, "original"
#print expanded.shape, "expanded"
#print ref_expanded.shape, "reference"
#cv2.imshow("original",expanded)
#cv2.imshow("expanded",ref_expanded)
#cv2.waitKey(0)
#print expanded
#print ref_expanded
correct = np.allclose(expanded, ref_expanded, atol=0.05)
self.assertTrue(correct, "Output does not match the reference "
"solution.")
def test_expand(self):
input_imgs = [
'test_expand1_img.npy', 'test_expand2_img.npy',
'test_expand3_img.npy'
]
ref_imgs = [
'test_expand1_ref.npy', 'test_expand2_ref.npy',
'test_expand3_ref.npy'
]
for i in range(3):
f1 = input_imgs[i]
f2 = ref_imgs[i]
test_array = np.load(INPUT_DIR + f1)
expanded = ps4.expand_image(test_array.copy())
ref_expanded = np.load(INPUT_DIR + f2)
correct = np.allclose(expanded, ref_expanded, atol=0.05)
self.assertTrue(correct, "Output does not match the reference "
"solution.")
def scale_u_and_v(u, v, level, pyr):
"""Scales up U and V arrays to match the image dimensions assigned
to the first pyramid level: pyr[0].
You will use this method in part 3. In this section you are asked
to select a level in the gaussian pyramid which contains images
that are smaller than the one located in pyr[0]. This function
should take the U and V arrays computed from this lower level and
expand them to match a the size of pyr[0].
This function consists of a sequence of ps4.expand_image operations
based on the pyramid level used to obtain both U and V. Multiply
the result of expand_image by 2 to scale the vector values. After
each expand_image operation you should adjust the resulting arrays
to match the current level shape
i.e. U.shape == pyr[current_level].shape and
V.shape == pyr[current_level].shape. In case they don't, adjust
the U and V arrays by removing the extra rows and columns.
Hint: create a for loop from level-1 to 0 inclusive.
Both resulting arrays' shapes should match pyr[0].shape.
Args:
u: U array obtained from ps4.optic_flow_lk
v: V array obtained from ps4.optic_flow_lk
level: level value used in the gaussian pyramid to obtain U
and V (see part_3)
pyr: gaussian pyramid used to verify the shapes of U and V at
each iteration until the level 0 has been met.
Returns:
tuple: two-element tuple containing:
u (numpy.array): scaled U array of shape equal to
pyr[0].shape
v (numpy.array): scaled V array of shape equal to
pyr[0].shape
"""
# TODO: Your code here
"""
(uh, uw) = u.shape[:2]
(vh, vw) = v.shape[:2]
(h, w) = pyr[level].shape[:2]
if not uh == h:
U = U[:h-uh, :]
if not uw == w:
U = U[:, :w-uw]
if not vh == h:
V = V[:h-vh, :]
if not vw == w:
V = V[:, :w-vw]
"""
for lev in range(level, 0, -1):
img = pyr[lev]
(uh, uw) = u.shape[:2]
(vh, vw) = v.shape[:2]
(h, w) = img.shape[:2]
if not uh == h:
u = u[:h - uh, :]
if not uw == w:
u = u[:, :w - uw]
if not vh == h:
v = v[:h - vh, :]
if not vw == w:
v = v[:, :w - vw]
u, v = ps4.optic_flow_lk(ps4.expand_image(img) * 2)
img = pyr[0]
(uh, uw) = u.shape[:2]
(vh, vw) = v.shape[:2]
(h, w) = img.shape[:2]
if not uh == h:
u = u[:h - uh, :]
if not uw == w:
u = u[:, :w - uw]
if not vh == h:
v = v[:h - vh, :]
if not vw == w:
v = v[:, :w - vw]
return u, v