def run_blend(black_image, white_image, mask):
""" This function administrates the blending of the two images according to
mask.
Assume all images are float dtype, and return a float dtype.
"""
# Automatically figure out the size
min_size = min(black_image.shape)
depth = int(math.floor(math.log(
min_size, 2))) - 4 # at least 16x16 at the highest level.
gauss_pyr_mask = assignment6.gaussPyramid(mask, depth)
gauss_pyr_black = assignment6.gaussPyramid(black_image, depth)
gauss_pyr_white = assignment6.gaussPyramid(white_image, depth)
lapl_pyr_black = assignment6.laplPyramid(gauss_pyr_black)
lapl_pyr_white = assignment6.laplPyramid(gauss_pyr_white)
outpyr = assignment6.blend(lapl_pyr_white, lapl_pyr_black, gauss_pyr_mask)
outimg = assignment6.collapse(outpyr)
outimg[
outimg <
0] = 0 # blending sometimes results in slightly out of bound numbers.
outimg[outimg > 255] = 255
outimg = outimg.astype(np.uint8)
return lapl_pyr_black, lapl_pyr_white, gauss_pyr_black, gauss_pyr_white, \
gauss_pyr_mask, outpyr, outimg
def run_blend(black_image, white_image, mask):
""" This function administrates the blending of the two images according to
mask.
Assume all images are float dtype, and return a float dtype.
"""
# Automatically figure out the size
min_size = min(black_image.shape)
depth = int(math.floor(math.log(min_size, 2))) - 4 # at least 16x16 at the highest level.
gauss_pyr_mask = assignment6.gaussPyramid(mask, depth)
gauss_pyr_black = assignment6.gaussPyramid(black_image, depth)
gauss_pyr_white = assignment6.gaussPyramid(white_image, depth)
lapl_pyr_black = assignment6.laplPyramid(gauss_pyr_black)
lapl_pyr_white = assignment6.laplPyramid(gauss_pyr_white)
outpyr = assignment6.blend(lapl_pyr_white, lapl_pyr_black, gauss_pyr_mask)
outimg = assignment6.collapse(outpyr)
outimg[outimg < 0] = 0 # blending sometimes results in slightly out of bound numbers.
outimg[outimg > 255] = 255
outimg = outimg.astype(np.uint8)
return lapl_pyr_black, lapl_pyr_white, gauss_pyr_black, gauss_pyr_white, \
gauss_pyr_mask, outpyr, outimg
def run_blend(black_image, white_image, mask):
"""
This function administrates the blending of the two images according to mask.
Assume all images are float dtype, and return a float dtype.
"""
# Automatically figure out the size
min_size = min(black_image.shape)
depth = int(math.floor(math.log(min_size, 2))) - 4 # at least 16x16 at the highest level
gauss_pyr_mask = a6.gaussPyramid(mask, depth)
gauss_pyr_black = a6.gaussPyramid(black_image, depth)
gauss_pyr_white = a6.gaussPyramid(white_image, depth)
lapl_pyr_black = a6.laplPyramid(gauss_pyr_black)
lapl_pyr_white = a6.laplPyramid(gauss_pyr_white)
outpyr = a6.blend(lapl_pyr_white, lapl_pyr_black, gauss_pyr_mask)
img = a6.collapse(outpyr)
return (gauss_pyr_black, gauss_pyr_white, gauss_pyr_mask,
lapl_pyr_black, lapl_pyr_white, outpyr, [img])
def test_blend_collapse():
""" This script will perform a unit test on your blend and collapse functions
and output any errors for debugging.
"""
lapl_pyr11 = [
np.array([[0., 0., 0., 0.], [0., 0., 0., 0.], [0., 0., 0., 0.]]),
np.array([[0., 0.], [0., 0.]])
]
lapl_pyr12 = [
np.array([[149.77, 122.46, 121.66, 178.69],
[138.08, 107.74, 106.84, 170.21],
[149.77, 122.46, 121.66, 178.69]]),
np.array([[124.95, 169.58], [124.95, 169.57]])
]
lapl_pyr21 = [
np.array([[149., 118.4, 99.2, 94.3, 99.2, 118.4, 149.],
[137.2, 103.3, 81.9, 76.5, 81.9, 103.3, 137.2],
[148.1, 117.4, 97.9, 93.1, 97.9, 117.4, 148.1],
[-63.1, -81.3, -92.8, -95.6, -92.8, -81.3, -63.1],
[-18.5, -23.8, -27.2, -28., -27.2, -23.8, -18.5]]),
np.array([[70.4, 107.1, 104.5, 82.3], [76.7, 115.4, 113.1, 87.3],
[-23.3, -29.4, -31., -16.3]]),
np.array([[67.7, 100.3], [34., 50.4]])
]
lapl_pyr22 = [
np.array([[-5., -25.2, -56.4, 149.8, 110.3, 116.2, 144.8],
[-6.5, -32.5, -72.6, 119.5, 68.6, 76.2, 113.],
[-7.2, -36., -80.3, 105.2, 48.9, 57.2, 98.],
[-6.5, -32.5, -72.6, 119.5, 68.6, 76.2, 113.],
[-5., -25.2, -56.4, 149.8, 110.3, 116.2, 144.8]]),
np.array([[-20.9, 4.8, 102.6, 84.1], [-23.2, 22.3, 167.9, 133.1],
[-20.9, 4.8, 102.6, 84.1]]),
np.array([[17.6, 90.8], [17.6, 90.8]])
]
mask_pyr1 = [
np.array([[0., 0., 1., 1.], [0., 0., 1., 1.], [0., 0., 1., 1.]]),
np.array([[0.03, 0.46], [0.03, 0.46]])
]
mask_pyr2 = [
np.array([[0., 0., 0., 0., 1., 1., 1.], [0., 0., 0., 0., 1., 1., 1.],
[0., 0., 0., 0., 1., 1., 1.], [0., 0., 0., 0., 1., 1., 1.],
[0., 0., 0., 0., 1., 1., 1.]]),
np.array([[0., 0., 0.5, 0.5], [0., 0., 0.7, 0.7], [0., 0., 0.5, 0.5]]),
np.array([[0., 0.3], [0., 0.3]])
]
out_pyr1 = [
np.array([[149.77, 122.46, 0., 0.], [138.08, 107.74, 0., 0.],
[149.77, 122.46, 0., 0.]]),
np.array([[120.58, 92.42], [120.58, 92.42]])
]
out_pyr2 = [
np.array([[-5., -25.2, -56.4, 149.8, 99.2, 118.4, 149.],
[-6.5, -32.5, -72.6, 119.5, 81.9, 103.3, 137.2],
[-7.2, -36., -80.3, 105.2, 97.9, 117.4, 148.1],
[-6.5, -32.5, -72.6, 119.5, -92.8, -81.3, -63.1],
[-5., -25.2, -56.4, 149.8, -27.2, -23.8, -18.5]]),
np.array([[-20.9, 4.8, 103.5, 83.2], [-23.2, 22.3, 129.5, 101.],
[-20.9, 4.8, 35.8, 33.9]]),
np.array([[17.6, 93.6], [17.6, 78.7]])
]
outimg1 = np.array([[244.91, 218.31, 77.39, 41.59],
[243.79, 214.24, 85.99, 46.21],
[244.91, 218.31, 77.39, 41.59]])
outimg2 = np.array([[0.1, 0.1, -0.1, 253.7, 241.3, 254., 256.],
[-0.3, -0.5, -2.7, 244.4, 250.3, 263.3, 263.2],
[-0.6, -1.4, -6., 233.4, 267.8, 278.2, 274.6],
[-0.9, -2.1, -8.7, 224.1, 42.2, 46.1, 37.3],
[-1., -2.4, -9.6, 221.2, 61.5, 59.5, 47.5]])
if __name__ == "__main__":
print 'Evaluating blend.'
for left_pyr, right_pyr, mask_pyr, out_pyr in ((lapl_pyr11, lapl_pyr12,
mask_pyr1, out_pyr1),
(lapl_pyr21, lapl_pyr22,
mask_pyr2, out_pyr2)):
usr_out = assignment6.blend(left_pyr, right_pyr, mask_pyr)
if not type(usr_out) == type(out_pyr):
if __name__ == "__main__":
print "Error- output layer has type {}. Expected type is {}.".format(
type(usr_out), type(out_pyr))
return False
if not len(usr_out) == len(out_pyr):
if __name__ == "__main__":
print "Error- blend out has len {}. Expected len is {}.".format(
len(usr_out), len(out_pyr))
return False
for usr_layer, true_layer, left_layer, right_layer, mask_layer in zip(
usr_out, out_pyr, left_pyr, right_pyr, mask_pyr):
if not type(usr_layer) == type(true_layer):
if __name__ == "__main__":
print "Error- blend out has type {}. Expected type is {}.".format(
type(usr_layer), type(true_layer))
return False
if not usr_layer.shape == true_layer.shape:
if __name__ == "__main__":
print "Error- blend output layer has shape {}. Expected shape is {}.".format(
usr_layer.shape, true_layer.shape)
return False
if not usr_layer.dtype == true_layer.dtype:
if __name__ == "__main__":
print "Error- blend output layer has dtype {}. Expected dtype is {}.".format(
usr_layer.dtype, true_layer.dtype)
return False
if not np.all(np.abs(usr_layer - true_layer) < 1):
if __name__ == "__main__":
print "Error- blend output layer has value:\n{}\nExpected value:\n{}\nInput left:\n{}\nInput right:\n{}\nInput mask:\n{}".format(
usr_layer, true_layer, left_layer, right_layer,
mask_layer)
return False
if __name__ == "__main__":
print "blend passed.\n"
print "Evaluating collapse."
for pyr, img in ((out_pyr1, outimg1), (out_pyr2, outimg2)):
if __name__ == "__main__":
print "input:\n{}".format(pyr)
usr_out = assignment6.collapse(pyr)
if not type(usr_out) == type(img):
if __name__ == "__main__":
print "Error- collapse out has type {}. Expected type is {}.".format(
type(usr_out), type(img))
return False
if not usr_out.shape == img.shape:
if __name__ == "__main__":
print "Error- collapse out has shape {}. Expected shape is {}.".format(
usr_out.shape, img.shape)
return False
if not usr_out.dtype == img.dtype:
if __name__ == "__main__":
print "Error- collapse out has dtype {}. Expected dtype is {}.".format(
usr_out.dtype, img.dtype)
return False
if not np.all(np.abs(usr_out - img) < 1):
if __name__ == "__main__":
print "Error- collapse out has value:\n{}\nExpected value:\n{}".format(
usr_out, img)
return False
if __name__ == "__main__":
print "collapse passed."
if __name__ == "__main__":
print "All unit tests successful."
return True
def test_blend_collapse():
""" This script will perform a unit test on your blend and collapse functions
and output any errors for debugging.
"""
lapl_pyr11 =[np.array([[ 0., 0., 0., 0.],
[ 0., 0., 0., 0.],
[ 0., 0., 0., 0.]]),
np.array([[ 0., 0.],
[ 0., 0.]])]
lapl_pyr12 =[np.array([[ 149.77, 122.46, 121.66, 178.69],
[ 138.08, 107.74, 106.84, 170.21],
[ 149.77, 122.46, 121.66, 178.69]]),
np.array([[ 124.95, 169.58],
[ 124.95, 169.57]])]
lapl_pyr21 =[np.array([[ 149. , 118.4, 99.2, 94.3, 99.2, 118.4, 149. ],
[ 137.2, 103.3, 81.9, 76.5, 81.9, 103.3, 137.2],
[ 148.1, 117.4, 97.9, 93.1, 97.9, 117.4, 148.1],
[ -63.1, -81.3, -92.8, -95.6, -92.8, -81.3, -63.1],
[ -18.5, -23.8, -27.2, -28. , -27.2, -23.8, -18.5]]),
np.array([[ 70.4, 107.1, 104.5, 82.3],
[ 76.7, 115.4, 113.1, 87.3],
[ -23.3, -29.4, -31. , -16.3]]),
np.array([[ 67.7, 100.3],
[ 34. , 50.4]])]
lapl_pyr22 =[np.array([[ -5. , -25.2, -56.4, 149.8, 110.3, 116.2, 144.8],
[ -6.5, -32.5, -72.6, 119.5, 68.6, 76.2, 113. ],
[ -7.2, -36. , -80.3, 105.2, 48.9, 57.2, 98. ],
[ -6.5, -32.5, -72.6, 119.5, 68.6, 76.2, 113. ],
[ -5. , -25.2, -56.4, 149.8, 110.3, 116.2, 144.8]]),
np.array([[ -20.9, 4.8, 102.6, 84.1],
[ -23.2, 22.3, 167.9, 133.1],
[ -20.9, 4.8, 102.6, 84.1]]),
np.array([[ 17.6, 90.8],
[ 17.6, 90.8]])]
mask_pyr1 =[np.array([[ 0., 0., 1., 1.],
[ 0., 0., 1., 1.],
[ 0., 0., 1., 1.]]),
np.array([[ 0.03, 0.46],
[ 0.03, 0.46]])]
mask_pyr2 = [np.array([[ 0., 0., 0., 0., 1., 1., 1.],
[ 0., 0., 0., 0., 1., 1., 1.],
[ 0., 0., 0., 0., 1., 1., 1.],
[ 0., 0., 0., 0., 1., 1., 1.],
[ 0., 0., 0., 0., 1., 1., 1.]]),
np.array([[ 0. , 0. , 0.5, 0.5],
[ 0. , 0. , 0.7, 0.7],
[ 0. , 0. , 0.5, 0.5]]),
np.array([[ 0. , 0.3],
[ 0. , 0.3]])]
out_pyr1 =[np.array([[ 149.77, 122.46, 0. , 0. ],
[ 138.08, 107.74, 0. , 0. ],
[ 149.77, 122.46, 0. , 0. ]]),
np.array([[ 120.58, 92.42],
[ 120.58, 92.42]])]
out_pyr2 = [np.array([[ -5. , -25.2, -56.4, 149.8, 99.2, 118.4, 149. ],
[ -6.5, -32.5, -72.6, 119.5, 81.9, 103.3, 137.2],
[ -7.2, -36. , -80.3, 105.2, 97.9, 117.4, 148.1],
[ -6.5, -32.5, -72.6, 119.5, -92.8, -81.3, -63.1],
[ -5. , -25.2, -56.4, 149.8, -27.2, -23.8, -18.5]]),
np.array([[ -20.9, 4.8, 103.5, 83.2],
[ -23.2, 22.3, 129.5, 101. ],
[ -20.9, 4.8, 35.8, 33.9]]),
np.array([[ 17.6, 93.6],
[ 17.6, 78.7]])]
outimg1 = np.array([[ 244.91, 218.31, 77.39, 41.59],
[ 243.79, 214.24, 85.99, 46.21],
[ 244.91, 218.31, 77.39, 41.59]])
outimg2 = np.array([[ 0.1, 0.1, -0.1, 253.7, 241.3, 254. , 256. ],
[ -0.3, -0.5, -2.7, 244.4, 250.3, 263.3, 263.2],
[ -0.6, -1.4, -6. , 233.4, 267.8, 278.2, 274.6],
[ -0.9, -2.1, -8.7, 224.1, 42.2, 46.1, 37.3],
[ -1. , -2.4, -9.6, 221.2, 61.5, 59.5, 47.5]])
if __name__ == "__main__":
print 'Evaluating blend.'
for left_pyr, right_pyr, mask_pyr, out_pyr in ((lapl_pyr11, lapl_pyr12, mask_pyr1, out_pyr1),
(lapl_pyr21, lapl_pyr22, mask_pyr2, out_pyr2)):
usr_out = assignment6.blend(left_pyr, right_pyr, mask_pyr)
if not type(usr_out) == type(out_pyr):
if __name__ == "__main__":
print "Error- output layer has type {}. Expected type is {}.".format(
type(usr_out), type(out_pyr))
return False
if not len(usr_out) == len(out_pyr):
if __name__ == "__main__":
print "Error- blend out has len {}. Expected len is {}.".format(
len(usr_out), len(out_pyr))
return False
for usr_layer, true_layer, left_layer, right_layer, mask_layer in zip(usr_out, out_pyr,
left_pyr, right_pyr, mask_pyr):
if not type(usr_layer) == type(true_layer):
if __name__ == "__main__":
print "Error- blend out has type {}. Expected type is {}.".format(
type(usr_layer), type(true_layer))
return False
if not usr_layer.shape == true_layer.shape:
if __name__ == "__main__":
print "Error- blend output layer has shape {}. Expected shape is {}.".format(
usr_layer.shape, true_layer.shape)
return False
if not usr_layer.dtype == true_layer.dtype:
if __name__ == "__main__":
print "Error- blend output layer has dtype {}. Expected dtype is {}.".format(
usr_layer.dtype, true_layer.dtype)
return False
if not np.all(np.abs(usr_layer - true_layer) < 1):
if __name__ == "__main__":
print "Error- blend output layer has value:\n{}\nExpected value:\n{}\nInput left:\n{}\nInput right:\n{}\nInput mask:\n{}".format(
usr_layer, true_layer, left_layer, right_layer, mask_layer)
return False
if __name__ == "__main__":
print "blend passed.\n"
print "Evaluating collapse."
for pyr, img in ((out_pyr1, outimg1),(out_pyr2, outimg2)):
if __name__ == "__main__":
print "input:\n{}".format(pyr)
usr_out = assignment6.collapse(pyr)
if not type(usr_out) == type(img):
if __name__ == "__main__":
print "Error- collapse out has type {}. Expected type is {}.".format(
type(usr_out), type(img))
return False
if not usr_out.shape == img.shape:
if __name__ == "__main__":
print "Error- collapse out has shape {}. Expected shape is {}.".format(
usr_out.shape, img.shape)
return False
if not usr_out.dtype == img.dtype:
if __name__ == "__main__":
print "Error- collapse out has dtype {}. Expected dtype is {}.".format(
usr_out.dtype, img.dtype)
return False
if not np.all(np.abs(usr_out - img) < 1):
if __name__ == "__main__":
print "Error- collapse out has value:\n{}\nExpected value:\n{}".format(
usr_out, img)
return False
if __name__ == "__main__":
print "collapse passed."
if __name__ == "__main__":
print "All unit tests successful."
return True
