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 = assignment5.gaussPyramid(mask, depth)
gauss_pyr_black = assignment5.gaussPyramid(black_image, depth)
gauss_pyr_white = assignment5.gaussPyramid(white_image, depth)
lapl_pyr_black = assignment5.laplPyramid(gauss_pyr_black)
lapl_pyr_white = assignment5.laplPyramid(gauss_pyr_white)
outpyr = assignment5.blend(lapl_pyr_white, lapl_pyr_black, gauss_pyr_mask)
outimg = assignment5.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 test_gaussian_laplacian():
""" This script will perform a unit test on your Gaussian and Laplacian
pyramid functions.
"""
gauss_pyr1 =[np.array([[ 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 255., 255., 255., 255., 0., 0.],
[ 0., 0., 255., 255., 255., 255., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0., 0., 0., 0.]]),
np.array([[ 0.64, 8.92, 12.11, 3.82],
[ 8.29, 116.03, 157.46, 49.73],
[ 3.82, 53.55, 72.67, 22.95]]),
np.array([[ 12.21, 31.85],
[ 17.62, 45.97]]),
np.array([[ 9.77]])]
gauss_pyr2 = [np.array([[ 255., 255., 255., 255., 255., 255., 255.],
[ 255., 255., 255., 255., 255., 255., 255.],
[ 255., 255., 125., 125., 125., 255., 255.],
[ 255., 255., 125., 125., 125., 255., 255.],
[ 0., 0., 0., 0., 0., 0., 0.]]),
np.array([[ 124.62, 173.95, 173.95, 124.62],
[ 165.35, 183.1 , 183.1 , 165.35],
[ 51.6 , 49.2 , 49.2 , 51.6 ]]),
np.array([[ 72.85, 104.71],
[ 49.53, 68.66]]),
np.array([[ 31.37]])]
if __name__ == "__main__":
print 'Evaluating gaussPyramid.'
for pyr in gauss_pyr1, gauss_pyr2:
if __name__ == "__main__":
print "input:\n{}\n".format(pyr[0])
usr_out = assignment5.gaussPyramid(pyr[0], 3)
if not type(usr_out) == type(pyr):
if __name__ == "__main__":
print "Error- gaussPyramid out has type {}. Expected type is {}.".format(
type(usr_out), type(pyr))
return False
if not len(usr_out) == len(pyr):
if __name__ == "__main__":
print "Error- gaussPyramid out has len {}. Expected len is {}.".format(
len(usr_out), len(pyr))
return False
for usr_layer, true_layer in zip(usr_out, pyr):
if not type(usr_layer) == type(true_layer):
if __name__ == "__main__":
print "Error- output layer 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- gaussPyramid 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- gaussPyramid 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- gaussPyramid layer has value:\n{}\nExpected value:\n{}".format(
usr_layer, true_layer)
return False
if __name__ == "__main__":
print "gaussPyramid passed.\n"
print "Evaluating laplPyramid."
lapl_pyr1 =[np.array([[ -2.95, -10.04, -17.67, -22.09, -23.02, -16.73, -8.97, -4.01],
[ -9.82, -33.47, -58.9 , -73.63, -76.75, -55.78, -29.9 , -13.39],
[ -15.57, -53.07, 161.59, 138.24, 133.29, 166.55, -47.41, -21.23],
[ -13.32, -45.42, 175.06, 155.07, 150.83, 179.3 , -40.58, -18.17],
[ -8.55, -29.16, -51.33, -64.16, -66.88, -48.61, -26.05, -11.67],
[ -4.21, -14.34, -25.24, -31.55, -32.89, -23.91, -12.81, -5.74]]),
np.array([[ -11.59, -11.88, -13.1 , -11.22],
[ -7.53, 89.12, 124.84, 30.27],
[ -12.43, 25.91, 39.17, 2.97]]),
np.array([[ 5.96, 27.94],
[ 13.71, 43.53]]),
np.array([[ 9.77]])]
lapl_pyr2 =[np.array([[ 146.27, 118.15, 101.65, 97.53, 101.65, 118.15, 146.27],
[ 121.16, 93.25, 79.83, 76.48, 79.83, 93.25, 121.16],
[ 118.2 , 95.65, -41.91, -43.79, -41.91, 95.65, 118.2 ],
[ 156.61, 142.69, 9.62, 8.85, 9.62, 142.69, 156.6 ],
[ -52.02, -57.74, -57.68, -57.67, -57.68, -57.74, -52.02]]),
np.array([[ 64.97, 97.02, 95.12, 79.3 ],
[ 107.73, 109.16, 107.63, 122.01],
[ 7.53, -6.95, -7.81, 18.9 ]]),
np.array([[ 52.77, 92.16],
[ 36.98, 60.82]]),
np.array([[ 31.37]])]
for gauss_pyr, lapl_pyr in zip((gauss_pyr1, gauss_pyr2), (lapl_pyr1, lapl_pyr2)):
if __name__ == "__main__":
print "input:\n{}".format(gauss_pyr)
usr_out = assignment5.laplPyramid(gauss_pyr)
if not type(usr_out) == type(lapl_pyr):
if __name__ == "__main__":
print "Error- laplPyramid out has type {}. Expected type is {}.".format(
type(usr_out), type(lapl_pyr))
return False
if not len(usr_out) == len(lapl_pyr):
if __name__ == "__main__":
print "Error- laplPyramid out has len {}. Expected len is {}.".format(
len(usr_out), len(lapl_pyr))
return False
for usr_layer, true_layer in zip(usr_out, lapl_pyr):
if not type(usr_layer) == type(true_layer):
if __name__ == "__main__":
print "Error- output layer 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- laplPyramid 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- laplPyramid 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- laplPyramid layer has value:\n{}\nExpected value:\n{}".format(
usr_layer, true_layer)
return False
if __name__ == "__main__":
print "laplPyramid passed."
if __name__ == "__main__":
print "Tests for Gaussian and Laplacian Pyramid successful."
return True
