def canny(F, s, high_threshold, low_threshold):
'''Apply a canny edge detector to the image.'''
blurred = gD(F, s, 0, 0)
filt = gauss1(1.4, f1_1)
Gx = convolve1d(blurred, filt, axis=0, mode='nearest')
Gy = convolve1d(blurred, filt, axis=1, mode='nearest')
G = zeros(F.shape)
angle = zeros(F.shape, dtype='int')
after_nm = zeros(F.shape)
# Finding intensity grade
for x in xrange(len(G[0])):
for y in xrange(len(G)):
G[x][y] = sqrt(Gx[x][y] ** 2 + Gy[x][y] ** 2)
angle[x][y] = int( \
round(arctan2(Gx[x][y], Gy[x][y]) * 4 / pi + 1)) % 4
# Non-maximum suppression
for x in xrange(len(G[0])):
for y in xrange(len(G)):
if angle[x][y] == 0:
side_one = G[x+1][y] if inImage(G, x+1, y) else 0
side_two = G[x-1][y] if inImage(G, x-1, y) else 0
elif angle[x][y] == 1:
side_one = G[x-1][y-1] if inImage(G, x-1, y-1) else 0
side_two = G[x+1][y+1] if inImage(G, x+1, y+1) else 0
elif angle[x][y] == 2:
side_one = G[x][y+1] if inImage(G, x, y+1) else 0
side_two = G[x][y-1] if inImage(G, x, y-1) else 0
elif angle[x][y] == 3:
side_one = G[x-1][y+1] if inImage(G, x-1, y+1) else 0
side_two = G[x+1][y-1] if inImage(G, x+1, y-1) else 0
if not (G[x][y] > side_one and G[x][y] > side_two):
after_nm[x][y] = 0
else:
after_nm[x][y] = G[x][y]
# Hysteresis thresholding
high_threshold *= (after_nm.max() - after_nm.min()) / 255
low_threshold *= (after_nm.max() - after_nm.min()) / 255
after_threshold = zeros(after_nm.shape, dtype = int)
def follow_edge(x, y):
"""Follow an edge by recursively checking if the neighbours are in
it."""
after_threshold[x][y] = 1
for x in xrange(-1, 2):
for y in xrange(-1, 2):
if (not x or not y):
if after_nm[x][y] >= low_threshold and not after_threshold:
follow_edge(x, y)
# Make border pixels zero
for i in xrange(len(after_nm[0])):
after_nm[i][0] = 0
after_nm[i][len(after_nm) - 1] = 0
for i in xrange(len(after_nm) - 1):
after_nm[0][i] = 0
after_nm[len(after_nm[0]) - 1][i] = 0
# Follow each line
for x in xrange(len(after_nm[0])):
for y in xrange(len(after_nm)):
if after_nm[x][y] >= high_threshold and not after_threshold[x][y]:
follow_edge(x, y)
return after_threshold
from sys import argv, exit
from gaussian_functions import gD
if len(argv) != 2:
print "Usage: python time.py s"
exit(1)
s = float(argv[1])
Image = imread('cameraman.png')
Images = zeros((6, Image.shape[0], Image.shape[1]))
labels = ['F', 'Fx', 'Fy', 'Fxx', 'Fxy', 'Fyy']
Images[0] = Image
j = 0
Images[1] = gD(Image, s, 1, 0)
Images[2] = gD(Image, s, 0, 1)
Images[3] = gD(Image, s, 2, 0)
Images[4] = gD(Image, s, 1, 1)
Images[5] = gD(Image, s, 0, 2)
figure()
for i in xrange(1, 10):
if i in [1, 4, 5, 7, 8, 9]:
subplot(330 + i)
axis('off')
imshow(Images[j], cmap='gray')
title(labels[j])
j += 1
s = float(argv[1])
method = argv[2]
show_out = int(argv[3])
Image = imread('cameraman.png')
if method == '2D':
Gs = gauss(s)
G = convolve(Image, Gs, mode='nearest')
elif method == '1D':
Gsx = gauss1(s, f1)
G2 = convolve1d(Image, Gsx, axis=0, mode='nearest')
G2 = convolve1d(G2, Gsx, axis=1, mode='nearest')
elif method == 'gD':
iorder = 2
jorder = 2
result = gD(Image, s, iorder, jorder)
else:
print "Invalid method"
exit(1)
if show_out == 1:
if method == '2D':
fig = figure()
X = arange(0, Gs.shape[0])
Y = arange(0, Gs.shape[1])
# create meshgrid
X, Y = meshgrid(X, Y)
# matplot lib version < 1.0 uses Axes3D
ax = Axes3D(fig)
