from pylab import *
from numpy import *
from PIL import Image
from PCV.localdescriptors import harris
from PCV.tools.imtools import imresize
"""
This is the Harris point matching example in Figure 2-2.
"""
im1 = array(Image.open("data/crans_1_small.jpg").convert("L"))
im2 = array(Image.open("data/crans_2_small.jpg").convert("L"))
# resize to make matching faster
im1 = imresize(im1, (im1.shape[1] / 2, im1.shape[0] / 2))
im2 = imresize(im2, (im2.shape[1] / 2, im2.shape[0] / 2))
wid = 5
harrisim = harris.compute_harris_response(im1, 5)
filtered_coords1 = harris.get_harris_points(harrisim, wid + 1)
d1 = harris.get_descriptors(im1, filtered_coords1, wid)
harrisim = harris.compute_harris_response(im2, 5)
filtered_coords2 = harris.get_harris_points(harrisim, wid + 1)
d2 = harris.get_descriptors(im2, filtered_coords2, wid)
print 'starting matching'
matches = harris.match_twosided(d1, d2)
figure()
gray()
from pylab import *
from numpy import *
from PIL import Image
from PCV.localdescriptors import harris
from PCV.tools.imtools import imresize
"""
This is the Harris point matching example in Figure 2-2.
"""
im1 = array(Image.open("../data/crans_1_small.jpg").convert("L"))
im2 = array(Image.open("../data/crans_2_small.jpg").convert("L"))
# resize to make matching faster
im1 = imresize(im1,(im1.shape[1]/2,im1.shape[0]/2))
im2 = imresize(im2,(im2.shape[1]/2,im2.shape[0]/2))
wid = 5
harrisim = harris.compute_harris_response(im1,5)
filtered_coords1 = harris.get_harris_points(harrisim,wid+1)
d1 = harris.get_descriptors(im1,filtered_coords1,wid)
harrisim = harris.compute_harris_response(im2,5)
filtered_coords2 = harris.get_harris_points(harrisim,wid+1)
d2 = harris.get_descriptors(im2,filtered_coords2,wid)
print 'starting matching'
matches = harris.match_twosided(d1,d2)
figure()
from PCV.localdescriptors import harris
from PCV.tools.imtools import imresize
"""
This is the Harris point matching example in Figure 2-2.
"""
# Figure 2-2上面的图
im1 = array(Image.open("../data/crans_1_small.jpg").convert("L"))
im2 = array(Image.open("../data/crans_2_small.jpg").convert("L"))
# Figure 2-2下面的图
# im1 = array(Image.open("../data/sf_view1.jpg").convert("L"))
# im2 = array(Image.open("../data/sf_view2.jpg").convert("L"))
# resize to make matching faster
im1 = imresize(im1, (int(im1.shape[1] / 2), int(im1.shape[0] / 2)))
im2 = imresize(im2, (int(im2.shape[1] / 2), int(im2.shape[0] / 2)))
wid = 5
harrisim = harris.compute_harris_response(im1, 5)
filtered_coords1 = harris.get_harris_points(harrisim, wid + 1)
d1 = harris.get_descriptors(im1, filtered_coords1, wid)
harrisim = harris.compute_harris_response(im2, 5)
filtered_coords2 = harris.get_harris_points(harrisim, wid + 1)
d2 = harris.get_descriptors(im2, filtered_coords2, wid)
print('starting matching')
matches = harris.match_twosided(d1, d2)
figure()