コード例 #1
0
ファイル: testComplie.py プロジェクト: guchengxi1994/homework
"""

# set paths to data folder
featname = ['../data/wanren/uu' + str(i + 1) + '.sift' for i in range(5)]
imname = ['../data/wanren/uu' + str(i + 1) + '.jpg' for i in range(5)]

# extract features and match
l = {}
d = {}
for i in range(5):
    sift.process_image(root + imname[i], root + featname[i])
    l[i], d[i] = sift.read_features_from_file(featname[i])

matches = {}
for i in range(4):
    matches[i] = sift.match(d[i + 1], d[i])

# visualize the matches (Figure 3-11 in the book)
for i in range(4):
    im1 = array(Image.open(imname[i]))
    im2 = array(Image.open(imname[i + 1]))
    figure()
    sift.plot_matches(im2, im1, l[i + 1], l[i], matches[i], show_below=True)


# function to convert the matches to hom. points
def convert_points(j):
    ndx = matches[j].nonzero()[0]
    fp = homography.make_homog(l[j + 1][ndx, :2].T)
    ndx2 = [int(matches[j][i]) for i in ndx]
    tp = homography.make_homog(l[j][ndx2, :2].T)
コード例 #2
0
ファイル: ch3_panorama.py プロジェクト: BelmonduS/PCV
"""

# set paths to data folder
featname = ['../data/Univ'+str(i+1)+'.sift' for i in range(5)] 
imname = ['../data/Univ'+str(i+1)+'.jpg' for i in range(5)]

# extract features and match
l = {}
d = {}
for i in range(5): 
    # sift.process_image(imname[i],featname[i])
    l[i],d[i] = sift.read_features_from_file(featname[i])

matches = {}
for i in range(4):
    matches[i] = sift.match(d[i+1],d[i])

# visualize the matches (Figure 3-11 in the book)
for i in range(4):
    im1 = array(Image.open(imname[i]))
    im2 = array(Image.open(imname[i+1]))
    figure()
    sift.plot_matches(im2,im1,l[i+1],l[i],matches[i],show_below=True)


# function to convert the matches to hom. points
def convert_points(j):
    ndx = matches[j].nonzero()[0]
    fp = homography.make_homog(l[j+1][ndx,:2].T) 
    ndx2 = [int(matches[j][i]) for i in ndx]
    tp = homography.make_homog(l[j][ndx2,:2].T) 
コード例 #3
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# 载入查询图像特征
# load image features for query image
q_locs,q_descr = sift.read_features_from_file(featlist[q_ind])
fp = homography.make_homog(q_locs[:,:2].T)

# RANSAC model for homography fitting
model = homography.RansacModel()

rank = {}
# load image features for result
for ndx in res_reg[1:]:
    locs,descr = sift.read_features_from_file(featlist[ndx-1])  # because 'ndx' is a rowid of the DB that starts at 1.
    # locs,descr = sift.read_features_from_file(featlist[ndx])
    # get matches
    matches = sift.match(q_descr,descr)
    ind = matches.nonzero()[0]
    ind2 = matches[ind]
    tp = homography.make_homog(locs[:,:2].T)
    # compute homography, count inliers. if not enough matches return empty list
    try:
        H,inliers = homography.H_from_ransac(fp[:,ind],tp[:,ind2],model,match_theshold=4)
    except:
        inliers = []
    # store inlier count
    rank[ndx] = len(inliers)

# sort dictionary to get the most inliers first
sorted_rank = sorted(rank.items(), key=lambda t: t[1], reverse=True)
res_geom = [res_reg[0]]+[s[0] for s in sorted_rank]
print 'top matches (homography):', res_geom
コード例 #4
0
ファイル: 03.py プロジェクト: VRER1997/python_CV
q_ind = 0
nbr_results = 20

res_reg = [w[1] for w in src.query(imlist[q_ind])[:nbr_results]]
print 'top matches (regular) : ', res_reg

q_locs, q_descr = sift.read_features_from_file(featlist[q_ind])
fp = homography.make_homog(q_locs[:, :2].T)

model = homography.RansacModel()
rank = {}

for ndx in res_reg[1:]:
    locs, descr = sift.read_features_from_file(featlist[ndx])
    matches = sift.match(q_descr, descr)
    ind = matches.nonzero()[0]
    ind2 = matches[ind]
    tp = homography.make_homog(locs[:, :2].T)
    try:
        H, inliners = homography.H_from_ransac(fp[:, ind],
                                               tp[:, ind2],
                                               model,
                                               match_theshold=4)
    except:
        inliners = []
    rank[ndx] = len(inliners)

sorted_rank = sorted(rank.items(), key=lambda t: t[1], reverse=True)
res_geom = [res_reg[0]] + [s[0] for s in sorted_rank]
# 显示查询结果
コード例 #5
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  im1f, im2f = sys.argv[1], sys.argv[2]
else:
  im1f = r'e:\Study\pythonxyProject\sift\images/02.jpg'
  im2f = r'e:\Study\pythonxyProject\sift\images/04.jpg'
#  im1f = '../data/crans_1_small.jpg'
#  im2f = '../data/crans_2_small.jpg'
#  im1f = '../data/climbing_1_small.jpg'
#  im2f = '../data/climbing_2_small.jpg'
im1 = array(Image.open(im1f))
im2 = array(Image.open(im2f))

sift.process_image(im1f, 'out_sift_1.txt')
l1, d1 = sift.read_features_from_file('out_sift_1.txt')
figure()
gray()
subplot(121)
sift.plot_features(im1, l1, circle=False)

sift.process_image(im2f, 'out_sift_2.txt')
l2, d2 = sift.read_features_from_file('out_sift_2.txt')
subplot(122)
sift.plot_features(im2, l2, circle=False)

matches = sift.match(d1, d2)
matches = sift.match_twosided(d1, d2)
print '{} matches'.format(len(matches.nonzero()[0]))

figure()
gray()
sift.plot_matches(im1, im2, l1, l2, matches, show_below=True)
show()