リンク内容

上のリンクを参考にpythonで回転不変位相限定相関を行っています。
上記のプログラム、上記の画像をそのまま利用して実行したのですが、エラーが出現してしまいます。

python
1#!/usr/bin/env python
2# -*- coding: utf-8 -*-
3import sys
4
5import numpy
6from numpy import pi, sin, cos
7from scipy.optimize import leastsq
8import scipy, scipy.fftpack
9
10import cv2
11
12
13import matplotlib.pyplot as plt
14
15def logpolar(src, center, magnitude_scale = 40):
16
17    mat1 = cv.fromarray(numpy.float64(src))
18    mat2 = cv.CreateMat(src.shape[0], src.shape[1], mat1.type)
19
20    cv.LogPolar(mat1, mat2, center, magnitude_scale, \
21                cv.CV_INTER_CUBIC+cv.CV_WARP_FILL_OUTLIERS)
22
23    return numpy.asarray(mat2)
24
25def zero_padding(src, dstshape, pos = (0, 0)):
26    y, x = pos
27    dst = numpy.zeros(dstshape)
28    dst[y:src.shape[0] + y, x:src.shape[1] + x] = src
29    return dst
30
31def pocfunc_model(alpha, delta1, delta2, r, u):
32    N1, N2 = r.shape
33    V1, V2 = map(lambda x: 2 * x + 1, u)
34    return lambda n1, n2: alpha / (N1 * N2) * sin((n1 + delta1) * V1 / N1 * pi) * sin((n2 + delta2) * V2 / N2 * pi)\
35                                            / (sin((n1 + delta1) * pi / N1) * sin((n2 + delta2) * pi / N2))
36
37def pocfunc(f, g, windowfunc = numpy.hanning, withlpf = False):
38    m = numpy.floor(map(lambda x: x / 2.0, f.shape))
39    u = map(lambda x: x / 2.0, m)
40
41    # hanning window
42    hy = windowfunc(f.shape[0])
43    hx = windowfunc(f.shape[1])
44    hw = hy.reshape(hy.shape[0], 1) * hx
45    f = f * hw
46    g = g * hw
47
48    # compute 2d fft
49    F = scipy.fftpack.fft2(f)
50    G = scipy.fftpack.fft2(g)
51    G_ = numpy.conj(G)
52    R = F * G_ / numpy.abs(F * G_)
53
54    if withlpf == True:
55        R = scipy.fftpack.fftshift(R)
56        lpf = numpy.ones(map(lambda x: x + 1.0, m))
57        lpf = zero_padding(lpf, f.shape, u)
58        R = R * lpf
59        R = scipy.fftpack.fftshift(R)
60
61    return scipy.fftpack.fftshift(numpy.real(scipy.fftpack.ifft2(R)))
62
63def poc(f, g, fitting_shape = (9, 9)):
64    # compute phase-only correlation
65    center = map(lambda x: x / 2.0, f.shape)
66    m = numpy.floor(map(lambda x: x / 2.0, f.shape))
67    u = map(lambda x: x / 2.0, m)
68
69    r = pocfunc(f, g)
70
71    # least-square fitting
72    max_pos = numpy.argmax(r)
73    peak = (max_pos / f.shape[1], max_pos % f.shape[1])
74    max_peak = r[peak[0], peak[1]]
75
76    mf = numpy.floor(map(lambda x: x / 2.0, fitting_shape))
77    fitting_area = r[peak[0] - mf[0] : peak[0] + mf[0] + 1,\
78                     peak[1] - mf[1] : peak[1] + mf[1] + 1]
79
80    p0 = [0.5, -(peak[0] - m[0]) - 0.02, -(peak[1] - m[1]) - 0.02]
81    y, x = numpy.mgrid[-mf[0]:mf[0] + 1, -mf[1]:mf[1] + 1]
82    y = y + peak[0] - m[0]
83    x = x + peak[1] - m[1]
84    errorfunction = lambda p: numpy.ravel(pocfunc_model(p[0], p[1], p[2], r, u)(y, x) - fitting_area)
85    plsq = leastsq(errorfunction, p0)
86    return (plsq[0][0], plsq[0][1], plsq[0][2])
87
88def ripoc(f, g, M = 50, fitting_shape = (9, 9)):
89
90    hy = numpy.hanning(f.shape[0])
91    hx = numpy.hanning(f.shape[1])
92    hw = hy.reshape(hy.shape[0], 1) * hx
93
94    ff = f * hw
95    gg = g * hw
96
97    F = scipy.fftpack.fft2(ff)
98    G = scipy.fftpack.fft2(gg)
99
100    F = scipy.fftpack.fftshift(numpy.log(numpy.abs(F)))
101    G = scipy.fftpack.fftshift(numpy.log(numpy.abs(G)))
102
103    FLP = logpolar(F, (F.shape[0] / 2, F.shape[1] / 2), M)
104    GLP = logpolar(G, (G.shape[0] / 2, G.shape[1] / 2), M)
105
106    R = poc(FLP, GLP)
107
108    angle = -R[1] / F.shape[0] * 360
109    scale = 1.0 - R[2] / 100
110
111    center = tuple(numpy.array(g.shape) / 2)
112    rot = cv2.getRotationMatrix2D(center, -angle, 1.0 + (1.0 - scale))
113
114    g_dash = cv2.warpAffine(g, rot, (g.shape[1], g.shape[0]), flags=cv2.INTER_LANCZOS4)
115
116    t = poc(f, g_dash)
117
118    return (t[1], t[2], angle, scale) 
119	
120

エラーの修正方法を教えてほしいです。

python
1>>> from poc import*
2>>> import cv2
3>>> img1=cv2.imread("lena.jpg",0)
4>>> img2=cv2.imread("lena_x59_y16_7_27deg.jpg",0)
5>>> ripoc(img1,img2)
6Traceback (most recent call last):
7  File "<stdin>", line 1, in <module>
8  line 103, in ripoc
9    FLP = logpolar(F, (F.shape[0] / 2, F.shape[1] / 2), M)
10  line 17, in logpolar
11    mat1 = cv.fromarray(numpy.float64(src))
12NameError: name 'cv' is not defined