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。

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys

import numpy
from numpy import pi, sin, cos
from scipy.optimize import leastsq
import scipy, scipy.fftpack

import cv2


import matplotlib.pyplot as plt

def logpolar(src, center, magnitude_scale = 40):

    mat1 = cv.fromarray(numpy.float64(src))
    mat2 = cv.CreateMat(src.shape[0], src.shape[1], mat1.type)

    cv.LogPolar(mat1, mat2, center, magnitude_scale, \
                cv.CV_INTER_CUBIC+cv.CV_WARP_FILL_OUTLIERS)

    return numpy.asarray(mat2)

def zero_padding(src, dstshape, pos = (0, 0)):
    y, x = pos
    dst = numpy.zeros(dstshape)
    dst[y:src.shape[0] + y, x:src.shape[1] + x] = src
    return dst

def pocfunc_model(alpha, delta1, delta2, r, u):
    N1, N2 = r.shape
    V1, V2 = map(lambda x: 2 * x + 1, u)
    return lambda n1, n2: alpha / (N1 * N2) * sin((n1 + delta1) * V1 / N1 * pi) * sin((n2 + delta2) * V2 / N2 * pi)\
                                            / (sin((n1 + delta1) * pi / N1) * sin((n2 + delta2) * pi / N2))

def pocfunc(f, g, windowfunc = numpy.hanning, withlpf = False):
    m = numpy.floor(map(lambda x: x / 2.0, f.shape))
    u = map(lambda x: x / 2.0, m)

    # hanning window
    hy = windowfunc(f.shape[0])
    hx = windowfunc(f.shape[1])
    hw = hy.reshape(hy.shape[0], 1) * hx
    f = f * hw
    g = g * hw

    # compute 2d fft
    F = scipy.fftpack.fft2(f)
    G = scipy.fftpack.fft2(g)
    G_ = numpy.conj(G)
    R = F * G_ / numpy.abs(F * G_)

    if withlpf == True:
        R = scipy.fftpack.fftshift(R)
        lpf = numpy.ones(map(lambda x: x + 1.0, m))
        lpf = zero_padding(lpf, f.shape, u)
        R = R * lpf
        R = scipy.fftpack.fftshift(R)

    return scipy.fftpack.fftshift(numpy.real(scipy.fftpack.ifft2(R)))

def poc(f, g, fitting_shape = (9, 9)):
    # compute phase-only correlation
    center = map(lambda x: x / 2.0, f.shape)
    m = numpy.floor(map(lambda x: x / 2.0, f.shape))
    u = map(lambda x: x / 2.0, m)

    r = pocfunc(f, g)

    # least-square fitting
    max_pos = numpy.argmax(r)
    peak = (max_pos / f.shape[1], max_pos % f.shape[1])
    max_peak = r[peak[0], peak[1]]

    mf = numpy.floor(map(lambda x: x / 2.0, fitting_shape))
    fitting_area = r[peak[0] - mf[0] : peak[0] + mf[0] + 1,\
                     peak[1] - mf[1] : peak[1] + mf[1] + 1]

    p0 = [0.5, -(peak[0] - m[0]) - 0.02, -(peak[1] - m[1]) - 0.02]
    y, x = numpy.mgrid[-mf[0]:mf[0] + 1, -mf[1]:mf[1] + 1]
    y = y + peak[0] - m[0]
    x = x + peak[1] - m[1]
    errorfunction = lambda p: numpy.ravel(pocfunc_model(p[0], p[1], p[2], r, u)(y, x) - fitting_area)
    plsq = leastsq(errorfunction, p0)
    return (plsq[0][0], plsq[0][1], plsq[0][2])

def ripoc(f, g, M = 50, fitting_shape = (9, 9)):

    hy = numpy.hanning(f.shape[0])
    hx = numpy.hanning(f.shape[1])
    hw = hy.reshape(hy.shape[0], 1) * hx

    ff = f * hw
    gg = g * hw

    F = scipy.fftpack.fft2(ff)
    G = scipy.fftpack.fft2(gg)

    F = scipy.fftpack.fftshift(numpy.log(numpy.abs(F)))
    G = scipy.fftpack.fftshift(numpy.log(numpy.abs(G)))

    FLP = logpolar(F, (F.shape[0] / 2, F.shape[1] / 2), M)
    GLP = logpolar(G, (G.shape[0] / 2, G.shape[1] / 2), M)

    R = poc(FLP, GLP)

    angle = -R[1] / F.shape[0] * 360
    scale = 1.0 - R[2] / 100

    center = tuple(numpy.array(g.shape) / 2)
    rot = cv2.getRotationMatrix2D(center, -angle, 1.0 + (1.0 - scale))

    g_dash = cv2.warpAffine(g, rot, (g.shape[1], g.shape[0]), flags=cv2.INTER_LANCZOS4)

    t = poc(f, g_dash)

    return (t[1], t[2], angle, scale) 

エラーの修正方法を教えてほしいです。

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

というエラーが出ています。
cvとcv2の違いもいまいちわかっていないので何方か教えていただけないでしょうか
よろしく御願い致します。