質問編集履歴
5
エラーコードを修正しました。
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```python
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>>> from poc import
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>>> from poc import*
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>>> import cv2
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>>> ripoc(img1,
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>>> ripoc(img1,img2)
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Traceback (most recent call last):
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File "<stdin>", line 1, in <module>
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line 103, in ripoc
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FLP = logpolar(F, (F.shape[0] / 2, F.shape[1] / 2), M)
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line 17, in logpolar
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mat1 = cv.fromarray(numpy.float64(src))
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NameError: name 'cv' is not defined
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gg = g * hw
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TypeError: unsupported operand type(s) for *: 'NoneType' and 'float'
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```
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というエラーが出ています。
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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
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よろしく御願い致します。
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4
エラーコードの修正
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File "<stdin>", line 1, in <module>
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File "C:\
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File "C:\poc.py", line 95, in ripoc
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gg = g * hw
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3
エラーを修正しました。
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import poc
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img1 = cv2.imread("lena.jpg", 0)
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img2 = cv2.imread("lena_x59_y16_7.27deg.jpg", 0)
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ripoc(img1, img2)
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```
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```python
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>>> from poc import *
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>>> img1 = cv2.imread("lena.jpg", 0)
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>>> img2 = cv2.imread("lena_x59_y16_7.27deg.jpg", 0)
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>>>
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ripoc(img1, img2)
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>>> ripoc(img1, img2)
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Traceback (most recent call last):
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File "<stdin>", line 1, in <module>
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File "C:\Users\bb35116033\AppData\Local\Programs\Python\poc.py", line 95, in ripoc
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gg = g * hw
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2
プログラムを追加し、追加して新たに出たエラーコードを掲載しました。
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```python
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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import sys
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import numpy
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from numpy import pi, sin, cos
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from scipy.optimize import leastsq
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import scipy, scipy.fftpack
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import cv2
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import matplotlib.pyplot as plt
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def logpolar(src, center, magnitude_scale = 40):
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mat1 = cv.fromarray(numpy.float64(src))
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mat2 = cv.CreateMat(src.shape[0], src.shape[1], mat1.type)
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cv.LogPolar(mat1, mat2, center, magnitude_scale, \
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cv.CV_INTER_CUBIC+cv.CV_WARP_FILL_OUTLIERS)
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return numpy.asarray(mat2)
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def zero_padding(src, dstshape, pos = (0, 0)):
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y, x = pos
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dst = numpy.zeros(dstshape)
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dst[y:src.shape[0] + y, x:src.shape[1] + x] = src
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return dst
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def pocfunc_model(alpha, delta1, delta2, r, u):
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N1, N2 = r.shape
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V1, V2 = map(lambda x: 2 * x + 1, u)
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return lambda n1, n2: alpha / (N1 * N2) * sin((n1 + delta1) * V1 / N1 * pi) * sin((n2 + delta2) * V2 / N2 * pi)\
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/ (sin((n1 + delta1) * pi / N1) * sin((n2 + delta2) * pi / N2))
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def pocfunc(f, g, windowfunc = numpy.hanning, withlpf = False):
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m = numpy.floor(map(lambda x: x / 2.0, f.shape))
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u = map(lambda x: x / 2.0, m)
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# hanning window
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hy = windowfunc(f.shape[0])
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hx = windowfunc(f.shape[1])
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hw = hy.reshape(hy.shape[0], 1) * hx
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f = f * hw
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g = g * hw
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# compute 2d fft
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F = scipy.fftpack.fft2(f)
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G = scipy.fftpack.fft2(g)
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G_ = numpy.conj(G)
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R = F * G_ / numpy.abs(F * G_)
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if withlpf == True:
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R = scipy.fftpack.fftshift(R)
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lpf = numpy.ones(map(lambda x: x + 1.0, m))
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lpf = zero_padding(lpf, f.shape, u)
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R = R * lpf
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R = scipy.fftpack.fftshift(R)
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return scipy.fftpack.fftshift(numpy.real(scipy.fftpack.ifft2(R)))
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def poc(f, g, fitting_shape = (9, 9)):
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# compute phase-only correlation
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center = map(lambda x: x / 2.0, f.shape)
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m = numpy.floor(map(lambda x: x / 2.0, f.shape))
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u = map(lambda x: x / 2.0, m)
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r = pocfunc(f, g)
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# least-square fitting
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max_pos = numpy.argmax(r)
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peak = (max_pos / f.shape[1], max_pos % f.shape[1])
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max_peak = r[peak[0], peak[1]]
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mf = numpy.floor(map(lambda x: x / 2.0, fitting_shape))
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fitting_area = r[peak[0] - mf[0] : peak[0] + mf[0] + 1,\
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peak[1] - mf[1] : peak[1] + mf[1] + 1]
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p0 = [0.5, -(peak[0] - m[0]) - 0.02, -(peak[1] - m[1]) - 0.02]
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y, x = numpy.mgrid[-mf[0]:mf[0] + 1, -mf[1]:mf[1] + 1]
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y = y + peak[0] - m[0]
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x = x + peak[1] - m[1]
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errorfunction = lambda p: numpy.ravel(pocfunc_model(p[0], p[1], p[2], r, u)(y, x) - fitting_area)
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plsq = leastsq(errorfunction, p0)
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return (plsq[0][0], plsq[0][1], plsq[0][2])
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def ripoc(f, g, M = 50, fitting_shape = (9, 9)):
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hy = numpy.hanning(f.shape[0])
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hx = numpy.hanning(f.shape[1])
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hw = hy.reshape(hy.shape[0], 1) * hx
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ff = f * hw
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gg = g * hw
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F = scipy.fftpack.fft2(ff)
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G = scipy.fftpack.fft2(gg)
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F = scipy.fftpack.fftshift(numpy.log(numpy.abs(F)))
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G = scipy.fftpack.fftshift(numpy.log(numpy.abs(G)))
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FLP = logpolar(F, (F.shape[0] / 2, F.shape[1] / 2), M)
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GLP = logpolar(G, (G.shape[0] / 2, G.shape[1] / 2), M)
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R = poc(FLP, GLP)
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angle = -R[1] / F.shape[0] * 360
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scale = 1.0 - R[2] / 100
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center = tuple(numpy.array(g.shape) / 2)
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rot = cv2.getRotationMatrix2D(center, -angle, 1.0 + (1.0 - scale))
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g_dash = cv2.warpAffine(g, rot, (g.shape[1], g.shape[0]), flags=cv2.INTER_LANCZOS4)
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t = poc(f, g_dash)
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return (t[1], t[2], angle, scale)
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import poc
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img1 = cv2.imread("lena.jpg", 0)
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img2 = cv2.imread("lena_x59_y16_7.27deg.jpg", 0)
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ripoc(img1, img2)
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```
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11
269
|
エラーの修正方法を教えてほしいです。
|
|
12
270
|
|
|
13
271
|
```python
|
1
エラーコードを修正しました・
test
CHANGED
|
File without changes
|
test
CHANGED
|
@@ -12,8 +12,12 @@
|
|
|
12
12
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13
13
|
```python
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|
14
14
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15
|
-
|
|
15
|
+
import poc
|
|
16
16
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17
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+
ripoc(img1, img2)
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gg = g * hw
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17
|
-
|
|
21
|
+
TypeError: unsupported operand type(s) for *: 'NoneType' and 'float'
|
|
18
22
|
|
|
19
23
|
```
|