OpenCV-Python接口、cv和cv2的性能对比 [英] Performance comparison of OpenCV-Python interfaces, cv and cv2
问题描述
几天前，我开始使用新的 OpenCV-Python 接口，cv2.
A few days back, I started using new OpenCV-Python interface, cv2.
我的问题是关于cv和cv2接口的比较.
My question is regarding the comparison of cv and cv2 interface.
在易用性方面，新的cv2界面改进了很多，使用cv2真的很轻松有趣.
Regarding the ease of use, new cv2 interface has improved far greater, and it is really easy and fun to work with cv2.
但是速度呢?
我制作了两个小代码片段，一个在 cv 中，另一个在 cv2 中，以检查性能.两者都执行相同的功能，访问图像的像素，测试它，进行一些修改等.
I made two small code snipplets, one in cv and another in cv2, to check the performances. Both does the same function, access pixels of an image, test it, make some modifications, etc.
代码如下:
cv2 接口:
import time
import numpy as np
import cv2
gray = cv2.imread('sir.jpg',0)
width = gray.shape[0]
height = gray.shape[1]
h = np.empty([width,height,3])
t = time.time()
for i in xrange(width):
for j in xrange(height):
if gray[i,j]==127:
h[i,j]=[255,255,255]
elif gray[i,j]>127:
h[i,j]=[0,0,255-gray[i,j]]
else:
h[i,j]=[gray[i,j],0,0]
t2 = time.time()-t
print "time taken = ",t2
====================================================
=====================================================
结果是:
所用时间 = 14.4029130936
time taken = 14.4029130936
======================================================
======================================================
简历界面:
import cv,time
gray = cv.LoadImage('sir.jpg',0)
h = cv.CreateImage(cv.GetSize(gray),8,3)
t=time.time()
for i in xrange(gray.width):
for j in xrange(gray.height):
k = cv.Get2D(gray,j,i)[0]
if k==127:
cv.Set2D(h,j,i,(255,255,255))
elif k>127:
cv.Set2D(h,j,i,(0,0,255-k))
else:
cv.Set2D(h,j,i,(k,0,0))
t2 = time.time()-t
print "time taken = ",t2
cv.ShowImage('img',h)
cv.WaitKey(0)
======================================================
======================================================
结果是:
所用时间 = 1.16368889809
time taken = 1.16368889809
======================================================
=======================================================
看，这里旧的 cv 比 cv2 快 12 倍.结果图像是相同的.(输入图像大小为 720x540)
See, here old cv is about 12 times faster than cv2. And resulting images are same. (input image is of size 720x540)
为什么会发生这种情况?
Why does this happen?
cv2 比 cv 慢吗?
Is cv2 slower compared to cv?
或者我在这里犯了什么错误?上面的代码在cv2中有更快的方法吗?
Or am I making any mistake here? Is there a faster method in cv2 for the above code?
推荐答案
cv2.imread()返回的图片是NumPy的一个数组对象.所以你可以使用 NumPy 的函数来加速计算.
The image returned by cv2.imread() is an array object of NumPy. So you can use NumPy's functions to speedup calculation.
以下程序展示了如何通过使用 ndarray 对象的 item()、itemset() 方法来加速源 for 循环版本.
The following program shows how to speedup your origin for loop version by using item(), itemset() method of ndarray object.
import time
import numpy as np
import cv2
gray = cv2.imread('lena_full.jpg',0)
height, width = gray.shape
h = np.empty((height,width,3), np.uint8)
t = time.time()
for i in xrange(height):
for j in xrange(width):
k = gray.item(i, j)
if k == 127:
h.itemset(i, j, 0, 255)
h.itemset(i, j, 1, 255)
h.itemset(i, j, 2, 255)
elif k > 127:
h.itemset(i, j, 0, 0)
h.itemset(i, j, 1, 0)
h.itemset(i, j, 2, 255-k)
else:
h.itemset(i, j, 0, k)
h.itemset(i, j, 1, 0)
h.itemset(i, j, 2, 0)
print time.time()-t
而下面的程序展示了如何首先创建调色板，并使用 NumPy 的数组索引来获取结果:
And the following program show how to create the palette first, and use NumPy's array index to get the result:
t = time.time()
palette = []
for i in xrange(256):
if i == 127:
palette.append((255, 255, 255))
elif i > 127:
palette.append((0,0,255-i))
else:
palette.append((i, 0, 0))
palette = np.array(palette, np.uint8)
h2 = palette[gray]
print time.time() - t
print np.all(h==h2)
输出为:
0.453000068665
0.0309998989105
True
cv 版本输出为:
0.468999862671
注意:0轴长度为图片高度，1轴长度为图片宽度
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