問題描述
幾天前，我開始使用新的 OpenCV-Python 接口，cv2.
A few days back, I started using new OpenCV-Python interface, cv2.
我的問題是關于 cv 和 cv2 接口的比較.
My question is regarding the comparison of cv and cv2 interface.
在易用性方面，新的 cv2 界面有了很大的改進，使用 cv2 真的很簡單有趣.
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?
我制作了兩個小代碼片段，一個在 cv 中，另一個在 cv2 中，以檢查性能.兩者都執行相同的功能，訪問圖像的像素，對其進行測試，進行一些修改等.
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.
下面是代碼:
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
======================================================
=====================================================
結果是:
所用時間 = 14.4029130936
time taken = 14.4029130936
=======================================================
======================================================
簡歷界面:
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)
=======================================================
======================================================
結果是:
所用時間 = 1.16368889809
time taken = 1.16368889809
========================================================
=======================================================
看，這里舊的 cv 比 cv2 快 12 倍.結果圖像是相同的.(輸入圖像大小為 720x540)
See, here old cv is about 12 times faster than cv2. And resulting images are same. (input image is of size 720x540)
為什么會這樣?
cv2 比 cv 慢嗎?
Is cv2 slower compared to cv?
或者我在這里犯了什么錯誤?以上代碼在cv2中有更快的方法嗎?
Or am I making any mistake here? Is there a faster method in cv2 for the above code?
推薦答案
cv2.imread()返回的圖片是NumPy的數組對象.所以你可以使用 NumPy 的函數來加速計算.
The image returned by cv2.imread() is an array object of NumPy. So you can use NumPy's functions to speedup calculation.
下面的程序展示了如何使用 ndarray 對象的 item(), itemset() 方法來加速你的 origin for 循環版本.
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
下面的程序展示了如何首先創建調色板，并使用 NumPy 的數組索引來獲取結果:
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)
輸出是:
0.453000068665
0.0309998989105
True
cv 版本輸出為:
0.468999862671
注意:0軸的長度是圖片的高度，1軸的長度是圖片的寬度
這篇關于OpenCV-Python接口、cv和cv2的性能比較的文章就介紹到這了，希望我們推薦的答案對大家有所幫助，也希望大家多多支持html5模板網！