本节实现的是使用OpenCV里自带的函数，计算程序的执行时间。

• 获取系统时钟数
• 获取系统时钟频率

实现过程

初始时间

不再赘述，代码如下。

# time start
t1 = cv2.getTickCount()

执行代码

我这里执行的是之前绘制直方图的代码，请参考我的博客和GitHub。

结束时间

获取程序结束时间。

# time end
t2 = cv2.getTickCount()

计算执行秒数

利用getTickFrequency()获取时钟频率。

t = (t2-t1)/cv2.getTickFrequency()
print t

源代码

整个程序的源代码如下：

# created by Huang Lu
# 2016/8/26 17:35
# Department of EE, Tsinghua Univ.

import cv2
import numpy as np

# get the hist graph of a gray image
def HistGraphGray(image, color):    
    hist= cv2.calcHist([image], [0], None, [256], [0.0,255.0])       
    histGraph = np.zeros([256,256,3], np.uint8)
    m = max(hist)
    hist = hist * 220 / m
    for h in range(256): 
        n = int(hist[h])
        cv2.line(histGraph,(h,255), (h,255-n), color)        
    return histGraph; 

# get the hist graph of a color image
def HistGraphColor(image):
    histGraph = np.zeros([256,256,3], np.uint8)
    colorBlue = [255, 0, 0]
    colorGreen = [0, 255, 0]
    colorRed = [0, 0, 255]
    b, g, r = cv2.split(image)
    bhist = cv2.calcHist([b], [0], None, [256], [0.0,255.0])
    ghist = cv2.calcHist([g], [0], None, [256], [0.0,255.0]) 
    rhist = cv2.calcHist([r], [0], None, [256], [0.0,255.0])
    bm = max(bhist)
    gm = max(ghist)
    rm = max(rhist)
    bhist = bhist * 220 / bm
    rhist = rhist * 220 / rm
    ghist = ghist * 220 / gm
    for h in range(256):
        bn = int(bhist[h])
        gn = int(ghist[h])
        rn = int(rhist[h])
        if h != 0:
            cv2.line(histGraph,(h-1,255-bStart), (h,255-bn), colorBlue)
            cv2.line(histGraph,(h-1,255-gStart), (h,255-gn), colorGreen)
            cv2.line(histGraph,(h-1,255-rStart), (h,255-rn), colorRed)
        bStart = bn
        gStart = gn
        rStart = rn
    return histGraph

# main fuction
if __name__ == '__main__':
    # time start
    t1 = cv2.getTickCount()

    # test for a gray image
    img1 = cv2.imread("../test1.jpg", 0)
    color = [255, 255, 255]
    histGraph1 = HistGraphGray(img1, color)
    cv2.imshow("Hist Gray", histGraph1)

    # test for a color image
    img2 = cv2.imread("../test2.jpg")
    # first tset for three channels
    colorRed = [0, 0, 255]
    colorGreen = [0, 255, 0]
    colorBlue = [255, 0, 0]
    b, g, r = cv2.split(img2)
    # blue channel
    bhistGraph = HistGraphGray(b, colorBlue)
    cv2.imshow("Hist Blue", bhistGraph)
    # green channel
    ghistGraph = HistGraphGray(g, colorGreen)
    cv2.imshow("Hist Green", ghistGraph)
    # red channel
    rhistGraph = HistGraphGray(r, colorRed)
    cv2.imshow("Hist Red", rhistGraph)
    # get three channels together
    histGraph2 = HistGraphColor(img2)
    cv2.imshow("Hist Color", histGraph2)

    # time end
    t2 = cv2.getTickCount()
    t = (t2-t1)/cv2.getTickFrequency()
    print t

    cv2.waitKey(0)    
    cv2.destroyAllWindows()

也可以参考我的GitHub上的，点击这里。

运行结果

在命令行进入该源程序所在目录后，运行python main.py后即可显示结果。显示结果如下：

根据上图，程序用时0.103647207s。

参考

• OpenCV-Python-Toturial-中文版.pdf
• https://github.com/hlthu/Python-OpenCV-Learn/tree/master/Run_Time/