opencv+python实现视频实时质心读取

利用opencv+python实现视频的实时质心读取：

# -*- coding: utf-8 -*-
"""
Created on Thu Apr 24 12:10:23 2018

@author: irene
"""

import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import spline  
import math as mt
import cv2

cap = cv2.VideoCapture('1.avi')  #读入视频
c=1
plt.figure(figsize=(8,8),dpi=80) 
aa =[]
bb =[]
cc =[]
#uing = np.logspace(-3,2,121)
while(cap.isOpened()):  
    ret, frame = cap.read() 
    #分解为一帧一帧图像
    if ret == True: 
        #cv2.imshow("frame"，image) 
        img=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY) #彩色转灰度  
       # print(frame)
       
       
       
        ret,thresh= cv2.threshold(img,127,255,0)   #二值化  
        image,contours,hierarchy = cv2.findContours(thresh, 3, 1)  
        img = cv2.medianBlur(image,5) #进行中值滤波

        cnt = contours[1]   #选取其中的第一个轮廓,这幅图像只有两个轮廓
        M = cv2.moments(cnt)  
        cX=int(M["m10"]/M["m00"])   #计算质心
        cY=int(M["m01"]/M["m00"])
        
        cv2.drawContours(img,contours,-1,(0,255,0),2)
        cv2.circle(img,(cX,cY),7,(255,255,255),-1)
        cv2.putText(img,"",(cX-20,cY-20),
        cv2.FONT_HERSHEY_SIMPLEX,0.5,(255,255,255),2) 
        
        cv2.imshow("img",img)
        cv2.imwrite('img/'+str(c) + '.jpg',frame) #存储为图像  
        
       # for u in uing:
        aa.append(cX)
        bb.append(cY)
        cc.append(c)
       # plt.plot(c,cX,'k-') 
        
        #plt.plot(c,cX,color='red',linewidth=2.5,linestyle=':')
       # plt.plot(c,cX,'k^') 
        #plt.plot(c,cY,'yo:')
        c = c+1  
              
    else:
          break  
   # cv2.imshow('frame',gray)  #显示标记后的图像q
     
    if cv2.waitKey(1) & 0xFF == ord('q'):  
         break  
    
cap.release()  
cv2.destroyAllWindows() 

c1=np.var(aa)
c2=np.var(bb)

c1_1=c1/720*2.3*mt.pi/180
c1_2=c2/512*2.3*mt.pi/180

print(c1_1)
print(c1_2)

plt.plot(cc,aa) 
plt.show()
plt.plot(cc,bb)
plt.show()