model11.py-20170919

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Sep 17 15:16:51 2017@author: vicky
"""
import numpy as np
import cv2cap = cv2.VideoCapture('/Users/vicky/Desktop/附件2-典型视频/有晃动/cars6/input.mov')
#创建一个3*3的椭圆核
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(5,5))#形态学运算，膨胀
#创建BackgroundSubtractorMOG2
fgbg1 = cv2.createBackgroundSubtractorMOG2()#视频的背景分割,Foreground Segmentation Algorithm
fgbg2 = cv2.createBackgroundSubtractorKNN()
#fgbg3 = cv2.bgsegm.createBackgroundSubtractorMOG()
#fgbg4 = cv2.createBackgroundSubtractorGMG()  
# Define the codec and create VideoWriter object
#fps = cap.get(cv2.CAP_PROP_FPS)
size = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
#out = cv2.VideoWriter('output.avi', -1, fps, size)
fourcc=cv2.VideoWriter_fourcc('X','V','I','D')
out = cv2.VideoWriter('out.avi',fourcc,20.0,size)Z=[]while(1):ret1, frame1 = cap.read(0)ret2, frame2 = cap.read(0)if ret1 == True:#img_new = framefgmask1 = fgbg1.apply(frame1)fgmask2 = fgbg2.apply(frame2)# 形态学开运算去噪点fgmask1 = cv2.morphologyEx(fgmask1, cv2.MORPH_OPEN, kernel)fgmask2 = cv2.morphologyEx(fgmask2, cv2.MORPH_OPEN, kernel)#平滑方式去除噪声,blured1 = cv2.bilateralFilter(fgmask1, 10, 5, 5)blured2 = cv2.GaussianBlur(fgmask1, (3, 3), 0)blured3 = cv2.blur(fgmask1, (5, 5))blured4 = cv2.medianBlur(fgmask1, 5)fgmask = blured2# 闭运算去噪点fgmask1 = closing = cv2.morphologyEx(fgmask1, cv2.MORPH_CLOSE, kernel)fgmask2 = closing = cv2.morphologyEx(fgmask2, cv2.MORPH_CLOSE, kernel)#寻找视频中的轮廓im1, contours1, hierarchy1 = cv2.findContours(fgmask1, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)for c in contours1:#计算各轮廓的周长perimeter = cv2.arcLength(c,True)if perimeter > 50:# CV2.moments會傳回一系列的moments值，我們只要知道中點X, Y的取得方式是如下進行即可。M = cv2.moments(c)cX = int(M['m10'] / M['m00'])cY = int(M['m01'] / M['m00'])# 在中心點畫上黃色實心圓cv2.circle(frame1, (cX, cY), 10, (1, 227, 254), -1)#找到一个直矩形（不会旋转）x,y,w,h = cv2.boundingRect(c)#画出这个矩形cv2.rectangle(frame1,(x,y),(x+w,y+h),(0,255,0),2)# 用红色表示有旋转角度的矩形框架rect = cv2.minAreaRect(c)box = cv2.boxPoints(rect)box = np.int0(box)cv2.drawContours(frame1, [box], 0, (0, 0, 255), 2)#cv2.imwrite('contours.png', frame)im2, contours2, hierarchy2 = cv2.findContours(fgmask2, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)for c in contours2:#计算各轮廓的周长perimeter = cv2.arcLength(c,True)Z.append(perimeter)if perimeter > 50:
#                # CV2.moments會傳回一系列的moments值，我們只要知道中點X, Y的取得方式是如下進行即可。
#                M = cv2.moments(c)
#                cX = int(M['m10'] / M['m00'])
#                cY = int(M['m01'] / M['m00'])
#                # 在中心點畫上黃色實心圓
#                cv2.circle(frame2, (cX, cY), 10, (1, 227, 254), -1)
#                #找到一个直矩形（不会旋转）x,y,w,h = cv2.boundingRect(c)#画出这个矩形cv2.rectangle(frame2,(x,y),(x+w,y+h),(0,255,0),2)# 用红色表示有旋转角度的矩形框架rect = cv2.minAreaRect(c)box = cv2.boxPoints(rect)box = np.int0(box)cv2.drawContours(frame2, [box], 0, (0, 0, 255), 2)out.write(fgmask1)#out.write(fgmask2)cv2.imshow('frame1',frame1)cv2.imshow('frame2',frame2)cv2.imshow('fgmask1',fgmask1)cv2.imshow('fgmask2',fgmask2)else:breakif cv2.waitKey(25) & 0xFF == ord('q'):breakout.release()
cap.release()
cv2.destroyAllWindows()

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