python opencv背景减法 [英] Python opencv background subtraction

问题描述

我需要做的很简单:

1-加载5帧视频文件
2-检测背景
3-在每一帧上，一一:
-1-减去背景(创建前景蒙版)
-2-对前景蒙版进行一些计算
-3-保存原始帧和前景蒙版

1- load a 5 frames video file
2- detect background
3- On every frames, one by one :
-- 1- subtract background (create foreground mask)
-- 2- do some calculations on foreground mask
-- 3- save both original frame and foreground mask

只看5帧和5个对应的fgmasks:

Just to see the 5 frames and the 5 corresponding fgmasks :

import numpy as np
import cv2  
cap = cv2.VideoCapture('test.avi')
fgbg = cv2.BackgroundSubtractorMOG()

while(True):
    # Capture frame-by-frame
    ret, frame = cap.read()

    fgmask = fgbg.apply(frame)
    # Display the fgmask frame
    cv2.imshow('fgmask',fgmask)
    # Display original frame
    cv2.imshow('img', frame)

    k = cv2.waitKey(0) & 0xff
    if k == 5:
        break

cap.release()
cv2.destroyAllWindows()

打开并正确显示每个框架，但是显示的fgmask与显示的原始框架不对应.在此过程中的某个地方，fgmask的顺序变得混乱.

Every frame gets opened and displayed correctly but the showed fgmask do not correspond to the showed original frame. Somewhere in the process, the order of the fgmasks gets mixed up.

背景确实被正确减去，但是我没有得到5个预期的fgmasks.

The background does get subtracted correctly but I don't get the 5 expected fgmasks.

我想念什么?我觉得这应该很简单:while循环在视频的5帧上运行，并且fgbg.apply对每帧应用背景减法功能.

What am I missing ? I feel like this should be straightforward : the while loop runs over the 5 frames of the video and fgbg.apply apply the background subtraction function to each frame.

opencv-2.4.9-3

opencv-2.4.9-3

推荐答案

正如bikz05所建议的那样，运行平均方法在我的5个图像集上效果很好.谢谢你的提示！

As bikz05 suggested, running average method worked pretty good on my 5 images sets. Thanks for the tip !

import cv2
import numpy as np

c = cv2.VideoCapture('test.avi')
_,f = c.read()

avg1 = np.float32(f)
avg2 = np.float32(f)

# loop over images and estimate background 
for x in range(0,4):
    _,f = c.read()

    cv2.accumulateWeighted(f,avg1,1)
    cv2.accumulateWeighted(f,avg2,0.01)

    res1 = cv2.convertScaleAbs(avg1)
    res2 = cv2.convertScaleAbs(avg2)

    cv2.imshow('img',f)
    cv2.imshow('avg1',res1)
    cv2.imshow('avg2',res2)
    k = cv2.waitKey(0) & 0xff
    if k == 5:
        break

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