使用带有Python和OpenCV的Raspberry Pi和Android IP摄像机进行对象检测

如何解决使用带有Python和OpenCV的Raspberry Pi和Android IP摄像机进行对象检测

这是我使用树莓派和Android Ip Camera进行对象检测的代码。在这里，我没有任何输出，代码也没有提供任何错误。有人可以找出错误所在吗？

import urllib.request
import cv2
import numpy as np
import datetime
import math

#global variables
width = 0
height = 0
EntranceCounter = 0
ExitCounter = 0
MinCountourArea = 3000  #Adjust ths value according to your usage
BinarizationThreshold = 70  #Adjust ths value according to your usage
OffsetRefLines = 150  #Adjust ths value according to your usage

#Check if an object in entering in monitored zone
def CheckEntranceLineCrossing(y,CoorYEntranceLine,CoorYExitLine):
  Absdistance = abs(y - CoorYEntranceLine)  

  if ((Absdistance <= 2) and (y < CoorYExitLine)):
                 return 1
  else:
                 return 0
#Check if an object in exitting from monitored zone
def CheckExitLineCrossing(y,CoorYExitLine):
    Absdistance = abs(y - CoorYExitLine)    

    if ((Absdistance <= 2) and (y > CoorYEntranceLine)):
                   return 1
    else:

                   return 0

这是我用来从IP摄像机获取视频流的代码

ReferenceFrame = None

while True:
  camera=cv2.VideoCapture("http://192.168.1.6:8080/shot.jpg")
  camera.set(3,640)
  camera.set(4,480)
  (ret,Frame)=camera.read()
  height = np.size(Frame,0)
  width = np.size(Frame,1)

#if cannot grab a frame,this program ends here.
  if not ret:
    break

这是我用来显示用于检测和计数物体的线条和框架的代码部分

#gray-scale convertion and Gaussian blur filter applying
    GrayFrame = cv2.cvtColor(Frame,cv2.COLOR_BGR2GRAY)
    GrayFrame = cv2.GaussianBlur(GrayFrame,(21,21),0)
    
    if ReferenceFrame is None:
        ReferenceFrame = GrayFrame
        continue

    #Background subtraction and image binarization
    FrameDelta = cv2.absdiff(ReferenceFrame,GrayFrame)
    FrameThresh = cv2.threshold(FrameDelta,BinarizationThreshold,255,cv2.THRESH_BINARY)[1]
    
    #Dilate image and find all the contours
    FrameThresh = cv2.dilate(FrameThresh,None,iterations=2)
    _,cnts,_ = cv2.findContours(FrameThresh.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

    QttyOfContours = 0

    #plot reference lines (entrance and exit lines) 
    CoorYEntranceLine = (height / 2)-OffsetRefLines
    CoorYExitLine = (height / 2)+OffsetRefLines
    cv2.line(Frame,(0,CoorYEntranceLine),(width,(255,0),2)
    cv2.line(Frame,CoorYExitLine),255),2)


    #check all found countours
    for c in cnts:
        #if a contour has small area,it'll be ignored
        if cv2.contourArea(c) < MinCountourArea:
            continue

        QttyOfContours = QttyOfContours+1    

        #draw an rectangle "around" the object
        (x,y,w,h) = cv2.boundingRect(c)
        cv2.rectangle(Frame,(x,y),(x + w,y + h),2)

        #find object's centroid
        Coordxcentroid = (x+x+w)/2
        CoordYCentroid = (y+y+h)/2
        ObjectCentroid = (Coordxcentroid,CoordYCentroid)
        cv2.circle(Frame,ObjectCentroid,1,5)
        
        if (CheckEntranceLineCrossing(CoordYCentroid,CoorYExitLine)):
            EntranceCounter += 1

        if (CheckExitLineCrossing(CoordYCentroid,CoorYExitLine)):  
            ExitCounter += 1

    print ("Total countours found: "+str(QttyOfContours))

    #Write entrance and exit counter values on frame and shows it
    cv2.putText(Frame,"Entrances: {}".format(str(EntranceCounter)),(10,50),cv2.FONT_HERShey_SIMPLEX,0.5,(250,1),2)
    cv2.putText(Frame,"Exits: {}".format(str(ExitCounter)),70),2)




   
  cv2.imshow('Salida',Frame)
  cv2.waitKey(1);

# When everything done,release the capture 
cap.release()
cv2.destroyAllWindows()

解决方法

正确的密码

import numpy as np
import math

def nothing(x):
    pass
width=0
height=0
EntranceCounter = 0
OffsetRefLines = 150
ExitCounter = 0
BinarizationThreshold = 70
MinCountourArea = 3000

cap = cv2.VideoCapture(0);
path="http://192.168.1.6:8080/video"
cap.open(path)
ReferenceFrame = None

#Check if an object in entering in monitored zone
def CheckEntranceLineCrossing(y,CoorYEntranceLine,CoorYExitLine):
  AbsDistance = abs(y - CoorYEntranceLine)  

  if ((AbsDistance <= 2) and (y < CoorYExitLine)):
                 return 1
  else:
                 return 0

#Check if an object in exitting from monitored zone
def CheckExitLineCrossing(y,CoorYExitLine):
    AbsDistance = abs(y - CoorYExitLine)    

    if ((AbsDistance <= 2) and (y > CoorYEntranceLine)):
                   return 1
    else:

                   return 0


#cv2.namedWindow("Tracking")
cv2.createTrackbar("LH","Tracking",255,nothing)
cv2.createTrackbar("LS",nothing)
cv2.createTrackbar("LV",nothing)
cv2.createTrackbar("UH",nothing)
cv2.createTrackbar("US",nothing)
cv2.createTrackbar("UV",nothing)

while True:
    #frame = cv2.imread('smarties.png')
  if cap.isOpened():
      rval,frame = cap.read()
    

  while rval:
    rval,frame = cap.read()
    hsv = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
    hsv = cv2.GaussianBlur(hsv,(21,21),0)

    if ReferenceFrame is None:
        ReferenceFrame = hsv
        continue
    
    #Background subtraction and image binarization
    FrameDelta = cv2.absdiff(ReferenceFrame,hsv)
    FrameThresh = cv2.threshold(FrameDelta,25,cv2.THRESH_BINARY)[1]

    #Dilate image and find all the contours
    FrameThresh = cv2.dilate(FrameThresh,None,iterations=2)
    cnts,_ = cv2.findContours(FrameThresh,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

    QttyOfContours = 0
    
    #plot reference lines (entrance and exit lines) 
    cv2.line(frame,(0,170),(2000,(255,0),5)

    cv2.line(frame,470),255),5)

    #check all found countours
    for c in cnts:
        #if a contour has small area,it'll be ignored
        if cv2.contourArea(c) < MinCountourArea:
            continue

        QttyOfContours = QttyOfContours+1    

        #draw an rectangle "around" the object
        (x,y,w,h) = cv2.boundingRect(c)
        cv2.rectangle(frame,(x,y),(x + w,y + h),2)


        #find object's centroid
        CoordXCentroid = int(x+x+w)/2
        CoordYCentroid = int(y+y+h)/2
        ObjectCentroid = (x,y)
        cv2.circle(frame,ObjectCentroid,2,5)

        if (CheckEntranceLineCrossing(CoordYCentroid,170,470)):
            EntranceCounter += 1

        if (CheckExitLineCrossing(CoordYCentroid,470)):  
            ExitCounter += 1

        print ("Total countours found: "+str(QttyOfContours))


        
        #Write entrance and exit counter values on frame and shows it
    cv2.putText(frame,"Entrances: {}".format(str(EntranceCounter)),(10,50),cv2.FONT_HERSHEY_SIMPLEX,(250,1),2)
    cv2.putText(frame,"Exits: {}".format(str(ExitCounter)),110),2)



    imS = cv2.resize(frame,(400,400))                    # Resize image
    #imSS = cv2.resize(mask,(200,200)) 
    #imSSS = cv2.resize(frame,200))   
    cv2.imshow("frame",imS)
    #cv2.imshow("mask",imSS)
    #cv2.imshow("res",imSSS)

    key = cv2.waitKey(1)
    if key == 27:
       break

cap.release()
cv2.destroyAllWindows()