对象检测使用Raspberry Pi和Android IP摄像头与Python和OpenCV

Question

这是我使用树莓派和安卓Ip相机进行物体检测的代码。这里我没有得到任何输出，代码也没有提供任何错误。有人能找出错误是什么吗

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, CoorYEntranceLine, 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

这是我用来显示物体检测和物体计数的行和帧的代码部分

#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,CoorYEntranceLine), (255, 0, 0), 2)
cv2.line(Frame, (0,CoorYExitLine), (width,CoorYExitLine), (0, 0, 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), (0, 255, 0), 2)
#find object's centroid
CoordXCentroid = (x+x+w)/2
CoordYCentroid = (y+y+h)/2
ObjectCentroid = (CoordXCentroid,CoordYCentroid)
cv2.circle(Frame, ObjectCentroid, 1, (0, 0, 0), 5)

if (CheckEntranceLineCrossing(CoordYCentroid,CoorYEntranceLine,CoorYExitLine)):
EntranceCounter += 1
if (CheckExitLineCrossing(CoordYCentroid,CoorYEntranceLine,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, 0, 1), 2)
cv2.putText(Frame, "Exits: {}".format(str(ExitCounter)), (10, 70),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)



cv2.imshow('Salida',Frame)
cv2.waitKey(1);
# When everything done, release the capture 
cap.release()
cv2.destroyAllWindows()

Answer 1

正确的代码

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, CoorYEntranceLine, CoorYExitLine):
AbsDistance = abs(y - CoorYExitLine)    
if ((AbsDistance <= 2) and (y > CoorYEntranceLine)):
return 1
else:
return 0

#cv2.namedWindow("Tracking")
cv2.createTrackbar("LH", "Tracking", 0, 255, nothing)
cv2.createTrackbar("LS", "Tracking", 0, 255, nothing)
cv2.createTrackbar("LV", "Tracking", 0, 255, nothing)
cv2.createTrackbar("UH", "Tracking", 255, 255, nothing)
cv2.createTrackbar("US", "Tracking", 255, 255, nothing)
cv2.createTrackbar("UV", "Tracking", 255, 255, 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, 255, 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), (2000,170), (255, 0, 0), 5)
cv2.line(frame, (0,470), (2000,470), (0, 0, 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), (0, 255, 0), 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, (0, 255, 0), 5)
if (CheckEntranceLineCrossing(CoordYCentroid,170,470)):
EntranceCounter += 1
if (CheckExitLineCrossing(CoordYCentroid,170,470)):  
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, 2, (250, 0, 1), 2)
cv2.putText(frame, "Exits: {}".format(str(ExitCounter)), (10, 110),
cv2.FONT_HERSHEY_SIMPLEX, 2, (0, 0, 255), 2)

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