Hey Everyone, so I've been working on my senior project and it's meant to write out the video recorded from a webcam connected to a raspberry pi and function as a motion detector. I'm having trouble getting OpenCV to write out the next motion once the initial motion is made. Currently it continues to write the second instance of motion to the same file as the first. Can anyone provide examples of how to fix this issue or provide assistance with the code below? Thanks in advance
import cv2, time, pandas, json, argparse, imutils,dropbox,functools, operator,os ,subprocess
from datetime import datetime
import datetime
from picamera.array import PiRGBArray
from picamera import PiCamera
from subprocess import Popen, PIPE
#Argument to set the min area of motion detection
#To start python ProgramName.py -a Area
ap = argparse.ArgumentParser()
ap.add_argument("-a", "--min-area" , type= int, default=500, help="min area size")
args = vars(ap.parse_args())
stillFrameCounter=0
camera = cv2.VideoCapture(-1)
background = None
motion = [None, None]
time = []
rw = PiRGBArray(camera, size=tuple([649, 480]))
fourcc = cv2.VideoWriter_fourcc(* 'DIVX')
name = str(datetime.datetime.now()) + '.avi'
at=dropbox.Dropbox('xxxxxxx')
uprev = datetime.datetime.now()
capper = cv2.VideoWriter(name, fourcc, 20.0, (640,480))
dboxup = "/home/pi/Desktop/dropbox_uploader.sh upload "
vup = "/home/pi/Desktop/tempvid/sample.text /" + name
while True:
print "Running: top of loop."
check, frame = camera.read()
motion = 0
text = "Streaming"
tw = datetime.datetime.now()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (21,21), 0 )
if background is None:
background = gray.copy()
b = gray.copy().astype("float")
rw.truncate(0)
continue
difference = cv2.absdiff(background,gray)
cv2.accumulateWeighted(gray, b, 0.5)
df = cv2.absdiff(gray, cv2.convertScaleAbs(b))
tf = cv2.threshold(difference, 30, 255, cv2.THRESH_BINARY)[1]
tf = cv2.dilate(tf, None, iterations = 2)
cnts = cv2.findContours(tf.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)
motionDetected = False
for c in cnts:
if cv2.contourArea(c) < 5000:
continue
# motion+=1
(x, y, w, h) = cv2.boundingRect(c)
cv2.rectangle(frame, (x,y) , (x+w, y+h), (255, 0, 0), 2)
motionDetected = True
text="Motion"
print "Motion Detected."
stillFrameCounter=0
ts = tw.strftime("%A %d %B %Y %I :%M:%S%p")
cv2.putText(frame, "Status: {} ".format(text), (10,20), cv2.FONT_HERSHEY_PLAIN, 0.5, (0,0, 255) ,2)
if motionDetected:
ret = False
if(tw - uprev).seconds >= 3:
ret,frame2 = camera.read()
if ret:
capper.write(frame2)
else:
stillFrameCounter = stillFrameCounter + 1
if(stillFrameCounter > 500):
print "Releasing capper."
capper.release()
capper = cv2.VideoWriter(name, fourcc, 20.0, (640,480))
cv2.imshow("Camera Stream", frame)
cv2.waitKey(1)
print motion
camera.release()
capper.release()
cv2.destroyAllWindows()
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