We Keep Coding

How to multithreading without causing app freeze or lag?

Hey I started learning python not so long time ago. Right now Im creating (or more likely trying to) face and motion detection script based on OpenCV library. Unfortunately Im stuck since few days cause I cant solve problem with I guess its called multi threading.
Here is my code:
import time
import cv2
import datetime
from discord_webhook import DiscordWebhook
import threading
faceCascade = cv2.CascadeClassifier("face_recognition.xml")
# define a video capture object
video_capture = cv2.VideoCapture(0)
#writing video
frame_width = int(video_capture.get(3))
frame_height = int(video_capture.get(4))
# Define the codec and create VideoWriter object.The output is stored in 'outpy.avi' file.
out = cv2.VideoWriter(datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p") + '.avi',cv2.VideoWriter_fourcc('M','J','P','G'), 10, (frame_width,frame_height))
#screenshot when detectors get triggered
def screenshot():
cv2.imwrite('screenshot.png',video_capture.read()[1])
#webhook notify
def alert():
webhook = DiscordWebhook(url="", rate_limit_retry=True,
content='!ALERT!')
webhook.execute()
while(True):
# Capture the video frame by frame
ret, frame = video_capture.read()
text="not detected"
text1="not detected"
timestamp = datetime.datetime.now()
#face recognition
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5,minSize=(30, 30))
if int(format(len(faces))) > 0:
#print("Found {0} faces!".format(len(faces)))
text="detected"
else:
text="not detected"
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
#motion detection
ret, frame1 = video_capture.read()
difference = cv2.absdiff(frame, frame1) # find the difference between the frames
gray = cv2.cvtColor(difference, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (5, 5), 0)
_, thresh = cv2.threshold(blur, 20, 255, cv2.THRESH_BINARY) # create threshold
dilated = cv2.dilate(thresh, None, iterations=3)
contours, _ = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for c in contours:
if cv2.contourArea(c) < 5000:
continue
x, y, w, h = cv2.boundingRect(c)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
text1="detected"
# Display the resulting frame
ts = timestamp.strftime("%A %d %B %Y %I:%M:%S%p")
cv2.putText(frame, "Face status: {}".format(text), (10, 25), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
cv2.putText(frame, "Motion status: {}".format(text1), (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
cv2.putText(frame, ts, (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.55, (0, 0, 255), 1)
#check if motion is detected if not change status text
if text1 == "not detected":
text1="detected"
else:
text1="not detected"
out.write(frame)
cv2.imshow('Press Q to quit', frame)
# the 'q' button is set as the
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# After the loop release the cap object
video_capture.release()
out.release()
cv2.destroyAllWindows()
Im trying to send webhook and make screen shot every 3 minutes if motion is detected but for loops completely lags this app. Tried time.sleep or thread timers but it only freezes or lags app. If someone can explain me how to solve this problem I will be very thankful. Have a great day or night

Save both input video and output video in Open CV python

i write a code from Open CV Document about Motion Detection .i want to save my input as a video and my output as a video but i have problems. i save video but i can just save the output video and some time the input video is the same out put video.my input video is from my computer's camera and it's like a normal video but the output is that video in addition by squares around motion objects.i need your help.
import cv2 as cv
import numpy as np
cap = cv.VideoCapture(0)
(grabbed, frame) = cap.read()
fshape = frame.shape
fheight = fshape[0]
fwidth = fshape[1]
print (fwidth , fheight)
ret, frame1 = cap.read()
ret, frame2 = cap.read()
while cap.isOpened():
diff = cv.absdiff(frame1, frame2)
gray = cv.cvtColor(diff, cv.COLOR_BGR2GRAY)
blur = cv.GaussianBlur(gray, (5, 5), 0)
_, thresh = cv.threshold(blur, 20, 255, cv.THRESH_BINARY)
dilated = cv.dilate(thresh, None, iterations=3)
contours, _ = cv.findContours(dilated, cv.RETR_TREE,
cv.CHAIN_APPROX_SIMPLE)
for contour in contours:
(x, y, w, h) = cv.boundingRect(contour)
if cv.contourArea(contour) < 100:
continue
cv.rectangle(frame1, (x, y), (x+w, y+h), (0, 0, 255), 3)
Final_Movie = cv.putText(frame1, "Status: {}".format('Movement'), (10,
20), cv.FONT_HERSHEY_DUPLEX,
1, (0, 0, 255), 3)
#cv.drawContours(frame1, contours, -1, (0, 0, 255), 3)
cv.imshow("feed", frame1)
cv.imshow("feed1", blur)
cv.imshow("feed2", gray)
cv.imshow("feed3", diff)
cv.imshow("feed4", thresh)
cv.imshow("feed5", dilated)
#cv.imshow("feed6", contours)
frame1 = frame2
ret, frame2 = cap.read()
if cv.waitKey(40) == 27:
break
cv.destroyAllWindows()
cap.release()
i tried this but it doesn't work.
import cv2 as cv
import numpy as np
cap = cv.VideoCapture(0)
(grabbed, frame) = cap.read()
fshape = frame.shape
fheight = fshape[0]
fwidth = fshape[1]
print (fwidth , fheight)
fourcc = cv.VideoWriter_fourcc(*'XVID')
out = cv.VideoWriter('output.avi', fourcc, 20.0, (fwidth, fheight))
out1 = cv.VideoWriter('input.avi', fourcc, 20.0, (fwidth, fheight))
ret, frame1 = cap.read()
ret, frame2 = cap.read()
while cap.isOpened():
diff = cv.absdiff(frame1, frame2)
gray = cv.cvtColor(diff, cv.COLOR_BGR2GRAY)
blur = cv.GaussianBlur(gray, (5, 5), 0)
_, thresh = cv.threshold(blur, 20, 255, cv.THRESH_BINARY)
dilated = cv.dilate(thresh, None, iterations=3)
contours, _ = cv.findContours(dilated, cv.RETR_TREE,
cv.CHAIN_APPROX_SIMPLE)
for contour in contours:
(x, y, w, h) = cv.boundingRect(contour)
if cv.contourArea(contour) < 100:
continue
cv.rectangle(frame1, (x, y), (x+w, y+h), (0, 0, 255), 3)
Final_Movie = cv.putText(frame1, "Status: {}".format('Movement'), (10,
20), cv.FONT_HERSHEY_DUPLEX,
1, (0, 0, 255), 3)
#cv.drawContours(frame1, contours, -1, (0, 0, 255), 3)
cv.imshow("feed", frame1)
cv.imshow("feed1", blur)
cv.imshow("feed2", gray)
cv.imshow("feed3", diff)
cv.imshow("feed4", thresh)
cv.imshow("feed5", dilated)
#cv.imshow("feed6", contours)
if ret == True:
out.write(Final_Movie)
out.write(frame2)
frame1 = frame2
ret, frame2 = cap.read()
if cv.waitKey(40) == 27:
break
cv.destroyAllWindows()
cap.release()

I am unable to download cv2, for whatever reason it does not work

from collections import deque
from imutils.video import VideoStream
import numpy as np
import argparse
import cv2
import imutils
import time
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video",
help="Users/ejr/Desktop/curry.mp4")
ap.add_argument("-b", "--buffer", type=int, default=64,
help="max buffer size")
args = vars(ap.parse_args())
greenLower = (29, 86, 6)
greenUpper = (64, 255, 255)
pts = deque(maxlen=args["buffer"])
if not args.get("video", False):
vs = VideoStream(src=0).start()
else:
vs = cv2.VideoCapture(args["video"])
time.sleep(2.0)
while True:
frame = vs.read()
frame = frame[1] if args.get("video", False) else frame
if frame is None:
break
frame = imutils.resize(frame, width=600)
blurred = cv2.GaussianBlur(frame, (11, 11), 0)
hsv = cv2.cvtColor(blurred, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv, greenLower, greenUpper)
mask = cv2.erode(mask, None, iterations=2)
mask = cv2.dilate(mask, None, iterations=2)
cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)
center = None
if len(cnts) > 0:
c = max(cnts, key=cv2.contourArea)
((x, y), radius) = cv2.minEnclosingCircle(c)
M = cv2.moments(c)
center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))
if radius > 10:
cv2.circle(frame, (int(x), int(y)), int(radius),
(0, 255, 255), 2)
cv2.circle(frame, center, 5, (0, 0, 255), -1)
pts.appendleft(center)
for i in range(1, len(pts)):
if pts[i - 1] is None or pts[i] is None:
continue
thickness = int(np.sqrt(args["buffer"] / float(i + 1)) * 2.5)
cv2.line(frame, pts[i - 1], pts[i], (0, 0, 255), thickness)
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
if key == ord("q"):
break
if not args.get("video", False):
vs.stop()
else:
vs.release()
cv2.destroyAllWindows()
This is my code, I have no idea why I keep getting the cv2 there is no module error when I try to pip install it. (I am on a Mac, Python 3.7.4). I am wondering what is the import error here, has the version changed, do I need to use Python 2, or is there like a newer cv that I should use

Try:
pip install opencv-python
or
pip3.7 install opencv-python
I think you are running pip install cv2, which it does not exists since the project of cv2 is: https://pypi.org/project/opencv-python/

How to put bounding box around the detected human outline

Here is the python code I have written :-
import cv2
import argparse
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video",
help = "path to the (optional) video file")
args = vars(ap.parse_args())
if not args.get("video", False):
cap = cv2.VideoCapture(0)
else:
cap = cv2.VideoCapture(args["video"])
fgbg = cv2.bgsegm.createBackgroundSubtractorMOG()
while True:
ret, frame = cap.read()
fgmask = fgbg.apply(frame)
cv2.imshow('frame',fgmask)
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()
How to put bounding box around the detected human outline and improve efficiency of the python code to perform background subtraction on the live video feed taken from webcam. Can someone help?

Drawing Contour Using Background Subtraction
import cv2
import argparse
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video",
help = "path to the (optional) video file")
args = vars(ap.parse_args())
if not args.get("video", False):
cap = cv2.VideoCapture(0)
else:
cap = cv2.VideoCapture(args["video"])
fgbg = cv2.bgsegm.createBackgroundSubtractorMOG()
while True:
ret, frame = cap.read()
fgmask = fgbg.apply(frame)
gray=cv2.cvtColor(fgmask,cv2.COLOR_BGR2GRAY)
ret,th1 = cv2.threshold(gray,25,255,cv2.THRESH_BINARY)
_,contours,hierarchy = cv2.findContours(th1,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
area = cv2.contourArea(cnt)
if area > 1000 and area < 40000:
x,y,w,h = cv2.boundingRect(cnt)
cv2.rectangle(fgmask,(x,y),(x+w,y+h),(255,0,0),2)
cv2.imshow('frame',fgmask)
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()
Drawing Contour using HSV Masking and Convex Hull
Set value for hsv mask.
import cv2
import argparse
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video",
help = "path to the (optional) video file")
args = vars(ap.parse_args())
if not args.get("video", False):
cap = cv2.VideoCapture(0)
else:
cap = cv2.VideoCapture(args["video"])
fgbg = cv2.bgsegm.createBackgroundSubtractorMOG()
while True:
ret, frame = cap.read()
frame = cv2.imread(frame)
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
lower = np.array([50,103,40])
upper = np.array([255,255, 255])
mask = cv2.inRange(hsv, lower, upper)
fg = cv2.bitwise_and(frame, frame, mask=255-mask)
fg = cv2.cvtColor(fg.copy(),cv2.COLOR_HSV2BGR)
fg = cv2.cvtColor(fg,cv2.COLOR_BGR2GRAY)
fg = cv2.threshold(fg, 120,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)[1]
#plt.imshow(fg)
#plt.show()
fgclosing = cv2.morphologyEx(fg.copy(), cv2.MORPH_CLOSE, kernel)
se = np.ones((3,3),np.uint8)
#fgdilated = cv2.morphologyEx(fgclosing, cv2.MORPH_CLOSE,cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (4,4)))
fgdilated = cv2.dilate(fgclosing, kernel = se , iterations = 8)
img = frame.copy()
ret, threshed_img = cv2.threshold(fgdilated,
127, 255, cv2.THRESH_BINARY)
image, contours, hier = cv2.findContours(threshed_img,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
for cnt in contours:
#print(cv2.contourArea(cnt))
if cv2.contourArea(cnt) > 44000:
# get convex hull
hull = cv2.convexHull(cnt)
#cv2.drawContours(img, [hull], -1, (0, 0, 255), 1)
#print(hull)
(x,y,w,h) = cv2.boundingRect(cnt)
#cv2.rectangle(img, (x,y), (x+w,y+h), (255, 0, 0), 2)
contours = hull
#c1 = max(contours, key=cv2.contourArea)
hull = cv2.convexHull(cnt)
c = hull
#print(c)
cv2.drawContours(img, [hull], -1, (0, 0, 255), 1)
# determine the most extreme points along the contour
extLeft = tuple(c[c[:, :, 0].argmin()][0])
extRight = tuple(c[c[:, :, 0].argmax()][0])
extTop = tuple(c[c[:, :, 1].argmin()][0])
extBot = tuple(c[c[:, :, 1].argmax()][0])
cv2.drawContours(img, [c], -1, (0, 255, 255), 2)
cv2.circle(img, extLeft, 8, (0, 0, 255), -1)
cv2.circle(img, extRight, 8, (0, 255, 0), -1)
cv2.circle(img, extTop, 8, (255, 0, 0), -1)
cv2.circle(img, extBot, 8, (255, 255, 0), -1)
lx = extLeft[1]
ly = extLeft[0]
rx = extRight[1]
ry = extRight[0]
tx = extTop[1]
ty = extTop[0]
bx = extBot[1]
by = extBot[0]
x,y = lx,by
w,h = abs(rx-lx),abs(ty-by)
#cv2.rectangle(img, (x,y), (x+w,y+h), (255, 0, 0), 2)
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img,str(extLeft[0])+','+str(extLeft[1]),(extLeft), font, 2,(0, 0, 255),2,cv2.LINE_AA)
cv2.putText(img,str(extRight[0])+','+str(extRight[1]),(extRight), font, 2,(0, 255, 0),2,cv2.LINE_AA)
cv2.putText(img,str(extTop[0])+','+str(extTop[1]),(extTop), font, 2,(255, 0, 0),2,cv2.LINE_AA)
cv2.putText(img,str(extBot[0])+','+str(extBot[1]),(extBot), font, 2,(255, 255, 0),2,cv2.LINE_AA)
im = frame[tx:bx,ly:ry,:]
cx = im.shape[1]//2
cy = im.shape[0]//2
cv2.circle(im, (cx,cy), 15, (0, 255, 0))
plt.imshow(img)
plt.show()

You can use findContours.
import cv2
import argparse
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video",
help = "path to the (optional) video file")
args = vars(ap.parse_args())
if not args.get("video", False):
cap = cv2.VideoCapture(0)
else:
cap = cv2.VideoCapture(args["video"])
fgbg = cv2.bgsegm.createBackgroundSubtractorMOG()
while True:
ret, frame = cap.read()
fgmask = fgbg.apply(frame)
mask = 255 - fgmask
_, contours, _ = cv2.findContours(
mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
fgmask = cv2.cvtColor(fgmask, cv2.COLOR_GRAY2BGR)
for contour in contours:
area = cv2.contourArea(contour)
#only show contours that match area criterea
if area > 500 and area < 20000:
rect = cv2.boundingRect(contour)
x, y, w, h = rect
cv2.rectangle(fgmask, (x, y), (x+w, y+h), (0, 255, 0), 3)
cv2.imshow('frame',fgmask)
k = cv2.waitKey(30) & 0xff
if k == 27:
break
cap.release()
cv2.destroyAllWindows()
I have tested with the video https://github.com/opencv/opencv/blob/master/samples/data/vtest.avi

(Edited) BackgroundSubtractionMOG2 + Mean-Shift Tracking?

I am doing a project where its a motion based detection program.
However it detects changes in the background as "motion" so i'd like a way to recapture a new first frame every few minutes to replace the current one to fix this issue.
I am using a Raspberry Pi 2B and a Logitech Webcam.
The code i am using is based of : Pyimagesearch
This is my version of the code.
Please help me
(Edit)I have changed my code to a BackgroundSubtractionMOG2 now my issue is how do i add Mean-Shift Tracking so that it'll recognize its the same object that entered the screen in the frame earlier?
import sys
sys.path.append('/usr/local/lib/python3.4/site-packages')
import numpy as np
import cv2
import imutils
from imutils import contours
import datetime
import time
#cap = cv2.VideoCapture("/home/pi/Desktop/Proj/VideoTestSample.mp4")
cap = cv2.VideoCapture(0)
fgbg = cv2.createBackgroundSubtractorMOG2()
while (cap.isOpened()):
(grabbed, frame) = cap.read()
text = " "
if not grabbed:
break
frame = imutils.resize(frame, width=500)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.medianBlur(gray, 5)
fgmask = fgbg.apply(gray)
thresh = cv2.erode(fgmask, None, iterations=2)
(_,cnts,hierarchy) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for (i,c) in enumerate(cnts):
if cv2.contourArea(c) < 300:
continue
(x, y, w, h) = cv2.boundingRect(c)
cv2.rectangle(frame, (x,y), (x+w,y+h), (0,255,0), 2)
cv2.putText(frame, "#{}".format(i + 1), (x, y - 15),
cv2.FONT_HERSHEY_SIMPLEX, 0.45, (0, 0, 255), 2)
text = "REC"
cv2.putText(frame, "{}". format(text), (10,20),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
cv2.putText(frame, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p"),
(10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35,(0,0,255), 1)
cv2.imshow('frame',frame)
cv2.imshow('gray', gray)
cv2.imshow('fgmask', fgmask)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()