Moving Object Detection with OpenCv & Imutils

Detecting moving objects in a video stream is a key task in many computer vision applications. Using OpenCV and Imutils, we can create a program that analyzes video frames to identify areas where there is motion. This can be useful in surveillance, tracking, and many other fields where detecting motion is important. In this article, we’ll explore how to use these libraries to create a simple motion detection program.

Let’s check out the code below for the same along with the output

you need to first create a file with .py extension and copy the below code and paste it there

import cv2 #image
import time #delay
import imutils #resize

cam = cv2.VideoCapture(0) #cam id
time.sleep(1)

firstFrame=None
area = 500

while True:
    _,img = cam.read() #read frame from camera
    text = "Normal" 
    img = imutils.resize(img, width=500) #resize

    grayImg = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #color 2 Gray scale image

    gaussianImg = cv2.GaussianBlur(grayImg, (21, 21), 0) #smoothened

    if firstFrame is None:
            firstFrame = gaussianImg #capturing 1st frame on 1st iteration
            continue

    imgDiff = cv2.absdiff(firstFrame, gaussianImg) #absolute diff b/w 1st nd current frame

    threshImg = cv2.threshold(imgDiff, 25, 255, cv2.THRESH_BINARY)[1] #binary

    threshImg = cv2.dilate(threshImg, None, iterations=2)

    cnts = cv2.findContours(threshImg.copy(), cv2.RETR_EXTERNAL,
            cv2.CHAIN_APPROX_SIMPLE)

    cnts = imutils.grab_contours(cnts)
    for c in cnts:
            if cv2.contourArea(c) < area:
                    continue
            (x, y, w, h) = cv2.boundingRect(c)
            cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
            text = "Moving Object detected"
    print(text)
    cv2.putText(img, text, (10, 20),
            cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
    cv2.imshow("cameraFeed",img)
    key = cv2.waitKey(1) & 0xFF
    if key == ord("q"):
        break

cam.release()
cv2.destroyAllWindows()

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