How to Detect An Object With OpenCV (Python)

OpenCV is the massive open source 

 library for computer vision, machine learning, and image processing. Now it plays an important role in real time operations which is very important in the current system. By using 

, images and video identification objects can be processed. faces or even the handwriting of a human. This article focuses on object detection.

Source code:

import cv2

video_object = cv2.VideoCapture(0)

while True:

    check, live_frame =video_object.read()

    is_motion_detected = 0

    gray = cv2.cvtColor(live_frame, cv2.COLOR_BGR2GRAY)

    gray = cv2.GaussianBlur(gray, (21,21),0)

    if intial_static_video_frame is None:

        intial_static_video_frame = gray

        continue

    difference_frame = cv2.absdiff(intial_static_video_frame, gray)

    threshold_frame = cv2.threshold(difference_frame, 30,255, cv2.THRESH_BINARY)[1]

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

    cnts, hierarchy =cv2.findContours(threshold_frame, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)

    for contour in cnts:

        if cv2.contourArea(contour):

            continue

        is_motion_detected = 1

        (x,y,w,h) = cv2.boundingRect(contour)

        cv2.rectangle(live_frame, (x,y), (x + w, y + h), (0, 255, 255), 3)

    cv2.imshow("Gray frame", gray)

    cv2.imshow("Difference frame", difference_frame)

    cv2.imshow("Threshold frame", threshold_frame)

    cv2.imshow("Color frame", live_frame)

    key =cv2.waitKey(1)

    if key == ord('q'):

        break

    video_object.release()

    cv2.destroyAllWindows()