Motion Detection OpenCV Python With Source Code

Motion Detection OpenCV Python With Source Code

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Motion Detection OpenCV Python With Source Code

The Motion Detection OpenCV Python was developed using Python OpenCV , This Project is used in CCTV Cameras to detect any kind of motion in the video frame.

In this blog, we are going to make a motion detection script using OpenCV in Python.

A Motion Detection OpenCV Python Algorithm Capture Video, in which you have to detect movement using OpenCV in Python.

In many applications based on machine vision, motion detection is used.

For example, when we want to count the people who pass by a certain place.

In all these cases, the first thing we have to do is extract the people that are at the scene.

What is OpenCV?

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library.

OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products.

In this Python OpenCV Project also includes a downloadable Python Project With Source Code for free, just find the downloadable source code below and click to start downloading.

By the way if you are new to python programming and you don’t know what would be the Python IDE to use, I have here a list of Best Python IDE for Windows, Linux, Mac OS that will suit for you.

I also have here How to Download and Install Latest Version of Python on Windows.

To start executing Motion Detection OpenCV Python With Source Code, make sure that you have installed Python 3.9 and PyCharm in your computer.

Motion Detection OpenCV Python With Source Code: Steps on how to run the project

Time needed: 5 minutes

These are the steps on how to run Motion Detection OpenCV Python With Source Code

  1. Step 1: Download the given source code below.

    First, download the given source code below and unzip the source code.
    Motion Detection OpenCV download source code

  2. Step 2: Import the project to your PyCharm IDE.

    Next, import the source code you’ve download to your PyCharm IDE.
    Motion Detection OpenCV open project

  3. Step 3: Run the project.

    last, run the project with the command “py main.py”
    Motion Detection OpenCV run project

Installed Libraries

import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt

Complete Source Code

import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt


def motionDetection():
    cap = cv.VideoCapture("./img/vtest.avi")
    ret, frame1 = cap.read()
    ret, frame2 = cap.read()

    while cap.isOpened():
        diff = cv.absdiff(frame1, frame2)
        diff_gray = cv.cvtColor(diff, cv.COLOR_BGR2GRAY)
        blur = cv.GaussianBlur(diff_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) < 900:
                continue
            cv.rectangle(frame1, (x, y), (x+w, y+h), (0, 255, 0), 2)
            cv.putText(frame1, "Status: {}".format('Movement'), (10, 20), cv.FONT_HERSHEY_SIMPLEX,
                       1, (255, 0, 0), 3)

        # cv.drawContours(frame1, contours, -1, (0, 255, 0), 2)

        cv.imshow("Video", frame1)
        frame1 = frame2
        ret, frame2 = cap.read()

        if cv.waitKey(50) == 27:
            break

    cap.release()
    cv.destroyAllWindows()


if __name__ == "__main__":
    motionDetection()

Output

motion detection opencv python output
motion detection opencv python output

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Download Source Code below

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Summary

In many applications based on machine vision, motion detection is used.

For example, when we want to count the people who pass by a certain place or how many cars have passed through a toll.

In all these cases, the first thing we have to do is extract the people or vehicles that are at the scene.

There are different techniques, methods, or algorithms that enable motion detection.

As in other subjects, there are no generic cases in artificial vision.

It will depend on each situation to use one or the other. Let us have a look at some methods used in OpenCV and Computer Vision.

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Inquiries

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