motion_detection.py

import cv2 
import numpy as np

def motion_detector():
    frame_count = 0
    previous_frame = None
    prepared_frame = None

    # Use '0' for the default camera (usually built-in webcam). 
    # If you have an external camera, you may need to change the index.
    cap = cv2.VideoCapture(0)  

    while True:
        frame_count += 1

        # 1. Capture frame from camera
        ret, frame = cap.read()

        if not ret:
            print("Error: Unable to capture frame")
            break

        if ((frame_count % 2) == 0):
            # 2. Prepare image; grayscale and blur
            prepared_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
            prepared_frame = cv2.GaussianBlur(src=prepared_frame, ksize=(5, 5), sigmaX=0)

        if (previous_frame is None):
            previous_frame = prepared_frame
            continue

        # Calculate difference and update previous frame
        diff_frame = cv2.absdiff(src1=previous_frame, src2=prepared_frame)
        previous_frame = prepared_frame

        # 4. Dilute the image a bit to make differences more seeable; more suitable for contour detection
        kernel = np.ones((5, 5))
        diff_frame = cv2.dilate(diff_frame, kernel, 1)

        # 5. Only take different areas that are different enough (>20 / 255)
        thresh_frame = cv2.threshold(src=diff_frame, thresh=20, maxval=255, type=cv2.THRESH_BINARY)[1]

        contours, _ = cv2.findContours(image=thresh_frame, mode=cv2.RETR_EXTERNAL, method=cv2.CHAIN_APPROX_SIMPLE)
        cv2.drawContours(image=frame, contours=contours, contourIdx=-1, color=(0, 255, 0), thickness=2, lineType=cv2.LINE_AA)

        contours, _ = cv2.findContours(image=thresh_frame, mode=cv2.RETR_EXTERNAL, method=cv2.CHAIN_APPROX_SIMPLE)
        for contour in contours:
            if cv2.contourArea(contour) < 50:
                # too small: skip!
                continue
            (x, y, w, h) = cv2.boundingRect(contour)
            cv2.rectangle(img=frame, pt1=(x, y), pt2=(x + w, y + h), color=(0, 255, 0), thickness=2)

        cv2.imshow('Motion detector', frame)

        if (cv2.waitKey(30) == 27):
            break

    # Release the camera and close the window
    cap.release()
    cv2.destroyAllWindows()

motion_detector()