My first realtime object detection using OpenCV

openCv.py

import cv2
import numpy as np

def detect_boxes(image):
    # Convert image to HSV color space
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)

    # Define range for brown color in HSV
    lower_brown = np.array([10, 50, 50])
    upper_brown = np.array([20, 255, 255])
    mask = cv2.inRange(hsv, lower_brown, upper_brown)

    # Morphological operations to clean the mask
    kernel = np.ones((5, 5), np.uint8)
    mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
    
    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    for contour in contours:
        epsilon = 0.02 * cv2.arcLength(contour, True)
        approx = cv2.approxPolyDP(contour, epsilon, True)

        if len(approx) == 4 and cv2.contourArea(contour) > 500:
            cv2.drawContours(image, [approx], -1, (0, 255, 0), 2)
            cv2.putText(image, "Box", (approx[0][0][0], approx[0][0][1]-10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)

    return image

cap = cv2.VideoCapture(2)

while True:
    ret, frame = cap.read()
    if not ret:
        break

    result = detect_boxes(frame)
    cv2.imshow("Box Detection", result)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()