How to remove multiple frames when detecting live objects

Question

I've made a code to detect the dimension of an MCB by using its HSV color code. However when I run the program, I achieve the expected output however I have 3 other frames around the detected object. Though the output text data is set to one frame, i still have an issue with the 3 other pointless frames roaming around. I would like to ask any advice in how to remove them.

I set the contour data to detect the largest area of the HSV code but that still didnt work.

Ill attach a screenshot of what the code provides to get a better idea.

The output image

The code is below:

import cv2
from collections import deque
from scipy.spatial import distance as dist
from imutils import perspective
import numpy as np
import argparse
import imutils
import math
import time

font = cv2.FONT_HERSHEY_SIMPLEX

def midpoint(ptA, ptB):
    return ((ptA[0] + ptB[0]) * 0.5, (ptA[1] + ptB[1]) * 0.5)

ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="path to the (optional) video file")
args = vars(ap.parse_args())

sensitivity = 43
greyLower = np.array([96,0,176-sensitivity])
greyUpper = np.array([180,sensitivity,255])
pixelsPerMetric = None
KNOWN_WIDTH = 19

if not args.get("video", False):
    camera = cv2.VideoCapture(0)
else:
    camera = cv2.VideoCapture(args["video"])

while True:
    (grabbed, frame) = camera.read()

    if args.get("video") and not grabbed:
        break

    frame = imutils.resize(frame, width=600)
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    mask = cv2.inRange(hsv,greyLower, greyUpper)
    mask = cv2.erode(mask, None, iterations=2)
    mask = cv2.dilate(mask, None, iterations=2)

    (_, contours, hierarchy) = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    center = None
    for pic, contour in enumerate(contours):

        if len(contours) > 0:
            contour = max(contours, key =cv2.contourArea)
            x,y,w,h = cv2.boundingRect(contour)
            rect = (x+w, y+h)
            rect = cv2.minAreaRect(contour)
            box = cv2.boxPoints(rect)
            box = np.int0(box)
            box = perspective.order_points(box)
            M = cv2.moments(contour)
            for (x, y) in box:
                M = cv2.rectangle(frame,(int(x),int(y)),(int(x+w), int(y+h)),(0,0,139),2)
            # unpack the ordered bounding box, then compute the midpoint
            # between the top-left and top-right coordinates, followed by
            # the midpoint between bottom-left and bottom-right coordinates
            (tl, tr, br, bl) = box
            (tltrX, tltrY) = midpoint(tl, tr)
            (blbrX, blbrY) = midpoint(bl, br)

            # compute the midpoint between the top-left and top-right points,
            # followed by the midpoint between the top-righ and bottom-right
            (tlblX, tlblY) = midpoint(tl, bl)
            (trbrX, trbrY) = midpoint(tr, br)

            # draw the midpoints on the image
            cv2.circle(M, (int(tltrX), int(tltrY)), 5, (255, 0, 0), -1)
            cv2.circle(M, (int(blbrX), int(blbrY)), 5, (255, 0, 0), -1)
            cv2.circle(M, (int(tlblX), int(tlblY)), 5, (255, 0, 0), -1)
            cv2.circle(M, (int(trbrX), int(trbrY)), 5, (255, 0, 0), -1)

            # draw lines between the midpoints
            cv2.line(M, (int(tltrX), int(tltrY)), (int(blbrX), int(blbrY)),
                    (255, 0, 255), 2)
            cv2.line(M, (int(tlblX), int(tlblY)), (int(trbrX), int(trbrY)),
                    (255, 0, 255), 2)
            # compute the Euclidean distance between the midpoints
            dA = dist.euclidean((tltrX, tltrY), (blbrX, blbrY))
            dB = dist.euclidean((tlblX, tlblY), (trbrX, trbrY))

            # if the pixels per metric has not been initialized, then
            # compute it as the ratio of pixels to supplied metric
            # (in this case, inches)

            # compute the size of the object
            dimA = dA / KNOWN_WIDTH
            dimB = dB / KNOWN_WIDTH

            if rect >300:
                    frame = cv2.rectangle(frame,(int(x),int(y)),(int(x+w), int(y+h)),(0,0,139),2)
                    cv2.putText(frame,"MCB",(x,y),cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0,0,139))

            # draw the object sizes on the image
            cv2.putText(frame, "{:.1f}cm".format(dimA),
                    (int(tltrX - 15), int(tltrY - 10)), cv2.FONT_HERSHEY_SIMPLEX,
                    0.65, (255, 255, 255), 2)
            cv2.putText(frame, "{:.1f}cm".format(dimB),
                    (int(trbrX + 10), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX,
                    0.65, (255, 255, 255), 2)
    cv2.imshow("Frame", frame)

    key = cv2.waitKey(10) & 0xFF

    if key == ord("q"):
        break

camera.release()
cv2.destroyAllWindows()

Please any advice will be helpful and Thank you in advance, cheers!