```

import cv2

import numpy as np

# load image

img = cv2.imread('path/to/image')

# convert to grayscale

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

# apply thresholding

thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

# find contours and get minimum area

contours = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

min_area = 10000000 # arbitrary value to filter out small contours

for c in contours:

area = cv2.contourArea(c)

if area < min_area:

break

# draw contour with color

color = (0, 255, 0)

cv2.drawContour(img, [c], -1, color)

# show image and contour

cv2.imshow('Image', img)

cv2.circle(img, (int(c[1][0]), int(c[1][1])), 10, (0, 255, 0), -1)

cv2.waitKey(0)

cv2.destroyAllWindows()

```

You can adjust the `min_area` value to filter out smaller or larger contours as needed.