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The code above wasn't buiding with Python3. Just in case if this is useful, see the code below with minor corrections.

import cv2 as cv import numpy as np

im = cv.imread("plank.jpg") gray = cv.cvtColor(im, cv.COLOR_BGR2GRAY) gray = cv.GaussianBlur(gray, (5, 5), 0) _, bin = cv.threshold(gray,120,255,1) # inverted threshold (light obj on dark bg) bin = cv.dilate(bin, None) # fill some holes bin = cv.dilate(bin, None) bin = cv.erode(bin, None) # dilate made our shape larger, revert that bin = cv.erode(bin, None) contours, hierarchy = cv.findContours(bin, cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)

rc = cv.minAreaRect(contours[0]) box = cv.boxPoints(rc) for p in box: pt = (p[0],p[1]) print(pt) cv.circle(im,pt,5,(200,0,0),2) cv.imshow("plank", im) cv.waitKey()

The code above wasn't buiding with Python3. Just in case if this is useful, see the code below with minor corrections.

import cv2 as cv
import numpy as np
np
  
im = cv.imread("plank.jpg")
gray = cv.cvtColor(im, cv.COLOR_BGR2GRAY)
gray = cv.GaussianBlur(gray, (5, 5), 0)
_, bin = cv.threshold(gray,120,255,1) # inverted threshold (light obj on dark bg)
bin = cv.dilate(bin, None) # fill some holes
bin = cv.dilate(bin, None)
bin = cv.erode(bin, None) # dilate made our shape larger, revert that
bin = cv.erode(bin, None)
contours, hierarchy = cv.findContours(bin, cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)cv.CHAIN_APPROX_SIMPLE)
  
rc = cv.minAreaRect(contours[0])
box = cv.boxPoints(rc)
for p in box:
pt = (p[0],p[1])
print(pt)
cv.circle(im,pt,5,(200,0,0),2)
cv.imshow("plank", im)
cv.waitKey()cv.waitKey()