# How to find extreme outer points in an image with Python OpenCV

## Issue

I have this image of a statue.

I’m trying to find the top, bottom, left, and right most points on the statue. Is there a way to measure the edge of each side to determine the outer most point on the statue? I want to get the `(x,y)` coordinate of each side. I have tried to use `cv2.findContours()` and `cv2.drawContours()` to get an outline of the statue.

``````import cv2

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

contours = cv2.findContours(gray, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)[0]
cv2.drawContours(img, contours, -1, (0, 200, 0), 3)

cv2.imshow('img', img)
cv2.waitKey()
``````

## Solution

Here’s a potential approach:

After converting to grayscale and blurring image, we threshold to get a binary image

Now we find contours using `cv2.findContours()`. Since OpenCV uses Numpy arrays to encode images, a contour is simply a Numpy array of `(x,y)` coordinates. We can slice the Numpy array and use `argmin()` or `argmax()` to determine the outer left, right, top, and bottom coordinates like this

``````left = tuple(c[c[:, :, 0].argmin()][0])
right = tuple(c[c[:, :, 0].argmax()][0])
top = tuple(c[c[:, :, 1].argmin()][0])
bottom = tuple(c[c[:, :, 1].argmax()][0])
``````

Here’s the result

left: (162, 527)

right: (463, 467)

top: (250, 8)

bottom: (381, 580)

``````import cv2
import numpy as np

# Load image, grayscale, Gaussian blur, threshold
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (3,3), 0)
thresh = cv2.threshold(blur, 220, 255, cv2.THRESH_BINARY_INV)[1]

# Find contours
cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
c = max(cnts, key=cv2.contourArea)

# Obtain outer coordinates
left = tuple(c[c[:, :, 0].argmin()][0])
right = tuple(c[c[:, :, 0].argmax()][0])
top = tuple(c[c[:, :, 1].argmin()][0])
bottom = tuple(c[c[:, :, 1].argmax()][0])

# Draw dots onto image
cv2.drawContours(image, [c], -1, (36, 255, 12), 2)
cv2.circle(image, left, 8, (0, 50, 255), -1)
cv2.circle(image, right, 8, (0, 255, 255), -1)
cv2.circle(image, top, 8, (255, 50, 0), -1)
cv2.circle(image, bottom, 8, (255, 255, 0), -1)

print('left: {}'.format(left))
print('right: {}'.format(right))
print('top: {}'.format(top))
print('bottom: {}'.format(bottom))
cv2.imshow('thresh', thresh)
cv2.imshow('image', image)
cv2.waitKey()
``````