Python | Detect Polygons in an Image using OpenCV

Approach : The approach we would be used to detect the shape of a given polygon will be based on classifying the detected shape on the basis of a number of sides it has. For example, if the detected polynomial has 3 sides, then it could be considered as a triangle, if the polynomial has 4 sides then it could be classified as a square or a rectangle.

Prerequisite :

Make sure you have Python3, OpenCV, numpy already installed on your computer.
Basic knowledge about OpenCV would be helpful – Basics of OpenCV
Make sure to save the image in which shapes is to be detected in your local directory

Implementation : In the following code, we will be detecting an arrow-shaped object from the image ‘arrow.jpg’. The shape will be detected on the basis of the number of sides it has

Code: Python program to detect polygons in an image

# Python code to detect an arrow (seven-sided shape) from an image. 
import numpy as np 
import cv2 
   
# Reading image 
img2 = cv2.imread('arrow.jpg', cv2.IMREAD_COLOR) 
   
# Reading same image in another variable and  
# converting to gray scale. 
img = cv2.imread('arrow.jpg', cv2.IMREAD_GRAYSCALE) 
   
# Converting image to a binary image  
# (black and white only image). 
_,threshold = cv2.threshold(img, 110, 255,  
                            cv2.THRESH_BINARY) 
   
# Detecting shapes in image by selecting region  
# with same colors or intensity. 
contours,_=cv2.findContours(threshold, cv2.RETR_TREE, 
                            cv2.CHAIN_APPROX_SIMPLE) 
   
# Searching through every region selected to  
# find the required polygon. 
for cnt in contours : 
    area = cv2.contourArea(cnt) 
   
    # Shortlisting the regions based on there area. 
    if area > 400:  
        approx = cv2.approxPolyDP(cnt,  
                                  0.009 * cv2.arcLength(cnt, True), True) 
   
        # Checking if the no. of sides of the selected region is 7. 
        if(len(approx) == 7):  
            cv2.drawContours(img2, [approx], 0, (0, 0, 255), 5) 
   
# Showing the image along with outlined arrow. 
cv2.imshow('image2', img2)  
   
# Exiting the window if 'q' is pressed on the keyboard. 
if cv2.waitKey(0) & 0xFF == ord('q'):  
    cv2.destroyAllWindows() 

Note : The parameter ‘110’ in threshold could be adjusted as per need if the object is of different colour and is based on trial and error.

Result :

Image with arrow

Binary Image

Binary Image

Outlined Arrow

My Personal Notes

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