How To Draw Contours Around Objects Using OpenCV

cover-contours-on-object-image

In this tutorial, you will learn how to draw a contour around an object.

Prerequisites

Draw a Contour Around a T-Shirt

tshirt-1

We’ll start with this t-shirt above. Save that image to some folder on your computer.


Now, in the same folder you saved that image above (we’ll call the file tshirt.jpg), open up a new Python program.

Name the program draw_contour.py.

Write the following code:

# Project: How To Draw Contours Around Objects Using OpenCV
# Author: Addison Sears-Collins
# Date created: October 7, 2020
# Reference: https://stackoverflow.com/questions/58405171/how-to-find-the-extreme-corner-point-in-image

import cv2 # OpenCV library
import numpy as np # NumPy scientific computing library

# Read the image
image = cv2.imread("tshirt.jpg")

# Convert the image to grayscale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Convert the image to black and white.
# Modify the threshold (e.g. 75 for tshirt.jpg) accordingly depending on how to output looks.
# If you have a dark item on a light background, use cv2.THRESH_BINARY_INV and consider 
# changing the lower color threshold to 115.
thresh = cv2.threshold(gray, 75, 255, cv2.THRESH_BINARY)[1]
#thresh = cv2.threshold(gray, 115, 255, cv2.THRESH_BINARY_INV)[1]

# Create a kernel (i.e. a small matrix)
kernel = np.ones((5,5),np.uint8)

# Use the kernel to perform morphological opening
thresh = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel)

# If you have a dark item on a light background, uncomment this line.
#thresh = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)

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

# Create a blank image
blank_image = np.ones((450,600,3), np.uint8)

# Set the minimum area for a contour
min_area = 5000

# Draw the contours on the original image and the blank image
for c in cnts:
    area = cv2.contourArea(c)
    if area > min_area:
        cv2.drawContours(image,, 0, (36,255,12), 2)
        cv2.drawContours(blank_image,, 0, (255,255,255), 2)

# Conver the blank image to grayscale for corner detection
gray = cv2.cvtColor(blank_image, cv2.COLOR_BGR2GRAY)

# Detect corners using the contours
corners = cv2.goodFeaturesToTrack(image=gray,maxCorners=25,qualityLevel=0.20,minDistance=50) # Determines strong corners on an image

# Draw the corners on the original image
for corner in corners:
    x,y = corner.ravel()
    cv2.circle(image,(x,y),10,(0,0,255),-1)

 # Display the image
image_copy = cv2.imread("tshirt.jpg")
cv2.imshow('original image', image_copy)
cv2.imshow('image with contours and corners', image)
cv2.imshow('blank_image with contours', blank_image)

# Save the image that has the contours and corners
cv2.imwrite('contour_tshirt.jpg', image)

# Save the image that has just the contours
cv2.imwrite('contour_tshirt_blank_image.jpg', blank_image)

# Exit OpenCV
if cv2.waitKey(0) & 0xff == 27:
    cv2.destroyAllWindows()

Run the code. Here is what you should see:

contour_tshirt_blank_image
Just the contour.
contour_tshirt
The contour with corner points.

Detecting Corners on Jeans

To detect corners on jeans, you’ll need to make the changes mentioned in the code. This is because the jeans are a dark object on a light background (in contrast to a light object on a dark background in the case of the t-shirt).

Let’s draw a contour around the pair of jeans.

Here is the input image (jeans.jpg):

jeans-1

Change the fileName variable in your code so that it is assigned the name of the image (‘jeans.jpg’).

Here is the output image:

contour_jeans_blank_image
contour_jeans

That’s it. Keep building!