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Draw a rectangular shape and extract objects using Python’s OpenCV

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OpenCV is an open-source computer vision and machine learning software library. Various image processing operations such as manipulating images and applying tons of filters can be done with the help of it. It is broadly used in Object detection, Face Detection, and other Image processing tasks.

Let’s see how to draw rectangular shape on image and extract the objects using OpenCV.

# Python program to extract rectangular
# Shape using OpenCV in Python3
import cv2
import numpy as np
drawing = False     # true if mouse is pressed
mode = True         # if True, draw rectangle.
ix, iy = -1, -1
# mouse callback function
def draw_circle(event, x, y, flags, param):
    global ix, iy, drawing, mode
    if event == cv2.EVENT_LBUTTONDOWN:
        drawing = True
        ix, iy = x, y
    elif event == cv2.EVENT_MOUSEMOVE:
        if drawing == True:
            if mode == True:
                cv2.rectangle(img, (ix, iy), (x, y), (0, 255, 0), 3)
                a = x
                b = y
                if a != x | b != y:
                    cv2.rectangle(img, (ix, iy), (x, y), (0, 0, 0), -1)
      , (x, y), 5, (0, 0, 255), -1)
    elif event == cv2.EVENT_LBUTTONUP:
        drawing = False
        if mode == True:
            cv2.rectangle(img, (ix, iy), (x, y), (0, 255, 0), 2)
  , (x, y), 5, (0, 0, 255), -1)
img = np.zeros((512, 512, 3), np.uint8)
cv2.setMouseCallback('image', draw_circle)
    cv2.imshow('image', img)
    k = cv2.waitKey(1) & 0xFF
    if k == ord('m'):
        mode = not mode
    elif k == 27:


Above piece of code will work with only black background image. But rectangles can be drawn to any images. We can write a program which allows us to select desired portion in an image and extract that selected portion as well. The task includes following things –

  • draw shape on any image
  • re-select the extract portion for in case bad selection
  • extract particular object from the image

# Write Python code here
# import the necessary packages
import cv2
import argparse
# now let's initialize the list of reference point
ref_point = []
crop = False
def shape_selection(event, x, y, flags, param):
    # grab references to the global variables
    global ref_point, crop
    # if the left mouse button was clicked, record the starting
    # (x, y) coordinates and indicate that cropping is being performed
    if event == cv2.EVENT_LBUTTONDOWN:
        ref_point = [(x, y)]
    # check to see if the left mouse button was released
    elif event == cv2.EVENT_LBUTTONUP:
        # record the ending (x, y) coordinates and indicate that
        # the cropping operation is finished
        ref_point.append((x, y))
        # draw a rectangle around the region of interest
        cv2.rectangle(image, ref_point[0], ref_point[1], (0, 255, 0), 2)
        cv2.imshow("image", image)
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required = True, help ="Path to the image")
args = vars(ap.parse_args())
# load the image, clone it, and setup the mouse callback function
image = cv2.imread(args["image"])
clone = image.copy()
cv2.setMouseCallback("image", shape_selection)
# keep looping until the 'q' key is pressed
while True:
    # display the image and wait for a keypress
    cv2.imshow("image", image)
    key = cv2.waitKey(1) & 0xFF
    # press 'r' to reset the window
    if key == ord("r"):
        image = clone.copy()
    # if the 'c' key is pressed, break from the loop
    elif key == ord("c"):
if len(ref_point) == 2:
    crop_img = clone[ref_point[0][1]:ref_point[1][1], ref_point[0][0]:
    cv2.imshow("crop_img", crop_img)
# close all open windows

Run : Save the file as and for testing select a demo picture which is located in the same directory. Now, execute the following command –

python --image demo.jpg

Output: First select the desired portion from the image. In addition, we can remove bad selection by pressing ‘r’ as programmed for making a new proper selection.

Fig: Selected Portion

Now after selecting a proper selection like above, just press ‘c’ to extract, as programmed.
Fig: Cut Portion

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Last Updated : 04 Jan, 2023
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