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

Last Updated : 04 Jan, 2023

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) 
            else: 
                cv2.circle(img, (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) 
      
        else: 
            cv2.circle(img, (x, y), 5, (0, 0, 255), -1) 
      
img = np.zeros((512, 512, 3), np.uint8) 
cv2.namedWindow('image') 
cv2.setMouseCallback('image', draw_circle) 
  
while(1): 
    cv2.imshow('image', img) 
    k = cv2.waitKey(1) & 0xFF
    if k == ord('m'): 
        mode = not mode 
    elif k == 27: 
        break
  
cv2.destroyAllWindows()  

Output:

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.namedWindow("image") 
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"): 
        break
  
if len(ref_point) == 2: 
    crop_img = clone[ref_point[0][1]:ref_point[1][1], ref_point[0][0]: 
                                                           ref_point[1][0]] 
    cv2.imshow("crop_img", crop_img) 
    cv2.waitKey(0) 
  
# close all open windows 
cv2.destroyAllWindows()  

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

python capture_events.py --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.