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.

Python3

# 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

Python3

# 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.