Implementation of SelectiveSearch using python OpenCV

Let’s Manually build the Region for SelectiveSearch

Importing Libraries

Python3

# importing necessary libraries
import cv2
import selectivesearch
import matplotlib.pyplot as plt

                    

Creation of bounding boxes Manually

Python3

# Load the image
image_path = 'img_1.jpg'
image = cv2.imread(image_path)
# Define bounding box coordinates (x, y, width, height)
bounding_boxes = [
    (100, 50, 200, 150),  # Example bounding box 1
    (300, 200, 150, 100),  # Example bounding box 2
    # Add more bounding boxes as needed
]
 
# Draw bounding boxes on the image
for (x, y, w, h) in bounding_boxes:
    cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
 
# Display the image with bounding boxes
cv2_imshow(image)
 
# Wait for a key press and close the window
cv2.waitKey(0)
cv2.destroyAllWindows()

                    

Output:

This bit of code shows how to load and display a picture with bounding boxes drawn around key areas. It specifies bounding boxes as tuples of (x, y, width, and height) coordinates and uses the OpenCV library (cv2) to read an image. The next step is to use cv2.rectangle() to create green rectangles around each location of interest on the image when the code loops over the list of bounding boxes. After using cv2_imshow() to display the image with bounding boxes, the software waits for a key press before destroying all open windows and releasing resources using cv2.waitKey(0) and cv2.destroyAllWindows().

OpenCV Selective Search For Object Detection

OpenCV is a Python library that is used to study images and video streams. It basically extracts the pixels from the images and videos (stream of image) so as to study the objects and thus obtain what they contain. It contains low-level image processing and high-level algorithms for object detection, feature matching etc.

In this article, we will dive into a computer vision technique i.e. selective search for Object Detection in OpenCV.

Table of Content

  • Object Detection
  • Selective Search
  • Implementation of SelectiveSearch using python OpenCV
  • Selective Search using Region proposals

Similar Reads

Object Detection

...

Selective Search

Object Detection is a fundamental computer vision task that involves identifying and localizing objects or specific features within an image or a video stream. It plays a crucial role in numerous applications, including autonomous driving, surveillance, robotics, and image analysis. Object detection goes beyond mere object recognition by providing both the classification of objects into predefined categories or classes and the precise localization of where these objects exist within the image....

Implementation of SelectiveSearch using python OpenCV

Selective Search is a region-based technique extensively used for object detection tasks within computer vision. It aims to generate a varied set of region proposals from an input image, where each region proposal representing a potential object or object portion.These region proposals are subsequently used as candidate regions by object detection algorithms to categorize and localize objects within an image....

Selective Search using Region proposals

Let’s Manually build the Region for SelectiveSearch...