Image Contour Detection and Visualization

This function reads an image from a specified path, converts it to a grayscale image, and then applies thresholding to get a binary image. After that, it uses OpenCV's findContours function to detect contours in the image and draws them on the original image. Finally, it displays the image with contours.

Technology Stack : OpenCV, NumPy

Code Type : Image processing

Code Difficulty : Intermediate

                
                    
def find_contours(image_path):
    import cv2
    import numpy as np

    # Read the image
    image = cv2.imread(image_path)
    # Convert the image to grayscale
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    # Apply thresholding to get a binary image
    _, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)
    # Find contours
    contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    # Draw contours on the original image
    cv2.drawContours(image, contours, -1, (0, 255, 0), 2)

    # Display the image with contours
    cv2.imshow('Image with Contours', image)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

    return contours