Red Object Detection in Images

This function reads an image from a specified path, converts the image to the HSV color space, defines the HSV range for red color, creates a mask for red color, finds contours of red objects in the image, and draws the contours on the original image.

Technology Stack : OpenCV, NumPy

Code Type : Image processing

Code Difficulty : Intermediate

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

    # Read the image
    image = cv2.imread(image_path)
    # Convert the image to HSV color space
    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
    # Define the range for red color in HSV
    lower_red = np.array([0, 120, 70])
    upper_red = np.array([10, 255, 255])
    lower_red2 = np.array([170, 120, 70])
    upper_red2 = np.array([180, 255, 255])
    # Create masks for red color
    mask1 = cv2.inRange(hsv, lower_red, upper_red)
    mask2 = cv2.inRange(hsv, lower_red2, upper_red2)
    # Combine the masks
    mask = cv2.add(mask1, mask2)
    # Bitwise-AND the original image and mask
    res = cv2.bitwise_and(image, image, mask=mask)
    # Find contours
    contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    # Draw contours on the image
    cv2.drawContours(image, contours, -1, (0, 255, 0), 3)
    # Return the image with red objects highlighted
    return image