I'm struggling to get the bounding box for an identified area in an image. The following code results in this image: https://i.sstatic.net/6HX4dNrB.png. However, as might be obvious from the picture, I'd like to bounding box to enclose the (black) identified large area instead. Any suggestions on how to accomplish that? import numpy as np import cv2 # Load the image image = cv2.imread("image.png") # Update with your image path gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) # Define refined HSV ranges for sandy ground (light brown, beige, gray) lower_sand = np.array([10, 20, 100]) # Lower bound for sand-like colors upper_sand = np.array([30, 100, 255]) # Upper bound for sand-like colors # Create a mask for the sandy competition ground mask_sand = cv2.inRange(hsv, lower_sand, upper_sand) # Apply morphological operations to reduce noise kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (7, 7)) mask_sand = cv2.morphologyEx(mask_sand, cv2.MORPH_CLOSE, kernel) # Close gaps mask_sand = cv2.morphologyEx(mask_sand, cv2.MORPH_OPEN, kernel) # Remove small noise # Invert the mask (to highlight everything except the competition area) mask = cv2.bitwise_not(mask_sand) # Apply the inverted mask to the original image output = cv2.bitwise_and(image, image, mask=mask) # Ensure the mask is properly binarized for contour detection ret, thresh = cv2.threshold(mask, 50, 255, cv2.THRESH_BINARY) # Find contours contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) if contours: # Find the largest contour by area largest_contour = max(contours, key=cv2.contourArea) # Approximate the contour to a quadrilateral epsilon = 0.02 * cv2.arcLength(largest_contour, True) approx = cv2.approxPolyDP(largest_contour, epsilon, True) # If the approximation has 4 points, use it; otherwise, use convex hull if len(approx) == 4: quadrilateral = approx else: quadrilateral = cv2.convexHull(largest_contour) # Draw the quadrilateral in green cv2.polylines(output, [quadrilateral], isClosed=True, color=(0, 255, 0), thickness=3) # Draw all detected contours in blue cv2.drawContours(output, contours, -1, (255, 0, 0), 2) # Show and save the output cv2.imshow("Result", np.hstack([image, output])) cv2.imwrite("output_image.png", output) cv2.waitKey(0) cv2.destroyAllWindows() Continue reading...
