Image Segmentation in OpenCV with Python and Contours

### Import the OpenCV library to handle image processing operations. import cv2 ### Import NumPy for numerical operations and for creating masks as arrays. import numpy as np  ### Read the input image from disk into a NumPy array using OpenCV. img = cv2.imread("Open-CV/Image-Segmentation-using-Contour-Detection/beach-and-boats.jpeg")  ### Convert the color image to grayscale to simplify thresholding and contour detection. gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) ### Apply an inverse binary threshold using the mean gray value as the threshold dynamically. _ , tresh = cv2.threshold(gray,np.mean(gray), 255, cv2.THRESH_BINARY_INV   )  ### Detect all contours from the thresholded image using a simple chain approximation. ### hierarchy is returned but not used directly in this script. contours , hierarchy = cv2.findContours(tresh, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)  ### Print the number of contours found for quick debugging and insight. print(len(contours))   ### Sort contours by area and select the largest one, which typically corresponds to the main object. cnt = sorted(contours, key=cv2.contourArea)[-1]  ### Create a blank single-channel mask with a specific height and width matching the target canvas. ### dtype=uint8 is required for OpenCV masking operations. mask = np.zeros( (750, 1038), dtype="uint8" )  ### Draw the largest contour onto the mask (filled) using a red color tuple. ### Color channels are provided, but with a single-channel mask the intensity value is what matters. maskedRed = cv2.drawContours(mask,[cnt] , -1 , (0 , 0 , 255), -1) ### Draw the same filled contour using white to produce the final binary mask of the object. maskedFinal = cv2.drawContours(mask,[cnt] , -1 , (255 , 255 , 255), -1)  ### Use bitwise_and to apply the mask to the original image and keep only the segmented object. finalImage = cv2.bitwise_and(img, img, mask=maskedFinal)  ### Show the original image in a window for comparison. cv2.imshow("Original", img) ### Show the masked result to verify segmentation visually. cv2.imshow("maskedFinal", finalImage)  ### Save the binary mask to disk for reuse or inspection. cv2.imwrite("c:/temp/maskedFinal.jpg",maskedFinal) ### Save the final segmented image result to disk. cv2.imwrite("c:/temp/finalImage.jpg",finalImage)  ### Wait indefinitely for a key press so the display windows remain visible. cv2.waitKey(0)  ### Clean up OpenCV windows to free resources. cv2.destroyAllWindows()