人像分割双十一促销活动

import cv2
import numpy as np

def segment_person(image_path):
    # Load the image
    img = cv2.imread(image_path)
    # Convert to grayscale
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    # Apply a GaussianBlur to reduce noise and improve edge detection
    blurred = cv2.GaussianBlur(gray, (11, 11), 0)
    # Use Canny edge detection
    edges = cv2.Canny(blurred, 30, 150)
    # Find contours
    contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    # Create a mask for the person
    mask = np.zeros_like(gray)
    cv2.drawContours(mask, contours, -1, (255), thickness=cv2.FILLED)
    # Apply the mask to the original image
    result = cv2.bitwise_and(img, img, mask=mask)
    return result

# Example usage
segmented_image = segment_person('path_to_image.jpg')
cv2.imshow('Segmented Image', segmented_image)
cv2.waitKey(0)
cv2.destroyAllWindows()