如何使用opencv python在各种颜色的背景中找到文档边缘？[在各种背景下扫描文档]

import cv2
import numpy as np

image = cv2.imread('your_image.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)

edges = cv2.Canny(blurred, 50, 150)

contours, _ = cv2.findContours(edges.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
doc_contour = None

for contour in contours:
    perimeter = cv2.arcLength(contour, True)
    approx = cv2.approxPolyDP(contour, 0.02 * perimeter, True)
    
    if len(approx) == 4:
        doc_contour = approx
        break

if doc_contour is not None:
    cv2.drawContours(image, [doc_contour], -1, (0, 255, 0), 2)
    rect = np.zeros((4, 2), dtype="float32")
    
    s = doc_contour.sum(axis=1)
    rect[0] = doc_contour[np.argmin(s)]
    rect[2] = doc_contour[np.argmax(s)]
    
    diff = np.diff(doc_contour, axis=1)
    rect[1] = doc_contour[np.argmin(diff)]
    rect[3] = doc_contour[np.argmax(diff)]
    
    (tl, tr, br, bl) = rect
    
    widthA = np.sqrt(((br[0] - bl[0]) ** 2) + ((br[1] - bl[1]) ** 2))
    widthB = np.sqrt(((tr[0] - tl[0]) ** 2) + ((tr[1] - tl[1]) ** 2))
    maxWidth = max(int(widthA), int(widthB))
    
    heightA = np.sqrt(((tr[0] - br[0]) ** 2) + ((tr[1] - br[1]) ** 2))
    heightB = np.sqrt(((tl[0] - bl[0]) ** 2) + ((tl[1] - bl[1]) ** 2))
    maxHeight = max(int(heightA), int(heightB))
    
    dst = np.array([[0, 0], [maxWidth - 1, 0], [maxWidth - 1, maxHeight - 1], [0, maxHeight - 1]], dtype="float32")
    M = cv2.getPerspectiveTransform(rect, dst)
    warped = cv2.warpPerspective(image, M, (maxWidth, maxHeight))

cv2.imshow("Scanned Document", warped)
cv2.waitKey(0)
cv2.destroyAllWindows()