python如何批量将文档照片校正后保存为干净的图片？

方法思路

边缘检测：使用Canny算法检测文档边缘轮廓识别：找到最大四边形轮廓（假定文档是最大的四边形）透视变换：将倾斜的四边形转换为矩形图像增强：二值化处理增强可读性批量处理：遍历文件夹处理所有图片实现代码

import cv2
import numpy as np
import glob
import os

def order_points(pts):
    """将四个点排序为：左上、右上、右下、左下"""
    rect = np.zeros((4, 2), dtype="float32")
    s = pts.sum(axis=1)
    rect[0] = pts[np.argmin(s)]  # 最小和为左上
    rect[2] = pts[np.argmax(s)]  # 最大和为右下

    diff = np.diff(pts, axis=1)
    rect[1] = pts[np.argmin(diff)]  # 最小差为右上
    rect[3] = pts[np.argmax(diff)]  # 最大差为左下
    return rect

def four_point_transform(image, pts):
    """执行透视变换"""
    rect = order_points(pts)
    (tl, tr, br, bl) = rect

    # 计算新宽度
    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))

    # 计算新高度
    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))

    # 构建目标点坐标
    dst = np.array([
        [0, 0],
        [maxWidth - 1, 0],
        [maxWidth - 1, maxHeight - 1],
        [0, maxHeight - 1]], dtype="float32")

    # 计算变换矩阵并执行变换
    M = cv2.get...

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