图像配准，代码哪里出错了

from imutils import paths
import numpy as np
import imutils
import cv2

images = 'C:\learn\python\images\scottsdale'  # 输入图片文件夹路径
output = 'C:\learn\python\output.png'  # 输出图片名称
crop = True
imagePaths = sorted(list(paths.list_images(images)))
images = []

# 读取文件夹图片
for imagePath in imagePaths:
    image = cv2.imread(imagePath)
    images.append(image)

# 创建缝合器
stitcher = cv2.Stitcher_create()
(status, stitched) = stitcher.stitch(images)

# status:状态，0代表成功
if status == 0:
    # 裁剪图像
    if crop:
        # 在拼图周围添加2像素
        stitched = cv2.copyMakeBorder(stitched, 2, 2, 2, cv2.BORDER_CONSTANT, (0, 0, 0))

        # 对图像进行灰度化和阈值化
        gray = cv2.cvtColor(stitched, cv2.COLOR_BGR2GRAY)
        thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY)[1]

        # 查找阈值图像的轮廓
        cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
                                cv2.CHAIN_APPROX_SIMPLE)
        cnts = imutils.grab_contours(cnts)
        c = max(cnts, key=cv2.contourArea)

        # 在这个轮廓下绘制最大的矩形
        mask = np.zeros(thresh.shape, dtype="uint8")
        (x, y, w, h) = cv2.boundingRect(c)
        cv2.rectangle(mask, (x, y), (x + w, y + h), 255, -1)

        # 创建两个遮罩
        # minRect作为不断腐蚀的矩形
        # sub作为阈值图像和minRect的插值来进行判断
        minRect = mask.copy()
        sub = mask.copy()

        while cv2.countNonZero(sub) > 0:
            minRect = cv2.erode(minRect, None)
            sub = cv2.subtract(minRect, thresh)

        # 得到最小的矩形，提取其范围坐标
        cnts = cv2.findContours(minRect.copy(), cv2.RETR_EXTERNAL,
                                cv2.CHAIN_APPROX_SIMPLE)
        cnts = imutils.grab_contours(cnts)
        c = max(cnts, key=cv2.contourArea)
        (x, y, w, h) = cv2.boundingRect(c)

        # 使用该范围坐标对原图进行裁剪
        stitched = stitched[y:y + h, x:x + w]

    # 保存图片
    cv2.imwrite(output, stitched)

else:
    print("拼接失败，错误码：{}".format(status))

cv2.copyMakeBorder()函数的调用存在问题，第26行改成

stitched = cv2.copyMakeBorder(stitched, 2, 2, 2, cv2.BORDER_CONSTANT, value=(0, 0, 0))

您好，我是有问必答小助手，您的问题已经有小伙伴帮您解答，感谢您对有问必答的支持与关注！
PS：问答VIP年卡【限时加赠：IT技术图书免费领】，了解详情>>> https://vip.csdn.net/askvip?utm_source=1146287632

这有个类似的问题, 你可以参考下: https://ask.csdn.net/questions/7706627
这篇博客你也可以参考下：图像翻转代码实现
除此之外, 这篇博客: 图像增强算法中的代码部分也许能够解决你的问题, 你可以仔细阅读以下内容或跳转源博客中阅读:

import cv2
import numpy as np
from matplotlib import pyplot as plt

img = cv2.imread('gu.jpg',0)

laplacian = cv2.Laplacian(img,cv2.CV_64F)
sobelx = cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3)
sobely = cv2.Sobel(img,cv2.CV_64F,0,1,ksize=3)

sobelx = np.uint8(np.absolute(sobelx))
sobely = np.uint8(np.absolute(sobely))
sobelCom = cv2.bitwise_or(sobelx,sobely)

C = img+laplacian
E = cv2.blur(sobelCom,(5,5))
F = C*E

mina = np.min(F)
maxa = np.max(F)
#print(mina,maxa)
F = np.uint8(255*(F-mina)/(maxa-mina))
G = img+F
H = cv2.pow(G/255.0,0.5)

plt.subplot(2,4,1),plt.imshow(img,cmap='gray')
plt.title('A = original'),plt.xticks([]),plt.yticks([])

plt.subplot(2,4,2),plt.imshow(laplacian,cmap='gray')
plt.title('B = laplacian'),plt.xticks([]),plt.yticks([])

plt.subplot(2,4,3),plt.imshow(C,cmap='gray')
plt.title('C = add a and b'),plt.xticks([]),plt.yticks([])

plt.subplot(2,4,4),plt.imshow(sobelCom,cmap='gray')
plt.title('D = sobel'),plt.xticks([]),plt.yticks([])

plt.subplot(2,4,5),plt.imshow(E,cmap='gray')
plt.title('E = blur sobel'),plt.xticks([]),plt.yticks([])

plt.subplot(2,4,6),plt.imshow(F,cmap='gray')
plt.title('F = C*E'),plt.xticks([]),plt.yticks([])

plt.subplot(2,4,7),plt.imshow(G,cmap='gray')
plt.title('G = add a and f'),plt.xticks([]),plt.yticks([])

plt.subplot(2,4,8),plt.imshow(H,cmap='gray')
plt.title('H = mi lv'),plt.xticks([]),plt.yticks([])

plt.show()

您还可以看一下颜廷吉老师的软件架构师成长之路课程中的动态代理模式小节, 巩固相关知识点