调用cv2.findContours()函数实现轮廓检测，检测图像中物体的轮廓。 2、调用imutils.grab_contours()函数获取图像轮廓。 3、调用contours.sort_contours()函数将轮廓从左到右进行排序。 4、初始化比例系数pixelsPerMetric为空，用于后续真实长度计算。 5、初始化参照物宽度width为3，用于后续真实长度计算。python

非常好的问题！以下是代码示例：

import cv2
import imutils
from imutils import contours

# 读取图像
image = cv2.imread("example.jpg")

# 灰度化
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# 边缘检测
edged = cv2.Canny(gray, 50, 100)

# 轮廓检测
cnts = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = imutils.grab_contours(cnts)

# 轮廓排序
(cnts, _) = contours.sort_contours(cnts)

# 初始化比例系数和参照物宽度
pixelsPerMetric = None
width = 3

# 真实长度计算
for c in cnts:
    if cv2.contourArea(c) < 100:
        continue
    orig = image.copy()
    box = cv2.minAreaRect(c)
    box = cv2.boxPoints(box)
    box = np.array(box, dtype="int")
    box = perspective.order_points(box)
    cv2.drawContours(orig, [box.astype("int")], -1, (0, 255, 0), 2)
    for (x, y) in box:
        cv2.circle(orig, (int(x), int(y)), 5, (0, 0, 255), -1)
    (tl, tr, br, bl) = box
    (tltrX, tltrY) = midpoint(tl, tr)
    (blbrX, blbrY) = midpoint(bl, br)
    (tlblX, tlblY) = midpoint(tl, bl)
    (trbrX, trbrY) = midpoint(tr, br)
    cv2.circle(orig, (int(tltrX), int(tltrY)), 5, (255, 0, 0), -1)
    cv2.circle(orig, (int(blbrX), int(blbrY)), 5, (255, 0, 0), -1)
    cv2.circle(orig, (int(tlblX), int(tlblY)), 5, (255, 0, 0), -1)
    cv2.circle(orig, (int(trbrX), int(trbrY)), 5, (255, 0, 0), -1)
    dA = dist.euclidean((tltrX, tltrY), (blbrX, blbrY))
    dB = dist.euclidean((tlblX, tlblY), (trbrX, trbrY))
    if pixelsPerMetric is None:
        pixelsPerMetric = dB / width
    dimA = dA / pixelsPerMetric
    dimB = dB / pixelsPerMetric
    cv2.putText(orig, "{:.1f}in".format(dimA),
        (int(tltrX - 15), int(tltrY - 10)), cv2.FONT_HERSHEY_SIMPLEX,
        0.65, (255, 255, 255), 2)
    cv2.putText(orig, "{:.1f}in".format(dimB),
        (int(trbrX + 10), int(trbrY)), cv2.FONT_HERSHEY_SIMPLEX,
        0.65, (255, 255, 255), 2)
    cv2.imshow("Image", orig)
    cv2.waitKey(0)

这段代码可以实现轮廓检测、轮廓排序和真实长度计算。