openmv，巡线两条黄线，如果有一条黄线突然没有了怎么靠另一条黄线寻线，但不影响啊后来的两条黄线巡线

以下是一个完整的 OpenMV 巡线代码，可以巡线两条黄线，并在一条黄线消失时通过另一条黄线进行寻线，同时不影响后来的两条黄线巡线。

import sensor
import image
import time
import math

# 设置巡线阈值
GRAYSCALE_THRESHOLD = (200, 255)
# 设置寻线偏移量
OFFSET = 30
# 设置两条黄线的最小距离
MIN_DIST = 50

# 初始化摄像头
sensor.reset()
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 2000)
sensor.set_auto_gain(False)
sensor.set_auto_whitebal(False)

# 初始化PID控制器
kp = 0.5
kd = 0.1
last_error = 0

# 记录上一次检测到的黄线
last_line1 = None
last_line2 = None

# 巡线
while True:
    # 获取图像
    img = sensor.snapshot()

    # 查找两条黄线
    line1 = None
    line2 = None
    for l in img.find_lines(threshold = 1000, theta_margin = 25, rho_margin = 25):
        if l.y1() < 60 or l.y2() < 60:
            continue
        if abs(l.theta()) < 60:
            line1 = l
        elif abs(l.theta()) > 120:
            line2 = l

    # 如果只有一条黄线，通过偏移量寻找另一条黄线
    if line1 is not None and line2 is None:
        line2_x = line1.x1() + (line1.x2() - line1.x1()) * (120 if line1.theta() < 0 else -120) / line1.theta()
        line2_y = line1.y1() + (line1.y2() - line1.y1()) * (120 if line1.theta() < 0 else -120) / line1.theta()
        line2 = (line2_x, line2_y, line1.x2(), line1.y2())

    # 如果两条黄线都存在，计算偏差值并进行PID控制
    if line1 is not None and line2 is not None:
        # 计算两条黄线的距离
        dist = math.sqrt((line1.x1() - line2.x1()) ** 2 + (line1.y1() - line2.y1()) ** 2)

        # 如果两条黄线的距离小于最小距离，忽略掉其中一条黄线
        if dist < MIN_DIST:
            if last_line1 is None or last_line2 is None:
                continue
            elif line1 == last_line1 and line2 == last_line2:
                continue
            elif line1 == last_line2 and line2 == last_line1:
                continue
            elif last_line1 is not None and last_line2 is not None:
                if dist < math.sqrt((last_line1.x1() - last_line2.x1()) ** 2 + (last_line1.y1() - last_line2.y1()) ** 2):
                    line1 = last_line1
                    line2 = last_line2

        # 计算机器人偏离中心线的距离
        error = (line1.x1() + line2.x1() - img.width()) / 2

        # 计算PID控制值
        pid = error * kp + (error - last_error) * kd
        last_error = error

        # 控制机器人行驶
        if abs(pid) > OFFSET:
            if pid > 0:
                # 左转
                pass
            else:
                # 右转
                pass
        else:
            # 直行
            pass

        # 更新上一条黄线
        last_line1 = line1
        last_line2 = line2

在这个例子中，我们添加了一个新的变量 `last_line1` 和 `last_line2` 来记录上一次检测到的黄线。当检测到两条黄线的距离小于最小距离时，我们会比较当前检测到的黄线和上一次检测到的黄线，选择距离更远的两条黄线进行巡线，同时忽略掉重复的情况。这样可以避免在一条黄线消失后立即切换到另一条黄线，从而影响后来的两条黄线巡线。