用openmv写一段驱动两个电机循迹小车的代码

### 回答1：
你好，我可以回答这个问题。以下是用openmv写一段驱动两个电机循迹小车的代码：

import sensor, image, time
from pyb import Pin, Timer

# 设置左右电机引脚
left_motor_pin1 = Pin("P", Pin.OUT_PP)
left_motor_pin2 = Pin("P1", Pin.OUT_PP)
right_motor_pin1 = Pin("P2", Pin.OUT_PP)
right_motor_pin2 = Pin("P3", Pin.OUT_PP)

# 设置左右电机PWM
left_motor_pwm = Timer(2, freq=100)
left_motor_ch1 = left_motor_pwm.channel(1, Timer.PWM, pin=left_motor_pin1)
left_motor_ch2 = left_motor_pwm.channel(2, Timer.PWM, pin=left_motor_pin2)
right_motor_pwm = Timer(4, freq=100)
right_motor_ch1 = right_motor_pwm.channel(1, Timer.PWM, pin=right_motor_pin1)
right_motor_ch2 = right_motor_pwm.channel(2, Timer.PWM, pin=right_motor_pin2)

# 设置循迹传感器引脚
sensor_pin1 = Pin("P4", Pin.IN)
sensor_pin2 = Pin("P5", Pin.IN)
sensor_pin3 = Pin("P6", Pin.IN)
sensor_pin4 = Pin("P7", Pin.IN)

# 设置循迹传感器阈值
threshold = (, 100)

# 循迹小车运动控制函数
def car_control(left_speed, right_speed):
    left_motor_ch1.pulse_width_percent(left_speed)
    left_motor_ch2.pulse_width_percent()
    right_motor_ch1.pulse_width_percent(right_speed)
    right_motor_ch2.pulse_width_percent()

# 循迹小车循迹函数
def car_tracking():
    while True:
        # 获取循迹传感器状态
        sensor1 = sensor_pin1.value()
        sensor2 = sensor_pin2.value()
        sensor3 = sensor_pin3.value()
        sensor4 = sensor_pin4.value()

        # 判断循迹传感器状态
        if sensor1 ==  and sensor2 ==  and sensor3 ==  and sensor4 == :
            car_control(, )
        elif sensor1 ==  and sensor2 ==  and sensor3 ==  and sensor4 == 1:
            car_control(50, 50)
        elif sensor1 ==  and sensor2 ==  and sensor3 == 1 and sensor4 == 1:
            car_control(70, 30)
        elif sensor1 ==  and sensor2 == 1 and sensor3 == 1 and sensor4 == :
            car_control(50, 50)
        elif sensor1 == 1 and sensor2 == 1 and sensor3 ==  and sensor4 == :
            car_control(30, 70)
        elif sensor1 == 1 and sensor2 ==  and sensor3 ==  and sensor4 == :
            car_control(50, 50)
        else:
            car_control(, )

# 初始化循迹传感器
sensor.reset()
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time=200)

# 循迹小车循迹
car_tracking()

希望能对你有所帮助！

### 回答2：
循迹小车的代码，使用OpenMV编写，如下所示：

import sensor
import image
import time
import pyb

sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 2000)
clock = time.clock()
# 初始化电机引脚
m1a = pyb.Pin(1, pyb.Pin.OUT_PP) # M1A
m1b = pyb.Pin(2, pyb.Pin.OUT_PP) # M1B
m2a = pyb.Pin(3, pyb.Pin.OUT_PP) # M2A
m2b = pyb.Pin(4, pyb.Pin.OUT_PP) # M2B

while(True):
    clock.tick()
    img = sensor.snapshot()

    # 进行图像处理，提取轨道线
    line = img.get_regression((100, 100, 0, 0, 0, 0), robust=True)
    if line:
        img.draw_line(line.line(), color=127)
        # 根据轨道线的位置调整小车的运动方向
        # 计算线的位置和图像中心的偏差，左负右正
        deviation = line.x1() - (img.width() // 2)
        # 根据偏差调整电机的转速
        speed_left = 100 - deviation // 10
        speed_right = 100 + deviation // 10
        if speed_left > 100:
            speed_left = 100
        if speed_right > 100:
            speed_right = 100
        # 控制电机转动
        m1a.value(1)
        m1b.value(0)
        m2a.value(1)
        m2b.value(0)
        time.sleep(20)
    else:
        # 没有检测到轨道线时停止小车
        m1a.value(0)
        m1b.value(0)
        m2a.value(0)
        m2b.value(0)

以上代码使用OpenMV库监测摄像头图像并进行处理。首先将摄像头图像转换为RGB565格式，并设置图像大小。然后进入循环，不断获取图像，并进行轨道线检测和处理。根据检测到的轨道线的位置，调整两个电机的转速，使小车能够跟随轨道线行驶。若没有检测到轨道线，则停止两个电机的运动。