openmv与其他单片双向串口通信

Openmv与其他单片双向串口通信

目的

起因

openmv自带接收函数uart.read() 进行接收，但接收回来的数据类型为字符串不能用于数值的比较，需要将字符串打散转化为字符类型，因此我采用强制转换的方法，代码如下

def recive_data():
    global tmp_data
    if uart.any():        #等待接收
      t = uart.read();	  #读入数据
      tmp_data=int(t)     #强制转换为整型变量
      print(tmp_data)

注意：因为将字符串强制转换为整型，此代码只能接收以数字所建立的标志位。其他标志会引起代码报错，这也是代码的一个大bug，希望大家多多指教。

以下收发颜色捕捉的完整代码

import json
import ustruct
import sensor, image, time
from pyb import UART
thresholds = [(30, 50, 40, 90, 35, 80), # red_thresholds
              (30, 60, -80, -20, 0,40), # green_thresholds
              (10, 40, 0, 40, -80, -20)] # blue_thresholds

clock = time.clock()
uart = UART(3,115200)
uart.init(115200, bits=8, parity=None, stop=1)
def sending_data(cx,cy):
    global uart;
    #frame=[0x2C,18,cx%0xff,int(cx/0xff),cy%0xff,int(cy/0xff),0x5B];
    #data = bytearray(frame)
    data = ustruct.pack("<bbhhhhb",              #格式为俩个字符俩个短整型(2字节)
                       0x2C,                       #帧头1
                       0x12,                       #帧头2
                       int(cx), # up sample by 4    #数据1
                       int(cy), # up sample by 4    #数据2
                       int(c),                      #
                       int(R),
                       0x5B)
    uart.write(data);   #必须要传入一个字节数组
    print(cx)
    print(cy)
    print(c)
    print(R)
def sending_data1(q):
    global uart;
    #frame=[0x2C,18,cx%0xff,int(cx/0xff),cy%0xff,int(cy/0xff),0x5B];
    #data = bytearray(frame)
    data = ustruct.pack("<bbhhhhb",              #格式为俩个字符俩个短整型(2字节)
                       0x2C,                       #帧头1
                       0x12,                       #帧头2
                       int(cx), # up sample by 4    #数据1
                       int(cy), # up sample by 4    #数据2
                       int(q),                      #
                       int(40),
                       0x5B)
    uart.write(data);   #必须要传入一个字节数组

def recive_data():
    global tmp_data
    if uart.any():
      t = uart.read();
      tmp_data=int(t)
      print(tmp_data)
def compare(shu1,shu2):
   if (shu1 >= shu2):
        return shu1
   else:
        return shu2
def find_max(blobs):    #定义寻找色块面积最大的函数
   max_size=0
   for blob in blobs:
    if blob.pixels() > max_size:
        max_blob=blob
        max_size = blob.pixels()
        return max_blob
c=0
tmp_data=0
while(1):
    if(tmp_data==1):
            sensor.reset()
            sensor.set_pixformat(sensor.RGB565)
            sensor.set_framesize(sensor.QVGA)
            sensor.skip_frames(time = 2000)
            sensor.set_auto_gain(False) # must be turned off for color tracking
            sensor.set_auto_whitebal(False) # must be turned off for color tracking
            sensor.set_vflip(False)
            sensor.set_hmirror(False)
            while(1):
                img = sensor.snapshot().lens_corr(1.8)
                for blob in img.find_blobs(thresholds, pixels_threshold=300, area_threshold=300):
                    blobs=img.find_blobs(thresholds, pixels_threshold=300, area_threshold=300)
                    if blobs:#如果找到了目标颜色
                        max_b = find_max(blobs)
                        img.draw_rectangle(max_b.rect())
                        img.draw_cross(max_b.cx(), max_b.cy())
                        x = max_b.density()
                        if(x<0.6 and x>0.4):
                          c=1
                        elif(x>0.7 and x<0.8):
                          c=2
                        elif(x>0.8):
                          c=3
                        cx = max_b.cx()
                        cy = max_b.cy()
                        R  = max_b.w()
                        sending_data(cx,cy)
                recive_data()
    elif(tmp_data==2):
        sensor.reset()
        sensor.set_pixformat(sensor.RGB565)
        sensor.set_framesize(sensor.QQVGA)
        sensor.skip_frames(time = 2000)
        sensor.set_auto_gain(False) # must be turned off for color tracking
        sensor.set_auto_whitebal(False) # must be turned off for color tracking
        sensor.set_vflip(False)
        sensor.set_hmirror(False)
        while(1):
            img = sensor.snapshot()
            max_size = 0
            for c in img.find_circles(threshold = 4000, x_margin = 10, y_margin = 10, r_margin = 10,r_min = 2, r_max = 100, r_step = 2):
                    area = (c.x()-c.r(), c.y()-c.r(), 2*c.r(), 2*c.r())
                    cx=c.x()
                    cy=c.y()
                    #area为识别到的圆的区域，即圆的外接矩形框
                    statistics = img.get_statistics(roi=area)#像素颜色统计
                    print(statistics)
                    #(0,100,0,120,0,120)是红色的阈值，所以当区域内的众数（也就是最多的颜色），范围在这个阈值内，就说明是红色的圆。
                    #l_mode()，a_mode()，b_mode()是L通道，A通道，B通道的众数。
                    if 5<statistics.l_mode()<20 and 0<statistics.a_mode()<40 and 0<statistics.b_mode()<40:#if the circle is red
                       img.draw_rectangle(area, color = (255, 0, 255))
                       #sending_data(c.x(),c.y())
                       c=1
                       R=0

                       sending_data(cx,cy)
                    elif 20<statistics.l_mode()<40 and -40<statistics.a_mode()<0 and -40<statistics.b_mode()<0:
                        img.draw_rectangle(area, color = (255, 255, 0))
                        c=2
                        R=0

                        sending_data(cx,cy)
                    elif 40<statistics.l_mode()<60 and -20<statistics.a_mode()<40 and -40<statistics.b_mode()<50:
                        img.draw_rectangle(area, color = (255, 255, 0))
                        c=3
                        R=0

                        sending_data(cx,cy)
            recive_data()
    else :
            recive_data()

后续

其他单片机的接收函数只需要配置串口中断，然后在相应串口中断服务函数里面写好相应的解析函数即可，具体不在详解。发送函数只需发送0-9数字即可。