594 lines
23 KiB
Python
594 lines
23 KiB
Python
'''
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K210 视频循迹示例
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'''
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import math
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import sensor, image, time, lcd
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import binascii
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from Maix import GPIO
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from machine import Timer, PWM, UART, Timer
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from fpioa_manager import fm
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# Debug模式开关，打开后方便显示调试信息
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#is_debug = True
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is_debug = False
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QR_num = 0
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JTD = False
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QR_Flag = False
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Flag_track = False
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#--------------感光芯片配置 START -------------------
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DISTORTION_FACTOR = 1 # 设定畸变系数
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IMG_WIDTH = 240
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IMG_HEIGHT = 320
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def init_sensor():
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'''
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初始化感光芯片
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'''
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lcd.init(freq=15000000) #初始化LCD
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sensor.reset() #复位和初始化摄像头
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sensor.set_vflip(1) #将摄像头设置成后置方式（所见即所得）
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sensor.set_pixformat(sensor.RGB565) # 设置像素格式为彩色 RGB565
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#sensor.set_pixformat(sensor.GRAYSCALE) # 设置像素格式为灰色
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sensor.set_framesize(sensor.QVGA) # 设置帧大小为 QVGA (320x240)
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#sensor.set_auto_gain(0,0)
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#sensor.set_auto_exposure(1) # 设置自动曝光
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sensor.set_auto_gain(0, gain_db = 8) # 设置画面增益 17 dB 影响实时画面亮度
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#sensor.set_auto_whitebal(0, rgb_gain_db = (0,0,0))
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sensor.skip_frames(time = 2000) # 等待设置生效
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clock = time.clock() # 创建一个时钟来追踪 FPS（每秒拍摄帧数）
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init_sensor()
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#--------------感光芯片配置 END -------------------
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#--------------串口UART部分 START -------------------
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#映射串口引脚
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fm.register(6, fm.fpioa.UART1_RX, force=True)
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fm.register(7, fm.fpioa.UART1_TX, force=True)
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#初始化串口
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uart = UART(UART.UART1, 115200, read_buf_len=4096)
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def get_symbol(num):
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'''
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根据数值正负，返回数值对应的符号
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正数： ‘+’， 负数‘-’ 主要为了方便C语言解析待符号的数值。
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尝试，若为0，输出‘,’。
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'''
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if num > 0:
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return ord('+')
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elif num < 0:
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return ord('-')
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else :
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return ord(',')
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def data_format_wrapper(down_center, state_crossing, deflection_angle):
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'''
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根据通信协议封装循迹数据
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TODO 重新编写通信协议 与配套C解析代码
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'''
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send_data = [
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0x55,
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0x02,
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0x91,
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down_center, # 底部色块中心是否在中点附近#底部色块十字路口
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1 if state_crossing else 0, #是否越障
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get_symbol(deflection_angle), # 偏航角符号 print输出是43 + 45- +向左转调整 -向右转调整 44 , 不调整
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abs(int(deflection_angle)), # 偏航角
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0xbb
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]
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global is_debug
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if is_debug:
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print(send_data)
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return bytes(send_data)
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def UsartSend(str_data):
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'''
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串口发送函数
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'''
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uart.write(str_data)
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#--------------串口UART部分 END -------------------
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#--------------定时器部分 START -------------------
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is_need_send_data = False # 是否需要发送数据的信号标志
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def uart_time_trigger(tim):
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'''
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串口发送数据的定时器，定时器的回调函数
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'''
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global is_need_send_data, QR_Flag, QR_num
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if QR_Flag:
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QR_num += 1
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if QR_num >= 200: # 10秒计时
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QR_Flag = False
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QR_num = 0
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is_need_send_data = True
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'''
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初始化定时器, 每秒执行20次
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period ： 周期1000/20=50
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callback： 回调函数
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'''
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tim1 = Timer(Timer.TIMER1, Timer.CHANNEL1, mode=Timer.MODE_PERIODIC, period=50, callback=uart_time_trigger)
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#--------------定时器部分 END -------------------
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#--------------舵机配置 START -------------------
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def Servo(angle):
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'''
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说明：舵机控制函数
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功能：180度舵机：angle:-90至90 表示相应的角度
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360连续旋转度舵机：angle:-90至90 旋转方向和速度值。
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【duty】占空比值：0-100
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'''
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#PWM通过定时器配置，接到IO17引脚
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tim_pwm = Timer(Timer.TIMER0, Timer.CHANNEL0, mode=Timer.MODE_PWM)
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S1 = PWM(tim_pwm, freq=50, duty=0, pin=17)
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S1.duty((angle+90)/180*10+2.5)
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Servo(0) # 默认向下0度
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time.sleep(1)
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#--------------舵机配置 END -------------------
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#--------------直线检测部分 START -------------------
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# 直线灰度图颜色阈值
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LINE_COLOR_THRESHOLD = [(0, 60)] #找黑色
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LINE_COLOR_BAISE=[(60,255)] #找白色
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#LIGHT_LINE_COLOR_THRESHOLD = [(9, 88)]
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#LINE_COLOR_THRESHOLD = [(0, 52, -19, 0, -1, 14)]
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# 以实际空间坐标为基准，取样窗口
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'''
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********屏幕ROI区域*******
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* | ------上方----- |
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* 左 ------中上----- 右
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* 侧 ------中下----- 侧
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* | ------下方----- |
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********屏幕ROI区域*******
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'''
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ROIS = {
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#'left': (0, 0, 320, 50), # 纵向取样-左侧
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#'right': (0, 190, 320, 50), # 纵向取样-右侧
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'left': (0, 0, 180, 50), # 纵向取样-左侧
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'right': (0, 190, 180, 50), # 纵向取样-右侧
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'up': (240, 0, 80, 240), # 横向取样-上方
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'middle_up': (160, 0, 80, 240), # 横向取样-中上
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'middle_down': (80, 0, 80, 240), # 横向取样-中下
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'down': (0, 0, 80, 240), # 横向取样-下方
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}
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#找黑色
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ROIS_BAISE = {
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'wleft':(110, 0, 100, 20),
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'wright':(110, 220, 100, 20),
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'wconte':(110, 45, 100, 150), #白色中心区域
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}
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#找白色
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def find_blobs_in_rois(img):
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'''
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说明：在ROIS中寻找色块，获取ROI中色块的中心区域与是否有色块的信息
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'''
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global ROIS # global定义全局变量 字典数组
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global is_debug # Debug模式开关，打开后方便显示调试信息
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canvas = img.copy() # 复制给 canvas 实时传输的图片 img类型
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canvas_baise = img.copy() # 判断白色的图片
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roi_blobs_result = {} # 在各个ROI中寻找色块的结果记录 空的 定义的
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roi_blobs_baise = {} # 定义白色的色块寻找色块的结果记录 空的 定义的
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for roi_direct in ROIS.keys(): # 赋值初始化键值 黑线
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roi_blobs_result[roi_direct] = {
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'cx':0,
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'cy':0,
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'w':0,
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'blob_flag': False # 标志位
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}
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for roi_baise in ROIS_BAISE.keys(): # 赋值初始化键值 白色
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roi_blobs_result[roi_baise] = {
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'wcx':0,
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'wcy':0,
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'ww':0,
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'wblob_baise': False # 标志位
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}
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for roi_direct, roi in ROIS.items(): # 返回键值对 赋值给前两个参数 第一个是键 第二个是值
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blobs=canvas.find_blobs(LINE_COLOR_THRESHOLD, roi=roi,area_threshold=400,merge=True)
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# 查找图像中所有区域黑色色块，并返回一个包括每个色块的色块对象的列表
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# 判断返回列表不为空
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if len(blobs) != 0:
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largest_blob = max(blobs, key=lambda b: b.pixels())
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if largest_blob.area() > 1000: # 判断色块返回面积是否大于1000
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x,y,width,height = largest_blob[:4] # 将列表0到3
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#roi_blobs_result[roi_direct]['cx'] = largest_blob.cy()-40 #存疑为什么-40 #此处XY轴互换
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roi_blobs_result[roi_direct]['cx'] = largest_blob.cy() #存疑为什么-40 #此处XY轴互换，返回色块的外框的中心Y坐标
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roi_blobs_result[roi_direct]['cy'] = largest_blob.cx() #存疑为什么-40 #此处XY轴互换，返回色块的外框的中心X坐标
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roi_blobs_result[roi_direct]['w'] = largest_blob.h()
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roi_blobs_result[roi_direct]['blob_flag'] = True
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if is_debug:
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print('LINE_COLOR_THRESHOLD*****')
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#print(largest_blob[:4] )
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#print('largest_blob内容*****')
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#print(largest_blob)
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#koimg.draw_rectangle((x,y,width, height), color=(0))
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#img.draw_rectangle((0, 0, 180, 50), color=(255))
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else:
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#blobs=canvas.find_blobs(LINE_COLOR_THRESHOLD, roi=roi, merge=True, pixels_area=10)
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continue
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blobs_baise = canvas.find_blobs(LINE_COLOR_BAISE, roi=(0, 0, 60, 240), merge=True)#车载摄像头屏幕下部找白色#宽度200修改为240#用途寻卡，y示例中40修改为0
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blobs_dixing = canvas.find_blobs(LINE_COLOR_BAISE, roi=(125, 0, 60, 240), merge=True)#车载摄像头屏幕中间找白色 #宽度200修改为240，y示例中40修改为0
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blobs_zuo = canvas.find_blobs(LINE_COLOR_THRESHOLD, roi=(0, 0, 180, 50), merge=True)#车载摄像头屏幕左下部找黑色
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blobs_you = canvas.find_blobs(LINE_COLOR_THRESHOLD, roi=(0, 190, 180, 50), merge=True)#车载摄像头屏幕右下部找黑色
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#if len(blobs_baise) != 0:#进行了修改先让摄像头中部区域先碰到白色
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if len(blobs_baise) != 0:
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print("*********进入循环第1步*******")
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largest_baise = max(blobs_baise , key = lambda b:b.pixels())
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wx,wy,wwidth,wwheight = largest_baise[:4]
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#print("宽度",largest_baise[2])
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#print("高度",largest_baise[3])
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#largest_blobs_zuo = max(blobs_zuo , key = lambda b:b.pixels())
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#Bx_L,By_L,Bwidth_L,Bwheight_L = largest_blobs_zuo[:4]
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#arc_L=Bwidth_L*Bwheight_L
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#largest_blobs_you = max(blobs_you , key = lambda b:b.pixels())
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#Bx_R,By_R,Bwidth_R,Bwheight_R = largest_blobs_you[:4]
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#arc_R=Bwidth_R*Bwheight_R
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if is_debug:
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#print('blobs_baise*****')
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img.draw_rectangle((0, 0, 80, 240), color=(255))
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#img.draw_rectangle((0, 190, 180, 50), color=(255))
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#state_crossing = True #线上为白色准备跨越
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#img.draw_rectangle((wx,wy,wwidth, wwheight), color=(255)) #标注
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arc = wwidth * wwheight
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if arc >= 11000:
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print("*********进入循环第2步*******")
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#UsartSend(data_format_wrapper(0, 1, 0))
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#img.draw_rectangle((wx,wy,wwidth, wwheight), color=(255))#左侧区域
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if len(blobs_dixing) != 0:
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print("*********进入循环第3步*******")
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largest_dixing = max(blobs_dixing , key = lambda b:b.pixels())
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wx,wy,wwidth,wwheight = largest_dixing[:4]
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#state_crossing = True
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#img.draw_rectangle((wx,wy,wwidth, wwheight), color=(255))
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arc = wwidth * wwheight
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if arc >= 11000:
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#UsartSend(data_format_wrapper(0, 1, 0))
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#img.draw_rectangle((wx,wy,wwidth, wwheight), color=(255))#右侧区域
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print('kapian') #首先中部区域识别到白色进入判断地形还是卡片，接着判断下部，如果为白色判断为卡片。
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UsartSend(data_format_wrapper(0, 1, 0))#地形停止命令
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if len(blobs_zuo) != 0 and len(blobs_you) != 0:
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print("ka十字路口")
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UsartSend(data_format_wrapper(1, 1, 0))#地形停止命令
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else:
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print('dixing')
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print(roi_blobs_result) #返回的是黑色色块，各区域中心位置
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UsartSend(data_format_wrapper(0, 1, 0))#地形停止命令
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return roi_blobs_result #返回的是黑色色块，各区域中心位置
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def state_deflection_angle(roi_blobs_result):
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'''
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说明：偏转状态值返回
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'''
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# ROI区域权重值
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#ROIS_WEIGHT = [0, 1, 0, 1]
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ROIS_WEIGHT = [1, 0, 0, 1] # ROIS对白色权重的数组
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state_crossing = False
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deflection_angle = 0 # 偏转角
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down_center = 0 # 中下值
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center_num = 0 # 中间值
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# 偏转值计算，ROI中心区域X值
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centroid_sum = roi_blobs_result['up']['cx']*ROIS_WEIGHT[0] + roi_blobs_result['middle_up']['cx']*ROIS_WEIGHT[1] \
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+ roi_blobs_result['middle_down']['cx']*ROIS_WEIGHT[2] + roi_blobs_result['down']['cx']*ROIS_WEIGHT[3]
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if roi_blobs_result['up']['blob_flag']:
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center_num += ROIS_WEIGHT[0]
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if roi_blobs_result['middle_up']['blob_flag']:
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center_num += ROIS_WEIGHT[1]
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if roi_blobs_result['middle_down']['blob_flag']:
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center_num += ROIS_WEIGHT[2]
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if roi_blobs_result['down']['blob_flag']:
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center_num += ROIS_WEIGHT[3]
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center_pos = centroid_sum / (ROIS_WEIGHT[0]+ROIS_WEIGHT[1]+ROIS_WEIGHT[2]+ROIS_WEIGHT[3])
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deflection_angle = (IMG_WIDTH/2)- center_pos
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#判断两侧ROI区域检测到黑色线
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if roi_blobs_result['left']['blob_flag'] and roi_blobs_result['right']['blob_flag']:
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# 判断两侧ROI区域检测到黑色线处于图像下方1/3处
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if roi_blobs_result['left']['cy'] <= ((IMG_HEIGHT/3)) or roi_blobs_result['right']['cy'] <= ((IMG_HEIGHT/3)):
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# 当最下方ROI区域的黑线宽度大于140像素（检测到路口）
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if roi_blobs_result['down']['w'] > 140:
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down_center=1#自行修改处 判断识别到十字路口
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print("输出了十字路口标识")
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if roi_blobs_result['left']['blob_flag'] and roi_blobs_result['right']['blob_flag']:
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# 判断两侧ROI区域检测到黑色线处于图像下方1/3处
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if roi_blobs_result['left']['cy'] <= ((IMG_HEIGHT/3)) or roi_blobs_result['right']['cy'] <= ((IMG_HEIGHT/3)):
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# 当最下方ROI区域的黑线宽度大于140像素（检测到路口）
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if roi_blobs_result['down']['w'] > 140:
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0
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return down_center, state_crossing, deflection_angle
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#--------------直线与路口检测部分 END -------------------
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#--------------二维码识别部分 START -------------------
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def QR_Check(img):
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'''
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说明：二维码函数
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'''
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hld = 0x01
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QR_rioRed =(28, 43, 3, 29, 6, 15)
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QR_rioGreen = (23, 37, -21, -13, 7, 20)
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QR_rioBlue = (8, 31, 3, 15, -36, -22)
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res = img.find_qrcodes() # 寻找二维码
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if len(res) > 0:
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# 在图片和终端显示二维码信息
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#img.draw_rectangle(res[0].rect())
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red_QR = img.find_blobs([QR_rioRed], rio=res[0].rect(), area_threshold=5000, merge = True)
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green_QR = img.find_blobs([QR_rioGreen], rio=res[0].rect(), area_threshold=5000, merge = True)
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blue_QR = img.find_blobs([QR_rioBlue], rio=res[0].rect(), area_threshold=5000, merge = True)
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#img.draw_string(2,2, res[0].payload(), color=(0,128,0), scale=2)
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if ((len(red_QR) != 0) and (120 <= (res[0].x() + res[0].w()/2) <=200) and (60 <= (res[0].y() + res[0].h()/2) <=180)):
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x1 = red_QR[0][0]
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y1 = red_QR[0][1]
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w1 = red_QR[0][2]
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h1 = red_QR[0][3]
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img.draw_rectangle(res[0].rect())
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print(res[0].payload())
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print("红色")
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hld = 0x01
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elif ((len(green_QR) != 0) and (120 <= (res[0].x() + res[0].w()/2) <=200) and (60 <= (res[0].y() + res[0].h()/2) <=180)):
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x1 = green_QR[0][0]
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y1 = green_QR[0][1]
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w1 = green_QR[0][2]
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h1 = green_QR[0][3]
|
||
img.draw_rectangle(res[0].rect())
|
||
print(res[0].payload())
|
||
print("绿色")
|
||
hld = 0x02
|
||
elif ((len(blue_QR) != 0) and (120 <= (res[0].x() + res[0].w()/2) <=200) and (60 <= (res[0].y() + res[0].h()/2) <=180)):
|
||
x1 = blue_QR[0][0]
|
||
y1 = blue_QR[0][1]
|
||
w1 = blue_QR[0][2]
|
||
h1 = blue_QR[0][3]
|
||
img.draw_rectangle(res[0].rect())
|
||
print(res[0].payload())
|
||
print("蓝色")
|
||
hld = 0x03
|
||
elif ((120 <= (res[0].x() + res[0].w()/2) <=200) and (60 <= (res[0].y() + res[0].h()/2) <=180)):
|
||
img.draw_rectangle(res[0].rect())
|
||
print(res[0].payload())
|
||
print("黑色")
|
||
hld = 0x04
|
||
#串口发送二维码信息
|
||
uart.write(bytes([0x55]))
|
||
uart.write(bytes([0x92]))
|
||
uart.write(bytes([0x01]))
|
||
uart.write(bytes([hld]))
|
||
uart.write(bytes([len(res[0].payload())]))
|
||
for qrdata in res[0].payload():
|
||
uart.write(bytes([ord(qrdata)]))
|
||
uart.write(bytes([0xbb]))
|
||
|
||
#--------------二维码识别部分 END -------------------
|
||
|
||
#-----------------交通灯识别 START-------------------#
|
||
###################################################################################################
|
||
# 返回值
|
||
# 1、红灯（蒙的答案选项）
|
||
# 2、绿灯
|
||
# 3、黄灯
|
||
#
|
||
# 需要完善部分：
|
||
# 1、过滤掉范围过小和过大部分--》提高识别效率
|
||
# 2、通信协议
|
||
###################################################################################################
|
||
|
||
def tick(timer):
|
||
global times,isCut
|
||
#print(times)
|
||
if(times == 4):
|
||
isCut = False
|
||
tim.deinit() #tim对象反初始化
|
||
times = 0
|
||
else:
|
||
times+=1;
|
||
|
||
def drawTrafficLight(isDraw): #识别红绿灯*******************
|
||
red = (49, 68, 40, 65, 23, 69) #红色阈值
|
||
green = (66, 93, -54, -32, 36, 52) #绿色阈值
|
||
yellow = (62, 98, -17, 22, 41, 68) #黄色阈值
|
||
hld = 0x01 #蒙答案
|
||
try:
|
||
TrafficLight_rio = (240, 0, 80, 240)
|
||
img.draw_rectangle(TrafficLight_rio, color=(255))
|
||
#tim.callback(tick) #回调函数的形参是用户函数或者匿名函数都必须有一个位置参数,才可以正常工作（位置参数可能就是一个实例），而且调用时不用些括号
|
||
red_blobs = img.find_blobs([red], rio=TrafficLight_rio,merge=True) #寻找红色色块 合并所有重叠的blod
|
||
green_blobs = img.find_blobs([green], rio=TrafficLight_rio,merge=True)
|
||
yellow_blobs = img.find_blobs([yellow],rio=TrafficLight_rio,merge=True)
|
||
|
||
if (len(red_blobs) != 0):
|
||
x1 = red_blobs[0][0]
|
||
y1 = red_blobs[0][1]
|
||
w1 = red_blobs[0][2]
|
||
h1 = red_blobs[0][3]
|
||
print("红灯")
|
||
if isDraw is True:
|
||
img.draw_rectangle((x1,y1,w1,h1),color=(255,0,0))
|
||
hld = 0x01
|
||
elif (len(green_blobs) != 0):
|
||
x1 = green_blobs[0][0]
|
||
y1 = green_blobs[0][1]
|
||
w1 = green_blobs[0][2]
|
||
h1 = green_blobs[0][3]
|
||
print("绿灯")
|
||
if isDraw is True:
|
||
img.draw_rectangle((x1,y1,w1,h1),color=(0,255,0))
|
||
hld = 0x02
|
||
elif (len(yellow_blobs) != 0):
|
||
x1 = yellow_blobs[0][0]
|
||
y1 = yellow_blobs[0][1]
|
||
w1 = yellow_blobs[0][2]
|
||
h1 = yellow_blobs[0][3]
|
||
print("黄灯")
|
||
if isDraw is True:
|
||
img.draw_rectangle((x1,y1,w1,h1),color=(255,255,255))
|
||
hld = 0x03
|
||
|
||
# 串口发送交通灯信息
|
||
uart.write(bytes([0x55]))
|
||
uart.write(bytes([0x92]))
|
||
uart.write(bytes([0x03]))
|
||
uart.write(bytes([hld]))
|
||
uart.write(bytes([0x03]))
|
||
uart.write(bytes([0x03]))
|
||
uart.write(bytes([0x03]))
|
||
uart.write(bytes([0xbb]))
|
||
except Exception as e:
|
||
print("识别红绿灯异常",e)
|
||
# 串口发送交通灯信息
|
||
uart.write(bytes([0x55]))
|
||
uart.write(bytes([0x92]))
|
||
uart.write(bytes([0x03]))
|
||
uart.write(bytes([hld]))
|
||
uart.write(bytes([0x03]))
|
||
uart.write(bytes([0x03]))
|
||
uart.write(bytes([0x03]))
|
||
uart.write(bytes([0xbb]))
|
||
|
||
|
||
#======================交通灯识别 END===========================#
|
||
|
||
|
||
#---------------------MAIN-----------------------
|
||
last_cx = 0
|
||
last_cy = 0
|
||
#将蓝灯引脚IO12配置到GPIO0，K210引脚支持任意配置
|
||
fm.register(12, fm.fpioa.GPIO0)
|
||
LED_B = GPIO(GPIO.GPIO0, GPIO.OUT) #构建LED对象
|
||
#按键KEY用于清屏
|
||
fm.register(16, fm.fpioa.GPIO1, force=True)
|
||
btn_debug = GPIO(GPIO.GPIO1, GPIO.IN)
|
||
x_num = 0
|
||
while True:
|
||
LED_B.value(0) #点亮LED
|
||
# 串口数据接收处理
|
||
data = uart.read(8)
|
||
if data is not None:
|
||
print(data)
|
||
print(len(data))
|
||
print(binascii.hexlify(data).decode('utf_8'))
|
||
if(len(data) >= 8):
|
||
if((data[1] == 0x02)&(data[7] == 0xBB)):
|
||
# 巡线与控制舵机
|
||
if(data[2] == 0x91):
|
||
if(data[3] == 0x01): # 启动识别
|
||
Servo(-75)
|
||
sensor.set_pixformat(sensor.GRAYSCALE) # 设置像素格式为灰色
|
||
print("巡线")
|
||
print("开始识别")
|
||
Flag_track = True
|
||
tim1.start()
|
||
if(data[3] == 0x02):
|
||
print("巡线")
|
||
print("停止识别")
|
||
Flag_track = False
|
||
tim1.stop() # 停止定时器
|
||
if(data[3] == 0x03): # 舵机调整
|
||
angle = data[5]
|
||
# 判断舵机控制方向
|
||
if data[4] == ord('-'):
|
||
# 限制舵机角度，防止过大损坏舵机
|
||
if angle > 80:
|
||
angle = 80
|
||
angle = -angle
|
||
elif data[4] == ord('+'):
|
||
# 限制舵机角度，防止过大损坏舵机
|
||
if angle > 35:
|
||
angle = 35
|
||
angle = angle
|
||
Servo(angle) # 控制舵机
|
||
# 二维码识别
|
||
if(data[2] == 0x92):
|
||
print("识别二维码")
|
||
sensor.set_pixformat(sensor.RGB565) # 设置像素格式为彩色 RGB565
|
||
if(data[3] == 0x01): #启动识别
|
||
print("开始识别")
|
||
tim1.start()
|
||
QR_Flag = True
|
||
if(data[3] == 0x02):
|
||
print("停止识别")
|
||
tim1.stop() # 停止定时器
|
||
QR_Flag = False
|
||
if(data[3] == 0x03):
|
||
print("开始识别")
|
||
tim1.start()
|
||
JTD = True
|
||
if(data[3] == 0x04):
|
||
print("停止识别")
|
||
tim1.stop()
|
||
JTD = False
|
||
|
||
# 拍摄图片
|
||
img = sensor.snapshot()
|
||
# 去除图像畸变
|
||
img.lens_corr(DISTORTION_FACTOR)
|
||
# 二维码识别
|
||
#QR_Flag = True
|
||
if QR_Flag:
|
||
QR_Check(img)
|
||
#JTD = 1
|
||
if JTD:
|
||
#Servo(10)
|
||
drawTrafficLight(img)
|
||
## 巡线
|
||
if is_debug:
|
||
Flag_track=1
|
||
Servo(-75)
|
||
if Flag_track:
|
||
roi_blobs_result = find_blobs_in_rois(img)
|
||
down_center, state_crossing, deflection_angle = state_deflection_angle(roi_blobs_result)
|
||
if is_need_send_data:
|
||
UsartSend(data_format_wrapper(down_center, state_crossing, deflection_angle))
|
||
print("下发指令")
|
||
print(data_format_wrapper(down_center, state_crossing, deflection_angle))
|
||
#time.sleep_ms(10)
|
||
#is_need_send_data = False
|
||
# 在LCD上显示
|
||
lcd.display(img)
|
||
#按键KEY按下。开启或关闭调试，并退出所有任务。
|
||
if btn_debug.value() == 0:
|
||
Flag_track = not Flag_track # 巡线任务退出
|
||
QR_Flag = not QR_Flag # 二维码任务退出
|
||
JTD = not JTD # 交通灯任务退出
|
||
is_debug = not is_debug # 调试标志位取
|
||
|