365 lines
12 KiB
Python
365 lines
12 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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QR_Flag = 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.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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'''
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if 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
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1 if state_crossing else 0,
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get_symbol(deflection_angle), # 偏航角符号
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abs(int(deflection_angle)), # 偏航角
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0xbb]
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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 = [(6, 65)]
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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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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
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global is_debug
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canvas = img.copy()
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roi_blobs_result = {} # 在各个ROI中寻找色块的结果记录
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for roi_direct in ROIS.keys():
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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
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}
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for roi_direct, roi in ROIS.items():
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blobs=canvas.find_blobs(LINE_COLOR_THRESHOLD, roi=roi, merge=True)
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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:
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x,y,width,height = largest_blob[:4]
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roi_blobs_result[roi_direct]['cx'] = largest_blob.cy()
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roi_blobs_result[roi_direct]['cy'] = largest_blob.cx()
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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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img.draw_rectangle((x,y,width, height), 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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return roi_blobs_result
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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 = [1, 1, 1, 1]
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ROIS_WEIGHT = [1, 0, 0, 1]
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state_crossing = False
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deflection_angle = 0
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down_center = 0
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center_num = 0
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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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state_crossing = True
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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():
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'''
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说明：二维码函数
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'''
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global QR_Flag
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if QR_Flag:
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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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img.draw_string(2,2, res[0].payload(), color=(0,128,0), scale=2)
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print(res[0].payload())
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# 串口发送二维码信息
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uart.write(bytes([0x55]))
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uart.write(bytes([0x02]))
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uart.write(bytes([0x92]))
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uart.write(bytes([0x01]))
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uart.write(bytes([len(res[0].payload())]))
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for qrdata in res[0].payload():
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uart.write(bytes([ord(qrdata)]))
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uart.write(bytes([0xbb]))
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#--------------二维码识别部分 END -------------------
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#---------------------MAIN-----------------------
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last_cx = 0
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last_cy = 0
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Flag_track = False
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#将蓝灯引脚IO12配置到GPIO0，K210引脚支持任意配置
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fm.register(12, fm.fpioa.GPIO0)
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LED_B = GPIO(GPIO.GPIO0, GPIO.OUT) #构建LED对象
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#按键KEY用于清屏
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fm.register(16, fm.fpioa.GPIO1, force=True)
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btn_debug = GPIO(GPIO.GPIO1, GPIO.IN)
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x_num = 0
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while True:
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LED_B.value(0) #点亮LED
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# 串口数据接收处理
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data = uart.read(8)
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if data is not None:
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print(data)
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print(len(data))
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print(binascii.hexlify(data).decode('utf_8'))
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if(len(data) >= 8):
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if((data[1] == 0x02)&(data[7] == 0xBB)):
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# 巡线与控制舵机
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if(data[2] == 0x91):
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if(data[3] == 0x01): # 启动识别
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print("巡线")
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print("开始识别")
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Flag_track = True
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tim1.start()
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if(data[3] == 0x02):
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print("巡线")
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print("停止识别")
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Flag_track = False
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tim1.stop() # 停止定时器
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if(data[3] == 0x03): # 舵机调整
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angle = data[5]
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# 判断舵机控制方向
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if data[4] == ord('-'):
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# 限制舵机角度，防止过大损坏舵机
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if angle > 80:
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angle = 80
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angle = -angle
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elif data[4] == ord('+'):
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# 限制舵机角度，防止过大损坏舵机
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if angle > 35:
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angle = 35
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angle = angle
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Servo(angle) # 控制舵机
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time.sleep(1) # 等待舵机角度更新
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# 二维码识别
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if(data[2] == 0x92):
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print("识别二维码")
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# Servo(-15) # 向下-15度
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# time.sleep(1)
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if(data[3] == 0x01): #启动识别
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print("开始识别")
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tim1.start()
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QR_Flag = True
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if(data[3] == 0x02):
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print("停止识别")
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tim1.stop() # 停止定时器
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QR_Flag = False
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# 拍摄图片
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img = sensor.snapshot()
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# 去除图像畸变
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#img.lens_corr(DISTORTION_FACTOR)
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# 二维码识别
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QR_Check()
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# 巡线
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if Flag_track:
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roi_blobs_result = find_blobs_in_rois(img)
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down_center, state_crossing, deflection_angle = state_deflection_angle(roi_blobs_result)
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if is_need_send_data:
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UsartSend(data_format_wrapper(down_center, state_crossing, deflection_angle))
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#time.sleep_ms(10)
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#is_need_send_data = False
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# 在LCD上显示
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lcd.display(img)
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#按键KEY按下。开启或关闭调试，并退出所有任务。
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if btn_debug.value() == 0:
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Flag_track = not Flag_track # 巡线任务退出
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QR_Flag = not QR_Flag # 二维码任务退出
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is_debug = not is_debug # 调试标志位取
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