# Untitled - By: 15622 - 周四 10月 6 2022
# Single Color RGB565 Blob Tracking Example
# This example shows off single color RGB565 tracking using the OpenMV Cam.
import sensor, image, time, math
import sensor, image, time
from pyb import UART                #加入
import json                    #载入库  加入
import pyb
import math
def modified_data(data):
   data = int(data)
   str_data = ''
   if data < 10:
       str_data = str_data + '000' + str(data)
   elif data >= 10 and data < 100:
       str_data = str_data + '00' + str(data)
   elif data >=100 and data <1000:
       str_data = str_data + '0' + str(data)
   else:
       str_data = str_data + str(data)
   return str_data.encode('utf-8')
kernel_size = 1 # kernel width= (size*2)+1, kernel height = (size*2)+1,默认不需改
kernel = [-2, -1,  0, \
          -1,  1,  1, \
           0,  1,  2]
threshold_index = 0 # 0 for red, 1 for green, 2 for blue

# Color Tracking Thresholds (L Min, L Max, A Min, A Max, B Min, B Max)
# The below thresholds track in general red/green/blue things. You may wish to tune them...
thresholds = [(100, 8, -13, -57, 25, 127), # generic_red_thresholds
              ] # generic_blue_thresholds
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time = 300)
uart = UART(3, 115200)
sensor.set_auto_gain(False) # must be turned off for color tracking
sensor.set_auto_whitebal(False) # must be turned off for color tracking
clock = time.clock()
sj=0
while(True):
    clock.tick()
    if uart.any():
        sj = uart.read(1)
        sj=int(sj)
# Only blobs that with more pixels than "pixel_threshold" and more area than "area_threshold" are
# returned by "find_blobs" below. Change "pixels_threshold" and "area_threshold" if you change the
# camera resolution. "merge=True" merges all overlapping blobs in the image.

        while(sj==1):
            img = sensor.snapshot().lens_corr(1.8 )       #镜头畸变矫正
            img.morph(kernel_size, kernel)        #核滤波
            img.laplacian(1, sharpen=True)        #锐化
            for c in img.find_circles(threshold = 6001, x_margin = 10, y_margin = 10, r_margin = 10,
            r_min = 15, r_max = 100, r_step = 2):
          #只需修改threshold和r_min，增大threshold可以提高准确性，减小可以提高灵敏度（太小会乱框）
           # 修改r_min值使其只识别大圆，不识别小圆
          #if c.r()>15 and c.r()<80:
                area = (c.x()-c.r(), c.y()-c.r(), 2*c.r(), 2*c.r())
              #area为识别到的圆的区域，即圆的外接矩形框
                img.draw_rectangle(area, color = (255,255,255)) #将圆用白色的矩形框出来
                img.draw_cross(c.x(),c.y())      #画十字
                mj=4*c.r()*c.r()        #矩形框面积
                xzb = modified_data(c.x())
                yzb = modified_data(c.y())
                mjzb = modified_data(mj)
                uart.write('st')
                uart.write(xzb)
                uart.write(yzb)
                uart.write(mjzb)                    # 串口发送数据
                print(xzb, yzb,mjzb)

        while(sj==2):
            img = sensor.snapshot()
            for blob in img.find_blobs([thresholds[threshold_index]], pixels_threshold=500, area_threshold=400, merge=True):
        # These values depend on the blob not being circular - otherwise they will be shaky.
                if blob.elongation()>0.5:
                    img.draw_edges(blob.min_corners(), color=(255,0,0))
                    img.draw_cross(blob.cx(), blob.cy())
        # Note - the blob rotation is unique to 0-180 only.
                img.draw_rectangle(blob.rect())
                img.draw_cross(blob.cx(), blob.cy())
                mj=blob.w()*blob.h()
                xzb = modified_data(blob.cx())
                yzb = modified_data(blob.cy())
                mjzb = modified_data(mj)
                uart.write('st')
                uart.write(xzb)
                uart.write(yzb)
                uart.write(mjzb)
                print(xzb, yzb,mjzb)