import sensor, image, time, os, tf, math, uos, gc
import json
from pyb import UART
from pyb import Pin, Timer
light = Timer(2, freq=50000).channel(1, Timer.PWM, pin=Pin("P6"))    #灯光基础参数引脚，频率，pwm（不用改）
light.pulse_width_percent(10)                                        #亮度
sensor.reset()                                 #复位和初始化传感器
sensor.set_pixformat(sensor.RGB565)            #设置像素格式为RGB565(或GRAYSCALE)
sensor.set_framesize(sensor.QVGA)              #设置帧大小为QVGA (320x240)
sensor.set_windowing((320, 240))               #设置320x240窗口
sensor.skip_frames(time=2000)                  #让相机调整一下。
uart = UART(3, 115200)                         #串口3，波特率115200
net = None
labels = None
min_confidence = 0.5                           #最小置信度（区分识别物与背景）！！！不知道别改
#以下为空定义，防止报错
mjzb=''
xzb=''
yzb=''
rect_area=0
center_x=0
center_y=0
blobs=0
str1="A雄"
str2="B雄"
str3="A雌"
str4="B雌"

left_roi = [0,0,320,240]

try:#加载模型，在堆上分配模型文件，如果加载后我们至少有64K的空闲空间
    net = tf.load("trained.tflite", load_to_fb=uos.stat('trained.tflite')[6] > (gc.mem_free() - (64*1024)))
except Exception as e:
    raise Exception('Failed to load "trained.tflite", did you copy the .tflite and labels.txt file onto the mass-storage device? (' + str(e) + ')')
try:
    labels = [line.rstrip('\n') for line in open("labels.txt")]
except Exception as e:
    raise Exception('Failed to load "labels.txt", did you copy the .tflite and labels.txt file onto the mass-storage device? (' + str(e) + ')')
yellow_thresholdA = (76, 99, -25, 83, 35, 111)     #色块追踪颜色阈值，可根据环境光不同修改，参数在tools-machine vision-threshold editor
#yellow_thresholdB = (34,85,-48,77,-8,87)
yellow_thresholdC = (100, 61, -105, 127, 35, 88)
white_threshold = (28, 33, -89, 127, -128, -58)   #识别方框的颜色阈值
pixel_size_mm = 0.1 / 25                          #0.1mm\25像素点
colors = [
          (255,   0,   0),#RED
          (  0, 255,   0),#GREEN
          (255, 255,   0),#YELLOW
          (  0,   0, 255),#BLUE
          (255,   0, 255),#PINK
          (  0, 255, 255),#CYAN
          (255, 255, 255),#WHITE
]                                                 #如果你同时检测到7种以上的类，添加更多的颜色。
clock = time.clock()
sj=9
def modified_data(data):                          #整型函数，将返回主控板的面积整型为四位数（根据手眼协调函数修改）
   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')                #返回编码通用转换格式


while(True):
    clock.tick()
    img = sensor.snapshot()#.lens_corr(1.8)
    for i, detection_list in enumerate(net.detect(img, thresholds=[(math.ceil(min_confidence * 255), 255)])):
        if (i == 0): continue
        if (len(detection_list) == 0): continue
        #print(labels[i])
        for d in detection_list:
            [x, y, w, h] = d.rect()
            center_x = math.floor(x + (w / 2))
            center_y = math.floor(y + (h / 2))
            xzb = modified_data(center_x)
            yzb = modified_data(center_y)
            img.draw_circle((center_x, center_y, 8), color=(0,0,0), thickness=2)

            print('识别到%s' % labels[i])
            if labels[i]== 'B雄' or labels[i]== 'A雄' :
                print('这是雄花')
                rect_area=0
                break
            elif labels[i]== 'A雌' or labels[i]== 'B雌' :
                blobs = img.find_blobs([yellow_thresholdA,yellow_thresholdC])
                if blobs:
                    largest_blob = max(blobs, key = lambda b: b.pixels())
                    rect = largest_blob.rect()
                    img.draw_rectangle(rect, color = (0,0,255))
                    white_region = img.crop(rect).find_blobs([white_threshold], pixels_threshold=100)
                    if white_region:
                        largest_white_region = max(white_region, key = lambda b: b.pixels())
                        rect_area = largest_white_region.pixels()
                        img.draw_rectangle(largest_white_region.rect(), color = (0, 0, 255))
                        mjzb = modified_data(rect_area)
                        print('*******')
                        uart.write('st')
                        uart.write(xzb)
                        uart.write(yzb)
                        uart.write(mjzb)
                        print('x==%d\ty==%d\tmj==%d' % (center_x, center_y, 10*rect_area))
                        print(xzb, yzb, mjzb)
                        print('这是%s\n' % labels[i])
                        time.sleep(0.15)