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12345678.py
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import sensor, image, time, os, tf, math,machine
from pyb import UART
import json
from pyb import LED
import lcd
from machine import I2C
from vl53l1x import VL53L1X
import time
sensor.reset() # Reset and initialize the sensor.
sensor.set_pixformat(sensor.RGB565) # Set pixel format to RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.QVGA) # Set frame size to QVGA (320x240)
sensor.set_windowing((320, 240)) # Set 240x240 window.
sensor.set_auto_whitebal(False, rgb_gain_db=(65.2256,60.2071,61.9736))
sensor.set_auto_exposure(False, 40000)#修改曝光度
sensor.set_auto_gain(False, 22)
#sensor.set_auto_whitebal(False)
#sensor.set_auto_exposure(False)
#sensor.set_auto_gain(False)
sensor.skip_frames(time=2000) # Let the camera adjust.
clock = time.clock()
red_lab=(0,100,40,70,20,60)#红色线条
white_lab=(90,100,-5,5,-5,5)#白色数字
black_lab=(15,60,-20,10,-10,20)#黑色终点/数字
#串口通信
uart = UART(3, 115200)
uart.init(115200, bits=8, parity=None, stop=1) #8位数据位，无校验位，1位停止位
#返回最大色块（也就是返回最近的垃圾）
def find_max(blobs):
max_size=0
for blob in blobs:
if blob[2]*blob[3] > max_size:
max_blob=blob
max_size = blob[2]*blob[3]
return max_blob
#参数
area=[0,0,320,240];area_1=[0,0,320,240];area_2=[0,0,320,240]
area_3=[0,0,320,240];area_3_1=[0,0,320,240];area_4=[0,0,320,240]
#数字识别
def num(wh,di_pix,ding_pix,zhong_3,zhong_3_xia,zhong_6):
if wh<0.6:return'1'#1
else:#非1
if di_pix>200:return'2'
else:#非1，2
if di_pix<80:#4和7
if ding_pix<80:return'4'#4
else:return'7'
else:#非1，4，7(3,5,6,8)
if zhong_3==0:return'3'
else:#非1，4，7，3（5，6，8）
if zhong_3_xia==0:return'5'
else:#非1，4，7，3，5（6，8）
if zhong_6==0:return'6'
else:return'8'
#主循环
while(1):
clock.tick()
#sensor.set_windowing((0,0,320,240))
img = sensor.snapshot()
LED(2).on()
#数字识别
number_areas = img.find_blobs([white_lab], pixels_threshold=20, area_threshold=20)
red_lines = img.find_blobs([red_lab], pixels_threshold=20, area_threshold=20)
black_numbers = img.find_blobs([black_lab], pixels_threshold=200, area_threshold=200,merge=True)
if black_numbers:#如果有黑色色块
for i in black_numbers:#框出所有的黑色色块
#参数重置
wh=0;di_pix=0;ding_pix=0;zhong_3=0;zhong_3_xia=0;zhong_6=0
#1的识别
wh=i.w()/i.h()
area[0]=i.x();area[1]=i.y()+int(i.h()/2);area[2]=i.w();area[3]=int(i.h()/2);
#底边参数
area_2[0]=i.x();area_2[1]=i.y()+i.h()-5;area_2[2]=i.w();area_2[3]=5;
blob_2s = img.find_blobs([black_lab],roi=area_2, pixels_threshold=20, area_threshold=20,merge=True)
if blob_2s:
blob_2=find_max(blob_2s);
img.draw_rectangle(blob_2.rect(),color=(225,0,0),thickness=2)
di_pix=blob_2.area()
#顶边参数
area_1[0]=i.x();area_1[1]=i.y();area_1[2]=i.w();area_1[3]=5;
blob_1s = img.find_blobs([black_lab],roi=area_1, pixels_threshold=20, area_threshold=20,merge=True)
if blob_1s:
blob_1=find_max(blob_1s);
img.draw_rectangle(blob_1.rect(),color=(225,0,0),thickness=2)
ding_pix=blob_1.area()
#3的左中间
area_3[0]=i.x();area_3[1]=i.y()+int(i.h()/3);area_3[2]=int(i.w()/3);area_3[3]=int(i.h()/3);
blob_3s = img.find_blobs([black_lab],roi=area_3, pixels_threshold=20, area_threshold=20,merge=True)
if blob_3s:
blob_3=find_max(blob_3s);
img.draw_rectangle(blob_3.rect(),color=(0,225,0),thickness=2)
zhong_3=blob_3.area()
#3中间的下面
area_3_1[0]=blob_3.x();area_3_1[1]=blob_3.y()+blob_3.h();area_3_1[2]=blob_3.w();area_3_1[3]=5;
blob_3_1s = img.find_blobs([black_lab],roi=area_3_1, pixels_threshold=20, area_threshold=20,merge=True)
if blob_3_1s:
blob_3_1=find_max(blob_3_1s);
img.draw_rectangle(blob_3_1.rect(),color=(0,0,225),thickness=2)
zhong_3_xia=blob_3_1.area()
#6的中间
area_4[0]=i.x()+int(i.w()/3);area_4[1]=i.y()+int(i.h()*2/9);area_4[2]=int(i.w()*5/7);area_4[3]=5;
blob_4s = img.find_blobs([black_lab],roi=area_4, pixels_threshold=20, area_threshold=20,merge=True)
if blob_4s:
blob_4=find_max(blob_4s);
img.draw_rectangle(blob_4.rect(),color=(255,0,0),thickness=2)
zhong_6=blob_4.area()
#打印识别结果
print(num(wh,di_pix,ding_pix,zhong_3,zhong_3_xia,zhong_6))
#框出每一个数字
img.draw_rectangle(i.rect(),color=(0,0,0),thickness=2)
#print('8--------------------------')
print('长宽比',wh)
#识别参数打印
print(wh,di_pix,ding_pix,zhong_3,zhong_3_xia,zhong_6)