# Template Matching Example - Normalized Cross Correlation (NCC)
#
# This example shows off how to use the NCC feature of your OpenMV Cam to match
# image patches to parts of an image... expect for extremely controlled enviorments
# NCC is not all to useful.
#
# WARNING: NCC supports needs to be reworked! As of right now this feature needs
# a lot of work to be made into somethin useful. This script will reamin to show
# that the functionality exists, but, in its current state is inadequate.
import time, sensor, image
from image import SEARCH_EX, SEARCH_DS
#从imgae模块引入SEARCH_EX和SEARCH_DS。使用from import仅仅引入SEARCH_EX,
#SEARCH_DS两个需要的部分，而不把image模块全部引入。
# Reset sensor
sensor.reset()
# Set sensor settings
sensor.set_contrast(1)
sensor.set_gainceiling(16)
# Max resolution for template matching with SEARCH_EX is QQVGA
sensor.set_framesize(sensor.QQVGA)
# You can set windowing to reduce the search image.
#sensor.set_windowing(((640-80)//2, (480-60)//2, 80, 60))
sensor.set_pixformat(sensor.GRAYSCALE)
# Load template.
# Template should be a small (eg. 32x32 pixels) grayscale image.
template01 = image.Image("/1.pgm")
template02 = image.Image("/2.pgm")
template03 = image.Image("/3.pgm")
template04 = image.Image("/4.pgm")
template05 = image.Image("/5.pgm")
template06 = image.Image("/6.pgm")
template07 = image.Image("/7.pgm")
template08 = image.Image("/8.pgm")
template3L = image.Image("/3L.pgm")
template3LL = image.Image("/3LL.pgm")
template3R = image.Image("/3R.pgm")
template3RR = image.Image("/3RR.pgm")
template4L = image.Image("/4L.pgm")
template4LL = image.Image("/4LL.pgm")
template4R = image.Image("/4R.pgm")
template4RR = image.Image("/4RR.pgm")
template5L = image.Image("/5L.pgm")
template5LL = image.Image("/5LL.pgm")
template5R = image.Image("/5R.pgm")
template5RR = image.Image("/5RR.pgm")
template6L = image.Image("/6L.pgm")
template6LL = image.Image("/6LL.pgm")
template6R = image.Image("/6R.pgm")
template6RR = image.Image("/6RR.pgm")
template7L = image.Image("/7L.pgm")
template7LL = image.Image("/7LL.pgm")
template7R = image.Image("/7R.pgm")
template7RR = image.Image("/7RR.pgm")
template8L = image.Image("/8L.pgm")
template8LL = image.Image("/8LL.pgm")
template8R = image.Image("/8R.pgm")
template8RR = image.Image("/8RR.pgm")
#加载模板图片
uart = pyb.UART(3, 9600, timeout_char = 1000) #定义串口3变量
blue_led = LED(3)
#通过接收stm32F103传过来数据，来决定使用以下哪种模式
# FindTask： 1.轮询1~8，直至识别到。 2.根据f103给的值，单纯识别那个数
Find_Task = 1
Target_Num = 0
find_flag = 0
x = 0
blue_led = LED(3)
data = [0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00,0x00]
########串口接收数据函数处理#########
def UartReceiveDate(): #这个函数不能运行太快，否则会导致串口读取太快导致出错
global Find_Task
global Target_Num
global x
global data
data[0] = uart.readchar()
data[1] = uart.readchar()
data[2] = uart.readchar()
data[3] = uart.readchar()
data[4] = uart.readchar()
data[5] = uart.readchar()
data[6] = uart.readchar()
data[7] = uart.readchar()
if data[x] == 42 and data[x+3] == 38 and x < 5:
Find_Task = data[x+1]
Target_Num = data[x+2]
Find_Task = Find_Task - 48
Target_Num = Target_Num - 48
print(Find_Task, Target_Num)
x = 0
elif x >= 5: x = 0
x+=1
blue_led.toggle
########串口接收数据函数处理完毕#############
# 当被调用时，我们将返回timer对象
# 注意:在回调中不允许分配内存的函数 #openmv会自动把接收到的数据放在缓冲区里
'''def tick(timer):
blue_led.toggle()
tim = Timer(2, freq=5) # 使用定时器2创建定时器对象-以1Hz触发
tim.callback(tick) ''' # 将回调设置为tick函数
#最初加载匹配
def FirstFindTemplate(template):
R = img.find_template(template, 0.5, step=4, roi=(26, 7, 124, 96), search=SEARCH_EX) #只检测中间的
return R
def FirstFindedNum(R, Finded_Num): #第一个参数是模板匹配的对象，第二个是它所代表的数字
global Find_Task
global find_flag
img.draw_rectangle(R, color=(225, 0, 0))
#本来中值是80的，但返回值是框边缘，所以减去15就好 小于65是在左边，大于65是在右边
LoR = 0
find_flag = 1
Num = Finded_Num
FH = bytearray(0x2C,0x12,Num, LoR, find_flag, Find_Task,0x5B)
uart.write(FH)
print("目标病房号：", Num)
###### FindTask == 1 时使用
#模板匹配
def FindTemplate(template):
R = img.find_template(template, 0.5, step=1, roi=(39, 32, 92, ), search=SEARCH_EX)
return R
def FindedNum(R, Finded_Num): #第一个参数是模板匹配的对象，第二个是它所代表的数字
global Find_Task
global find_flag
img.draw_rectangle(R, color=(225, 0, 0))
#本来中值是80的，但返回值是框边缘，所以减去15就好 小于65是在左边，大于65是在右边
if R[0] >= 65:
LoR = 2 #2是右
elif 0< R[0] <65:
LoR = 1 #1是左
find_flag = 1
Num = Finded_Num
FH = bytearray([0x2C,0x12,Num, LoR, find_flag, Find_Task,0x5B])
uart.write(FH)
print("识别到的数字是：", Num, "此数字所在方位：", LoR) #打印模板名字
clock = time.clock()
# Run template matching
while (True):
clock.tick()
img = sensor.snapshot()
UartReceiveDate()
# find_template(template, threshold, [roi, step, search])
# ROI: The region of interest tuple (x, y, w, h).
# Step: The loop step used (y+=step, x+=step) use a bigger step to make it faster.
# Search is either image.SEARCH_EX for exhaustive search or image.SEARCH_DS for diamond search
#
# Note1: ROI has to be smaller than the image and bigger than the template.
# Note2: In diamond search, step and ROI are both ignored.
if Find_Task == 1:
#进行模板匹配
r01 = FirstFindTemplate(template01)
r02 = FirstFindTemplate(template02)
r03 = FirstFindTemplate(template03)
r04 = FirstFindTemplate(template04)
r05 = FirstFindTemplate(template05)
r06 = FirstFindTemplate(template06)
r07 = FirstFindTemplate(template07)
r08 = FirstFindTemplate(template08)
#判断哪个模板匹配成功，并将成功匹配的相应数据发送给主控
if r01:
FirstFindedNum(r01, 1)
elif r02:
FirstFindedNum(r02,2)
elif r03:
FirstFindedNum(r03,3)
elif r04:
FirstFindedNum(r04,4)
elif r05:
FirstFindedNum(r05,5)
elif r06:
FirstFindedNum(r06,6)
elif r07:
FirstFindedNum(r07,7)
elif r08:
FirstFindedNum(r08,8)
else:
FH = bytearray([0x2C,0x12,0x00, 0x00, 0x00, 0x00,0x5B])
uart.write(FH)
elif Find_Task == 2:
#判断需要数字3~8中断哪一个
if Target_Num == 3:
#进行模板匹配 //这里每个数字至少给3个模板， 但给五六个其实也行
r3L = FindTemplate(template3L)
r3LL = FindTemplate(template3LL)
r3R = FindTemplate(template3R)
r3RR = FindTemplate(template3RR)
#判断哪个模板匹配成功，并将成功匹配的相应数据发送给主控
if r3L:
FindedNum(r3L, 3)
elif r3LL:
FindedNum(r3LL, 3)
elif r3R:
FindedNum(r3R, 3)
elif r3RR:
FindedNum(r3RR, 3)
else:
FH = bytearray([0x2C,0x12, 0x00, 0x00, find_flag, Find_Task,0x5B])
uart.write(FH)
elif Target_Num == 4:
#进行模板匹配 //这里每个数字至少给3个模板， 但给五六个其实也行
r4L = FindTemplate(template4L)
r4LL = FindTemplate(template4LL)
r4R = FindTemplate(template4R)
r4RR = FindTemplate(template4RR)
#判断哪个模板匹配成功，并将成功匹配的相应数据发送给主控
if r4L:
FindedNum(r4L, 4)
elif r4LL:
FindedNum(r4LL, 4)
elif r4R:
FindedNum(r4R, 4)
elif r4RR:
FindedNum(r4RR, 4)
else:
FH = bytearray([0x2C,0x12, 0x00, 0x00, find_flag, Find_Task,0x5B])
uart.write(FH)
elif Target_Num == 5:
#进行模板匹配 //这里每个数字至少给3个模板， 但给五六个其实也行
r5L = FindTemplate(template5L)
r5LL = FindTemplate(template5LL)
r5R = FindTemplate(template5R)
r5RR = FindTemplate(template5RR)
#判断哪个模板匹配成功，并将成功匹配的相应数据发送给主控
if r5L:
FindedNum(r5L, 5)
elif r5LL:
FindedNum(r5LL, 5)
elif r5R:
FindedNum(r5R, 5)
elif r5RR:
FindedNum(r5RR, 5)
else:
FH = bytearray([0x2C,0x12, 0x00, 0x00, find_flag, Find_Task,0x5B])
uart.write(FH)
elif Target_Num == 6:
#进行模板匹配 //这里每个数字至少给3个模板， 但给五六个其实也行
r6L = FindTemplate(template6L)
r6LL = FindTemplate(template6LL)
r6R = FindTemplate(template6R)
r6RR = FindTemplate(template6RR)
#判断哪个模板匹配成功，并将成功匹配的相应数据发送给主控
if r6L:
FindedNum(r6L, 6)
elif r6LL:
FindedNum(r6LL, 6)
elif r6R:
FindedNum(r6R, 6)
elif r6RR:
FindedNum(r6RR, 6)
else:
FH = bytearray([0x2C,0x12, 0x00, 0x00, find_flag, Find_Task,0x5B])
uart.write(FH)
elif Target_Num == 7:
#进行模板匹配 //这里每个数字至少给3个模板， 但给五六个其实也行
r7L = FindTemplate(template7L)
r7LL = FindTemplate(template7LL)
r7R = FindTemplate(template7R)
r7RR = FindTemplate(template7RR)
#判断哪个模板匹配成功，并将成功匹配的相应数据发送给主控
if r7L:
FindedNum(r7L, 7)
elif r7LL:
FindedNum(r7LL, 7)
elif r7R:
FindedNum(r7R, 7)
elif r7RR:
FindedNum(r7RR, 7)
else:
FH = bytearray([0x2C,0x12, 0x00, 0x00, find_flag, Find_Task,0x5B])
uart.write(FH)
elif Target_Num == 8:
#进行模板匹配 //这里每个数字至少给3个模板， 但给五六个其实也行
r8L = FindTemplate(template8L)
r8LL = FindTemplate(template8LL)
r8R = FindTemplate(template8R)
r8RR = FindTemplate(template8RR)
#判断哪个模板匹配成功，并将成功匹配的相应数据发送给主控
if r8L:
FindedNum(r8L, 8)
elif r8LL:
FindedNum(r8LL, 8)
elif r8R:
FindedNum(r8R, 8)
elif r8RR:
FindedNum(r8RR, 8)
else:
FH = bytearray([0x2C,0x12, 0x00, 0x00, find_flag, Find_Task,0x5B])
uart.write(FH)
#else: time.sleep_ms(100)
else: time.sleep_ms(100)
print(clock.fps(),Find_Task, Target_Num)
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