பLMemoryError:内存分配失败，分配7250字节
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# 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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https://book.openmv.cc/image/mulity-template-match.html
不要一开始就把所有模板导入，内存消耗太大了。
解决办法：参考这个代码，https://book.openmv.cc/image/mulity-template-match.html