@kidswong999看过写字例程还是不会加啊 不知道该怎么加，加在哪里，帮忙看看吧

不会加啊 不知道该加在哪里，帮忙看看吧

import sensor, time, image, pyb

import lcd


RED_LED_PIN = 1

GREEN_LED_PIN = 2



sensor.reset() # Initialize the camera sensor.

sensor.set_pixformat(sensor.GRAYSCALE) # or sensor.GRAYSCALE

sensor.set_framesize(sensor.B128X128) # or sensor.QQVGA (or others)

sensor.set_windowing((92,112))

lcd.init() # Initialize the lcd screen.

#lcd初始化





face_cascade = image.HaarCascade("frontalface", stages=25)




#SUB = "s1"

NUM_SUBJECTS = 1 #图像库中不同人数，一共2人

NUM_SUBJECTS_IMGS = 20 #每人有20张样本图片



# 拍摄当前人脸。
while (True):
    lcd.display(sensor.snapshot().histeq()) # Take a picture and display the image.

#将图像显示在lcd中
    img = sensor.snapshot().histeq()
    img.median(0, percentile=0.5)
    objects = img.find_features(face_cascade, threshold=0.75, scale=1.35)
#img = image.Image("face/%s/1.pgm"%(SUB))
    if not objects:
        pyb.LED(GREEN_LED_PIN).off()
        pyb.LED(RED_LED_PIN).on()
        print("没有检测到人脸")

    for r in objects:

        img.draw_rectangle(r)

    img = sensor.snapshot().histeq()
    img.median(0, percentile=0.5)
    d0 = img.find_lbp((0, 0, img.width(), img.height()))

#d0为当前人脸的lbp特征

    img = None

    pmin = 999999

    num=0



    def min(pmin, a, s):

        global num

        if a<pmin:

            pmin=a

            num=s

        return pmin



    for s in range(1, NUM_SUBJECTS+1):

        dist = 0

        for i in range(2, NUM_SUBJECTS_IMGS+1):

            img = image.Image("face/s%d/%d.pgm"%(s, i))

            d1 = img.find_lbp((0, 0, img.width(), img.height()))

        #d1为第s文件夹中的第i张图片的lbp特征

            dist += image.match_descriptor(d0, d1)#计算d0 d1即样本图像与被检测人脸的特征差异度。

   # print("Average dist for subject %d: %d"%(s, dist/NUM_SUBJECTS_IMGS))

        pmin = min(pmin, dist/NUM_SUBJECTS_IMGS, s)#特征差异度越小，被检测人脸与此样本更相似更匹配。

   # print(pmin)
        for r in objects:
            if pmin < 7000:
               pyb.LED(GREEN_LED_PIN).on()
               print(num)
            else:
               pyb.LED(GREEN_LED_PIN).off()
               pyb.LED(RED_LED_PIN).on()
               print("识别失败")

@kidswong999 识别成功后要在屏幕上显示人的编号该怎么加，加哪里呢

上面是我现在的代码，是人脸检测和人脸分辨同时进行，要怎样改成先检测有无人脸存在，有人脸则计算LBP特征值，无人脸则直接输出无人脸？

import sensor, time, image, pyb

import lcd


RED_LED_PIN = 1

GREEN_LED_PIN = 2



sensor.reset() # Initialize the camera sensor.

sensor.set_pixformat(sensor.GRAYSCALE) # or sensor.GRAYSCALE

sensor.set_framesize(sensor.B128X128) # or sensor.QQVGA (or others)

sensor.set_windowing((92,112))

lcd.init() # Initialize the lcd screen.

#lcd初始化





face_cascade = image.HaarCascade("frontalface", stages=25)




#SUB = "s1"

NUM_SUBJECTS = 3 #图像库中不同人数，一共3人

NUM_SUBJECTS_IMGS = 20 #每人有20张样本图片



# 拍摄当前人脸。
while (True):

    img = sensor.snapshot()

    objects = img.find_features(face_cascade, threshold=0.75, scale=1.35)
#img = image.Image("face/%s/1.pgm"%(SUB))
    for r in objects:

        img.draw_rectangle(r)

    img = sensor.snapshot()
    d0 = img.find_lbp((0, 0, img.width(), img.height()))

#d0为当前人脸的lbp特征

    img = None

    pmin = 999999

    num=0



    def min(pmin, a, s):

        global num

        if a<pmin:

            pmin=a

            num=s

        return pmin



    for s in range(1, NUM_SUBJECTS+1):

        dist = 0

        for i in range(2, NUM_SUBJECTS_IMGS+1):

            img = image.Image("face/s%d/%d.pgm"%(s, i))

            d1 = img.find_lbp((0, 0, img.width(), img.height()))

        #d1为第s文件夹中的第i张图片的lbp特征

            dist += image.match_descriptor(d0, d1)#计算d0 d1即样本图像与被检测人脸的特征差异度。

   # print("Average dist for subject %d: %d"%(s, dist/NUM_SUBJECTS_IMGS))

        pmin = min(pmin, dist/NUM_SUBJECTS_IMGS, s)#特征差异度越小，被检测人脸与此样本更相似更匹配。

   # print(pmin)
        if pmin < 6000:
           pyb.LED(GREEN_LED_PIN).on()
           print(num)
        else:
           pyb.LED(GREEN_LED_PIN).off()
           pyb.LED(RED_LED_PIN).on()
           print(0)


        lcd.display(sensor.snapshot()) # Take a picture and display the image.

    #将图像显示在lcd中