4. 代码整合问题，如何将人脸识别和人脸追踪的代码整合到一起？人脸的代码也不知道对不对？大佬求助
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    • 代码整合问题，如何将人脸识别和人脸追踪的代码整合到一起？人脸的代码也不知道对不对？大佬求助


    • 这个是人脸追踪代码

      import sensor, image, time

      from pid import PID
      from pyb import Servo

      pan_servo=Servo(1)
      tilt_servo=Servo(2)
      red_threshold = (13, 49, 18, 61, 6, 47)
      pan_pid = PID(p=0.07, i=0, imax=90) #脱机运行或者禁用图像传输，使用这个PID
      tilt_pid = PID(p=0.05, i=0, imax=90) #脱机运行或者禁用图像传输，使用这个PID

      #pan_pid = PID(p=0.1, i=0, imax=90)#在线调试使用这个PID

      #tilt_pid = PID(p=0.1, i=0, imax=90)#在线调试使用这个PID
      sensor.reset() # Initialize the camera sensor.
      sensor.set_contrast(1)
      sensor.set_gainceiling(16)
      sensor.set_pixformat(sensor.GRAYSCALE) # use RGB565.
      sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.

      sensor.skip_frames(10) # Let new settings take affect.

      sensor.set_auto_whitebal(False) # turn this off.

      clock = time.clock() # Tracks FPS.
      face_cascade = image.HaarCascade("frontalface", stages=25)

      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

      while(True):

      clock.tick() # Track elapsed milliseconds between snapshots().

img = sensor.snapshot() # Take a picture and return the image.



blobs = img.find_features(face_cascade, threshold=0.75, scale=1.35)

if blobs:

    max_blob = find_max(blobs)

    pan_error = max_blob[0]+max_blob[2]/2-img.width()/2

    tilt_error = max_blob[1]+max_blob[3]/2-img.height()/2



    print("pan_error: ", pan_error)



    img.draw_rectangle(max_blob) # rect

    img.draw_cross (int(max_blob[0]+max_blob[2]/2), int(max_blob[1]+max_blob[3]/2)) # cx, cy



    pan_output=pan_pid.get_pid(pan_error,1)/2

    tilt_output=tilt_pid.get_pid(tilt_error,1)

    print("pan_output",pan_output)

    pan_servo.angle(pan_servo.angle()+pan_output)

    tilt_servo.angle(tilt_servo.angle()-tilt_output)

      这个是人脸识别代码

      import sensor, image, time

      from pid import PID
      from pyb import Servo

      pan_servo=Servo(1)
      tilt_servo=Servo(2)
      red_threshold = (13, 49, 18, 61, 6, 47)
      pan_pid = PID(p=0.07, i=0, imax=90) #脱机运行或者禁用图像传输，使用这个PID
      tilt_pid = PID(p=0.05, i=0, imax=90) #脱机运行或者禁用图像传输，使用这个PID

      #pan_pid = PID(p=0.1, i=0, imax=90)#在线调试使用这个PID

      #tilt_pid = PID(p=0.1, i=0, imax=90)#在线调试使用这个PID
      sensor.reset() # Initialize the camera sensor.
      sensor.set_contrast(1)
      sensor.set_gainceiling(16)
      sensor.set_pixformat(sensor.GRAYSCALE) # use RGB565.
      sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.

      sensor.skip_frames(10) # Let new settings take affect.
      sensor.skip_frames(time = 500)

      sensor.set_auto_whitebal(False) # turn this off.

      clock = time.clock() # Tracks FPS.
      face_cascade = image.HaarCascade("frontalface", stages=25)

      NUM_SUBJECT = 6
      NUM_SUBJECT_IMGS = 10

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

      def min(pmin,a,s):
      global num
      if a<pmin:
      pmin=a
      num=s
      return pmin

      imgs = None
      pmin = 999999
      num=0

      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

      while():

      clock.tick() # Track elapsed milliseconds between snapshots().

img = sensor.snapshot() # Take a picture and return the image.



blobs = img.find_features(face_cascade, threshold=0.75, scale=1.35)

if blobs:

    max_blob = find_max(blobs)

    pan_error = max_blob[0]+max_blob[2]/2-img.width()/2

    tilt_error = max_blob[1]+max_blob[3]/2-img.height()/2



    print("pan_error: ", pan_error)



    img.draw_rectangle(max_blob) # rect

    img.draw_cross (int(max_blob[0]+max_blob[2]/2), int(max_blob[1]+max_blob[3]/2)) # cx, cy



    pan_output=pan_pid.get_pid(pan_error,1)/2

    tilt_output=tilt_pid.get_pid(tilt_error,1)

    print("pan_output",pan_output)

    pan_servo.angle(pan_servo.angle()+pan_output)

    tilt_servo.angle(tilt_servo.angle()-tilt_output)




    for s in range(2,NUM_SUBJECT+1):
            dist = 0
            for i in range(2,NUM_SUBJECT+1):
                imgs = image.Image("singtown/s%d/%d.pmg"%(s,i))
                d1 = imgs.find_lbp((0,0,imgs.width(),imgs.height()))
                dist +=image.match_descriptor(d0,d1)
            pmin = min(pmin.dist/NUM_SUBJECTS_IMGS，s)
    if pmin<7000:
        print("wellcome!")
    else：
    print("检测到陌生人")
else:
    print("未检测到人脸")
      0