云台人脸追踪效果巨差
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import sensor, image, time
from pid import PID
from pyb import Servopan_servo=Servo(1)
tilt_servo=Servo(2)#pan_servo.calibration(500,2500,500)
#tilt_servo.calibration(500,2500,500)#red_threshold = (13, 49, 18, 61, 6, 47)
pan_pid = PID(p=0.17, 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=0.085, 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PIDsensor.reset() # Initialize the camera sensor.
sensor.set_contrast(3)
sensor.set_gainceiling(16)
sensor.set_pixformat(sensor.GRAYSCALE) # use RGB565.
sensor.set_framesize(sensor.B160X160) # use QQVGA for speed.
sensor.set_vflip(True)
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_auto_whitebal(False) # turn this off.降低环境因素的影响
sensor.set_auto_gain(True) # 开启自动增益
sensor.set_auto_exposure(True) # 开启自动曝光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_blobwhile(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)
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