Simple (and fairly crap) face tracker for Raspberry Pi with a pan-tilt hat.

face.py

import numpy as np
import cv2
import pantilthat
import picamera

pantilthat.pan(0)
pantilthat.tilt(0)

faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
camera = picamera.PiCamera()
camera.resolution = (640, 480)
while True:
    output = np.empty((480, 640, 3), dtype=np.uint8)
    camera.capture(output, 'bgr')
    img = cv2.flip(output, -1)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = faceCascade.detectMultiScale(
        gray,     
        scaleFactor=1.2,
        minNeighbors=5,     
        minSize=(20, 20)
    )
    for (x,y,w,h) in faces:
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]  
    if len(faces) == 1:
        xx = x+w/2
        print(xx)
        if xx < 300:
            current_pan = pantilthat.get_pan()
            delta = max(int((320 - xx)/10), 1)
            pan = min(current_pan + delta, 70)
            pantilthat.pan(pan)
        elif xx > 340:
            current_pan = pantilthat.get_pan()
            delta = max(int((xx - 320)/10), 1)
            pan = max(current_pan - delta, -70)
            pantilthat.pan(pan)
        yy = y+h/2
        print(yy)
        if yy > 260:
            current_tilt = pantilthat.get_tilt()
            delta = max(int((yy-240)/8), 1)
            tilt = min(current_tilt + delta, 70)
            pantilthat.tilt(tilt)
        elif yy < 220:
            current_tilt = pantilthat.get_tilt()
            delta = max(int((240-yy)/8), 1)
            tilt = max(current_tilt - delta, -70)
            pantilthat.tilt(tilt)

    cv2.imshow('video',img)
    k = cv2.waitKey(30) & 0xff
    if k == 27: # press 'ESC' to quit
        break
cv2.destroyAllWindows()