import cv2
import numpy as np
import time
from pad4pi import rpi_gpio

# Set up keypad
KEYPAD = [
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9],
    ['*', 0, '#']
]

ROW_PINS = [5, 6, 13, 19]  # BCM numbering
COL_PINS = [21, 20, 16]  # BCM numbering

factory = rpi_gpio.KeypadFactory()

keypad = factory.create_keypad(keypad=KEYPAD, row_pins=ROW_PINS, col_pins=COL_PINS)

# Set up servo
SERVO_PIN = 17
SERVO_MIN_DUTY = 3
SERVO_MAX_DUTY = 14

# Set up face recognition model (Assuming you have pre-trained model)
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

# Set up webcam
cap = cv2.VideoCapture(0)

# Function to recognize faces
def recognize_faces():
    # Your face recognition code here
    pass

# Function to control servo
def control_servo(angle):
    # Calculate duty cycle from angle
    duty = SERVO_MIN_DUTY + (angle / 180) * (SERVO_MAX_DUTY - SERVO_MIN_DUTY)
    # Your servo control code here
    pass

# Function to handle keypad input
def handle_keypad_input(key):
    # Your keypad input handling code here
    pass

# Main loop
while True:
    ret, frame = cap.read()
    if not ret:
        continue

    # Convert frame to grayscale for face detection
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Detect faces in the grayscale frame
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)

    for (x, y, w, h) in faces:
        # Draw rectangle around the face
        cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)

    cv2.imshow('frame', frame)

    # Check for keypad input
    keypad.registerKeyPressHandler(handle_keypad_input)

    # Exit if 'q' is pressed
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()