import cv2
import numpy as np


# Load the Haar cascade files for face and eye detection
face_cascade = cv2.CascadeClassifier(
    'haar_cascade_files/haarcascade_frontalface_default.xml')

eye_cascade = cv2.CascadeClassifier(
    'haar_cascade_files/haarcascade_eye.xml')

# Check if the face cascade file has been loaded correctly
if face_cascade.empty():
    raise IOError('Unable to load the face cascade classifier xml file')
    
# Check if the eye cascade file has been loaded correctly
if eye_cascade.empty():
    raise IOError('Unable to load the eye cascade classifier xml file')
    
# Initialize the video capture object
cap = cv2.VideoCapture(0)

# Define the scaling factor
ds_factor = 0.5

# Iterate until the user presses the 'Esc' key
while True:
    # Capture the current frame
    _, frame = cap.read()
    
    # Resize the frame
    frame = cv2.resize(frame, None, fx = ds_factor, fy = ds_factor,
                       interpolation = cv2.INTER_AREA)
    
    # Convert the frame from RGB to grayscale
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    
    # Run the face detector on the grayscale image
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    
    # For each face detected, run the eye detector 
    # within that region
    for (x, y, w, h) in faces:
        # Extract the grayscale face ROI
        roi_gray = gray[y:y + h, x:x + w]
        
        # Extract the color face ROI
        roi_color = frame[y:y + h, x:x + w]
        
        # Run the eye detector on the grayscale ROI
        eyes = eye_cascade.detectMultiScale(roi_gray)
        
        # Draw circles around the eyes
        for (x_eye, y_eye, w_eye, h_eye) in eyes:
            center = (int(x_eye + 0.5 * w_eye), 
                      int(y_eye + 0.5 * h_eye))
            radius = int(0.3 * (w_eye + h_eye))
            color = (0, 255, 0)
            thickness = 3
            cv2.circle(roi_color, center, radius, color, thickness)
            
    # Display the output
    cv2.imshow('Eye Detector', frame)
        
    # Check if the user pressed the 'Esc' key
    c = cv2.waitKey(1)
    if c == 27:
        break
    
# Release the video capture object
cap.release()

# Close all windows
cv2.destroyAllWindows()
