import cv2

# Membaca gambar asli
original_image = cv2.imread('images/backup/testface/Akshay Kumar/Akshay Kumar_40.jpg')
cv2.imshow('Original Image', original_image)

# Mengonversi gambar ke grayscale
gray_image = cv2.cvtColor(original_image, cv2.COLOR_BGR2GRAY)
cv2.imshow('Grayscale Image', gray_image)

# Meningkatkan kontras gambar grayscale
contrastpic = cv2.equalizeHist(gray_image)
cv2.imshow('Contrast Enhanced Image', contrastpic)

# Memuat classifier Haar Cascade untuk deteksi wajah
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

# Mendeteksi wajah dalam gambar grayscale
faces = face_cascade.detectMultiScale(gray_image, scaleFactor=1.2, minNeighbors=10, minSize=(50, 50))

# Inisialisasi variabel cropped_face dengan nilai kosong
cropped_face = None

for i, (x, y, w, h) in enumerate(faces, 1):
    # Memotong wajah dari gambar asli
    cropped_face = original_image[y:y + h, x:x + w]
    cv2.imshow(f'Cropped Face {i}', cropped_face)

# Mengubah ukuran wajah terpotong
if cropped_face is not None:
    resized_face = cv2.resize(cropped_face, (300, 300))
    cv2.imshow('Resized Face', resized_face)

    # Mengonversi wajah yang diubah ukurannya ke grayscale
    gray_resized_face = cv2.cvtColor(resized_face, cv2.COLOR_BGR2GRAY)
    cv2.imshow('Grayscale Resized Face', gray_resized_face)

    # Melakukan normalisasi pada wajah grayscale yang diubah ukurannya
    normalized_face = cv2.normalize(gray_resized_face, None, alpha=0, beta=255, norm_type=cv2.NORM_MINMAX)
    cv2.imshow('Normalized Face', normalized_face)

cv2.waitKey(0)
cv2.destroyAllWindows()