from PIL import Image, ImageOps

import matplotlib.pyplot as plt

# Load the image

image_path = '/mnt/data/1000005810.jpg'

img = Image.open(image_path)

# Convert to RGB just in case

img = img.convert('RGB')

# Crop the face region roughly (manual approximation for this image)

width, height = img.size

center_x = width // 2

center_y = height // 2

# We'll take a square crop around the center for symmetry check

crop_size = min(width, height) // 2

left = center_x - crop_size // 2

top = center_y - crop_size // 2

right = center_x + crop_size // 2

bottom = center_y + crop_size // 2

face_crop = img.crop((left, top, right, bottom))

# Split into left and right halves

face_width, face_height = face_crop.size

left_half = face_crop.crop((0, 0, face_width // 2, face_height))

right_half = face_crop.crop((face_width // 2, 0, face_width, face_height))

# Mirror the halves to compare

left_mirror = ImageOps.mirror(left_half)

right_mirror = ImageOps.mirror(right_half)

# Combine for visualization: original halves mirrored

left_combo = Image.new('RGB', (face_width, face_height))

left_combo.paste(left_half, (0, 0))

left_combo.paste(left_mirror, (face_width // 2, 0))

right_combo = Image.new('RGB', (face_width, face_height))

right_combo.paste(right_mirror, (0, 0))

right_combo.paste(right_half, (face_width // 2, 0))

# Plot original crop and the mirrored versions

fig, axes = plt.subplots(1, 3, figsize=(12, 6))

axes[0].imshow(face_crop)

axes[0].set_title("Original Face Crop")

axes[0].axis("off")

axes[1].imshow(left_combo)

axes[1].set_title("Left Side Mirrored")

axes[1].axis("off")

axes[2].imshow(right_combo)

axes[2].set_title("Right Side Mirrored")

axes[2].axis("off")

plt.tight_layout()

plt.show()