before/after animation

import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation

# Load the images
original = Image.open('1.png')
enhanced = Image.open('2.png')

# Ensure both images are the same size
assert original.size == enhanced.size, "Images must be the same size"

# Get image dimensions
width, height = original.size

# Convert images to RGB mode
original = original.convert('RGB')
enhanced = enhanced.convert('RGB')

# Convert images to numpy arrays
original_array = np.array(original)
enhanced_array = np.array(enhanced)

# Calculate figure size (dividing by 100 to convert pixels to inches)
figsize = (width/100, height/100)

# Create the figure and axis
fig, ax = plt.subplots(figsize=figsize)

# Remove all margins
plt.subplots_adjust(left=0, right=1, top=1, bottom=0)

# Initialize the plot with the original image
im = ax.imshow(original_array, aspect='auto')

# Remove axis ticks and labels
ax.set_xticks([])
ax.set_yticks([])
ax.axis('off')

# Function to update the frame
def update(frame):
    # Create a mask for the enhanced portion
    mask = np.zeros(original_array.shape[:2], dtype=bool)
    mask[:, :frame] = True

    # Combine the original and enhanced images
    combined = np.where(mask[:, :, np.newaxis], enhanced_array, original_array)

    # Update the image data
    im.set_array(combined)

    # Add a vertical line to show the split
    ax.clear()  # Clear previous lines
    ax.imshow(combined, aspect='auto')
    ax.axvline(x=frame, color='white', linewidth=1)
    ax.set_xticks([])
    ax.set_yticks([])
    ax.axis('off')

    return [ax]

# Create the animation
anim = FuncAnimation(fig, update, frames=width, interval=50, blit=False)

# Save the animation as a gif
anim.save('comparison.gif', writer='pillow', fps=20, dpi=100)

plt.close(fig)

print("Animation saved as 'comparison.gif'")