import numpy as np
import cv2
from skimage.transform import radon
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation, PillowWriter

# Load and resize the image
image_path = '_58f4b8e1-9f7c-4ab7-85c5-6cdf5deea15e.jpeg' 
image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
image_small = cv2.resize(image, (1920, 1920))  # Resize to 1080p

# Create a figure for the plot
fig, axs = plt.subplots(1, 2)

# Initialize the plot with the first frame
axs[0].imshow(image_small, cmap='gray')
line, = axs[0].plot([960, 960], [0, 1079], color='red')

# Compute the full radon transformation
theta = np.linspace(0., 180., 180, endpoint=False)
image_radon = radon(image_small, theta=theta)
im = axs[1].imshow(image_radon, cmap='gray', aspect='auto')
line_radon, = axs[1].plot([0, 0], [0, image_radon.shape[0]], color='red')

def update(i):
    # Update the red line in the original image
    x = 960 + 960 * np.cos(np.deg2rad(i+90))
    y = 960 + 960 * np.sin(np.deg2rad(i+90))
    line.set_data([1920-x, x], [1920-y, y])

    # Update the red line in the radon transformation image
    line_radon.set_data([i, i], [0, image_radon.shape[0]])

# Create an animation
ani = FuncAnimation(fig, update, frames=np.arange(0, 180, 1))

# Save the animation as a GIF
gif_path = 'radon_transform.gif'  # replace with your preferred path
ani.save(gif_path, writer=PillowWriter(fps=60))  # Increase FPS to 60