# Importing required libraries
import gradio as gr
from PIL import Image
import random

# Define pixel sizes for different levels
pixel_sizes = [128, 96, 64, 32, 24, 16, 12, 8, 4, 2]

# Function to pixelate an image
def pixelate(image, pixel_size):
    # Reduce the image size
    small = image.resize((image.size[0] // pixel_size, image.size[1] // pixel_size), Image.Resampling.NEAREST)
    # Scale back to original size
    return small.resize(image.size, Image.Resampling.NEAREST)

# List of celebrities and folder paths
celeb_list = ["Tom Cruise", "Jake Gyllenhal", "Natalie Portman", "Aubrey Plaza", "Oscar Isaac", "Kate Winslet", "Ellen DeGeneres"]
celeb_folder = {
    "Tom Cruise": "./Celebs/TomCruise.jpeg",
    "Jake Gyllenhal": "./Celebs/JakeGyllenhal.jpg",
    "Natalie Portman": "./Celebs/NataliePortman.png",
    "Aubrey Plaza": "./Celebs/AubreyPlaza.jpg",
    "Oscar Isaac": "./Celebs/OscarIsaac.jpg",
    "Kate Winslet": "./Celebs/KateWinslet.jpg",
    "Ellen DeGeneres": "./Celebs/EllenDeGeneres.jpg"
}

# Initialize global variables
current_index = 0
current_pixel_size = 256

def clear_and_start(prev_size=256):
    """
    Resets the current image and returns the first level of pixelation.
    """
    global current_index, current_pixel_size
    current_pixel_size = prev_size
    celebrity = celeb_list[current_index]
    image_path = celeb_folder[celebrity]
    
    # Open and pixelate the image
    img = Image.open(image_path)
    result_img = pixelate(img, current_pixel_size)
    return result_img, celebrity, current_pixel_size

def next_image(pixel_size):
    """
    Moves to the next celebrity and pixelates the image.
    """
    global current_index, current_pixel_size
    current_index = (current_index + 1) % len(celeb_list)  # Loop through the list
    current_pixel_size = pixel_size
    celebrity = celeb_list[current_index]
    image_path = celeb_folder[celebrity]
    
    # Open and pixelate the image
    img = Image.open(image_path)
    result_img = pixelate(img, current_pixel_size)
    return result_img, celebrity, current_pixel_size

def progressive_clear(pixel_size):
    """
    Progressively clears the pixelation of the current image.
    """
    global current_pixel_size
    current_pixel_size = max(pixel_size - 32, 2)  # Decrease pixel size for better clarity
    celebrity = celeb_list[current_index]
    image_path = celeb_folder[celebrity]
    
    # Open and pixelate the image
    img = Image.open(image_path)
    result_img = pixelate(img, current_pixel_size)
    return result_img, celebrity, current_pixel_size

# Gradio App Layout
MARKDOWN = "## Guess the Celebrity before the Image Clears Up!"
with gr.Blocks(theme=gr.themes.Ocean()) as demo:
    gr.Markdown(MARKDOWN)
    
    with gr.Row():
        with gr.Column(scale=1):
            pixelated_image = gr.Image(type='pil', label='Pixelated Image')
            with gr.Accordion("Reveal Answer", open=False):
                answer = gr.Textbox(label="Current Celebrity")

        with gr.Column(scale=1):
            Start_button = gr.Button(value='Start', variant='primary')
            Clear_button = gr.Button(value='Clear More', variant='secondary')
            Next_button = gr.Button(value='Next Image', variant='success')

    # Define button actions
    Start_button.click(fn=clear_and_start, inputs=[], outputs=[pixelated_image, answer, gr.State(current_pixel_size)])
    Clear_button.click(fn=progressive_clear, inputs=[gr.State(current_pixel_size)], outputs=[pixelated_image, answer, gr.State(current_pixel_size)])
    Next_button.click(fn=next_image, inputs=[gr.State(current_pixel_size)], outputs=[pixelated_image, answer, gr.State(current_pixel_size)])

demo.launch(debug=True, show_error=True)