from PIL import Image
import gradio as gr
import numpy as np

def convert_to_ascii(image, text_size):
    if isinstance(image, str):
        gimage = Image.open(image)
    elif isinstance(image, np.ndarray):
        gimage = Image.fromarray(image)
    else:
         raise ValueError("Unsupported input type. Please provide a file path or a NumPy array.")

    
    width, height = gimage.size
    aspect_ratio = height / width
    new_width = int(text_size)
    new_height = int(aspect_ratio * text_size * 0.5)

    resized_image = gimage.resize((new_width, new_height))
    grayscale_image = resized_image.convert('L')

    ascii_chars = '█@&%#*░+=-:,.\/|][}{)(´„‟‚‛‘ '  # add more characters if you want

    ascii_image = ''
    for y in range(new_height):
        for x in range(new_width):
            pixel_value = grayscale_image.getpixel((x, y))
            if pixel_value == 255:  # make sure to use the GOD DAM transparency
                ascii_image += ' '
            else:
                ascii_image += ascii_chars[int(pixel_value / 255 * (len(ascii_chars) - 1))]
        ascii_image += '\n'

    return ascii_image




# Create an Interface with a title
iface = gr.Interface(
    fn=convert_to_ascii,  # Function to run
    inputs=["image","number"],  # Input component (in this case, an image)
    outputs="text",  # Output component (in this case, text)
    title="image-to-ascii (by peasoup)"
)

# Function to generate HTML code for the output text with a copy button
def copy_button(output_text):
    return f"{output_text}<br><br><button onclick=\"navigator.clipboard.writeText('{output_text}').then(() => {{alert('Text copied to clipboard')}})\">Copy to Clipboard</button>"

    # Set custom post-processing for the output text
iface.test_command = lambda output_text: copy_button(output_text)

# Launch the interface
iface.launch()