import gradio as gr
from PIL import Image
import os
import tempfile
import pyheif
import ntpath

def open_heic_image(image_path):
    heif_file = pyheif.read(image_path)
    img = Image.frombytes(
        heif_file.mode, 
        heif_file.size, 
        heif_file.data,
        "raw",
        heif_file.mode,
        heif_file.stride,
    )
    return img

def optimize_image(image, png_optimize, jpeg_quality, jpeg_resolution, webp_quality):
    # Obtener el nombre del archivo original sin la extensión
    original_filename = ntpath.basename(image.name)
    base_name, ext = os.path.splitext(original_filename)
    
    # Manejar archivos HEIC
    if image.name.lower().endswith(".heic"):
        img = open_heic_image(image.name)
    else:
        img = Image.open(image)

    # Convertir la imagen a RGB si está en RGBA o en un modo no soportado por JPEG
    if img.mode not in ['RGB', 'L']:
        img = img.convert('RGB')
    
    original_size = os.path.getsize(image.name) / 1024  # tamaño en KB
    output_dir = "/tmp/optimized_images"
    os.makedirs(output_dir, exist_ok=True)
    
    # Lista para almacenar los resultados
    results = []

    # Optimización para PNG
    if png_optimize:
        lossless_output_path = os.path.join(output_dir, f"{base_name}-lossless.png")
        img.save(lossless_output_path, format="PNG", optimize=True)
        lossless_size = os.path.getsize(lossless_output_path) / 1024
        percent_reduction = 100 * (original_size - lossless_size) / original_size
        results.append((Image.open(lossless_output_path), f"PNG: {lossless_size:.2f} KB (diferencia: {-percent_reduction:.2f} KB)", lossless_output_path))

    # Optimización para JPEG
    lossy_output_path = os.path.join(output_dir, f"{base_name}-lossy.jpg")
    img.save(lossy_output_path, format="JPEG", quality=jpeg_quality, optimize=True)
    lossy_size = os.path.getsize(lossy_output_path) / 1024
    percent_reduction = 100 * (original_size - lossy_size) / original_size
    results.append((Image.open(lossy_output_path), f"JPEG: {lossy_size:.2f} KB (diferencia: {-percent_reduction:.2f} KB)", lossy_output_path))

    # Reducción de resolución (JPEG)
    reduced_output_path = os.path.join(output_dir, f"{base_name}-reduced_resolution.jpg")
    new_resolution = (img.width * jpeg_resolution // 100, img.height * jpeg_resolution // 100)
    reduced_img = img.resize(new_resolution, Image.LANCZOS)
    reduced_img.save(reduced_output_path, format="JPEG", quality=jpeg_quality, optimize=True)
    reduced_size = os.path.getsize(reduced_output_path) / 1024
    percent_reduction = 100 * (original_size - reduced_size) / original_size
    results.append((Image.open(reduced_output_path), f"JPEG (resolución reducida): {reduced_size:.2f} KB (diferencia: {-percent_reduction:.2f} KB)", reduced_output_path))

    # Optimización para WebP
    webp_lossy_output_path = os.path.join(output_dir, f"{base_name}-lossy.webp")
    img.save(webp_lossy_output_path, format="WEBP", quality=webp_quality, optimize=True)
    webp_lossy_size = os.path.getsize(webp_lossy_output_path) / 1024
    percent_reduction = 100 * (original_size - webp_lossy_size) / original_size
    results.append((Image.open(webp_lossy_output_path), f"WebP: {webp_lossy_size:.2f} KB (diferencia: {-percent_reduction:.2f} KB)", webp_lossy_output_path))

    # Asegurarse de que todos los resultados están presentes (4 entradas)
    while len(results) < 4:
        results.append((None, "", None))
    
    # Dividir los resultados en imágenes, textos y rutas para descarga
    outputs = []
    for result in results:
        outputs.extend(result)

    return outputs

with gr.Blocks() as demo:
    with gr.Tab("Optimización Tradicional"):
        image_input = gr.File(label="Sube tu imagen", file_types=['image', '.heic'])
        optimize_button = gr.Button("Optimizar")

        with gr.Row():
            with gr.Column():
                optimized_output1 = gr.Image(label="Optimización sin pérdida")
                png_optimize = gr.Checkbox(label="Optimizar PNG", value=True)
                download_button1 = gr.File(label="Descargar", visible=True)
                optimized_size1 = gr.Text(value="", interactive=False, show_label=False)

            with gr.Column():
                optimized_output2 = gr.Image(label="Optimización con pérdida (JPEG)")
                jpeg_quality = gr.Slider(label="Calidad JPEG", minimum=10, maximum=100, value=75, step=1)
                download_button2 = gr.File(label="Descargar", visible=True)
                optimized_size2 = gr.Text(value="", interactive=False, show_label=False)
                
            with gr.Column():
                optimized_output3 = gr.Image(label="Reducción de resolución (JPEG)")
                jpeg_resolution = gr.Slider(label="Resolución JPEG (%)", minimum=10, maximum=100, value=75, step=1)
                download_button3 = gr.File(label="Descargar", visible=True)
                optimized_size3 = gr.Text(value="", interactive=False, show_label=False)

            with gr.Column():
                optimized_output4 = gr.Image(label="Optimización WebP con pérdida")
                webp_quality = gr.Slider(label="Calidad WebP", minimum=10, maximum=100, value=75, step=1)
                download_button4 = gr.File(label="Descargar", visible=True)
                optimized_size4 = gr.Text(value="", interactive=False, show_label=False)

        # Conectar cada control a la función de optimización
        optimize_button.click(
            fn=optimize_image,
            inputs=[image_input, png_optimize, jpeg_quality, jpeg_resolution, webp_quality],
            outputs=[
                optimized_output1, optimized_size1, download_button1,
                optimized_output2, optimized_size2, download_button2,
                optimized_output3, optimized_size3, download_button3,
                optimized_output4, optimized_size4, download_button4
            ]
        )

demo.launch()