# created with great guidance from https://github.com/NimaBoscarino

import gradio as gr

import kornia as K
from kornia.core import Tensor


def filters(file, box_blur, blur_pool2d, gaussian_blur2d, max_blur_pool2d, median_blur):      
    # load the image using the rust backend          
    img: Tensor = K.io.load_image(file.name, K.io.ImageLoadType.RGB32)
    img = img[None]  # 1xCxHxW / fp32 / [0, 1]

    # apply tensor image enhancement
    x_out: Tensor = K.filters.box_blur(img, (int(box_blur), int(box_blur)))
    x_out = K.filters.blur_pool2d(x_out, int(blur_pool2d))
    x_out = K.filters.gaussian_blur2d(x_out, 
                                      (int(gaussian_blur2d), int(gaussian_blur2d)), 
                                      (float(gaussian_blur2d), float(gaussian_blur2d)))
    x_out = K.filters.max_blur_pool2d(x_out, int(max_blur_pool2d))
    x_out = K.filters.median_blur(x_out, (int(median_blur), int(median_blur)))

    return K.utils.tensor_to_image(x_out)


examples = [
    ["examples/monkey.jpg", 1, 1, 1, 1, 1],
    ["examples/pikachu.jpg", 1, 1, 1, 1, 1],
]

title = "Kornia Image Filters"
description = "<p style='text-align: center'>This is a Gradio demo for Kornia's Image Filters.</p><p style='text-align: center'>To use it, simply upload your image, or click one of the examples to load them, and use the sliders to enhance! Read more at the links at the bottom.</p>"
article = "<p style='text-align: center'><a href='https://kornia.readthedocs.io/en/latest/' target='_blank'>Kornia Docs</a> | <a href='https://github.com/kornia/kornia' target='_blank'>Kornia Github Repo</a> | <a href='https://kornia-tutorials.readthedocs.io/en/latest/image_enhancement.html' target='_blank'>Kornia Enhancements Tutorial</a></p>"

iface = gr.Interface(
    filters,
    [
        gr.inputs.Image(type="file"),
        gr.inputs.Slider(minimum=1, maximum=10, step=1, default=1, label="Box Blur"),
        gr.inputs.Slider(minimum=1, maximum=10, step=1, default=1, label="Blur Pool"),
        gr.inputs.Slider(minimum=1, maximum=21, step=2, default=1, label="Gaussian Blur"),
        gr.inputs.Slider(minimum=1, maximum=20, step=1, default=1, label="Max Pool"),
        gr.inputs.Slider(minimum=1, maximum=5, step=2, default=1, label="Median Blur"),
    ],
    "image",
    examples=examples,
    # title=title,
    # description=description,
    # article=article,
    live=True
)

iface.launch()