doc(narugo): add documentation for new methods

from typing import Tuple

from typing import Tuple, List

import matplotlib.pyplot as plt

from PIL import Image

from imgutils.data import load_image, grid_transparent

from imgutils.data import load_image, grid_transparent, ImageTyping

from imgutils.validate.truncate import _mock_load_truncated_images

INCHES_TO_PIXELS = 96

def _image_input_process(img) -> Tuple[Image.Image, str]:

    if isinstance(img, tuple):

        ax.axis('off')

    plt.savefig(save_as, bbox_inches='tight', pad_inches=0.1, dpi=300, transparent=True)

@_mock_load_truncated_images(True)

def image_table(images: List[List[ImageTyping]], columns: List[str], rows: List[str], save_as: str,

                keep_axis: bool = False, figsize=(720, 600), dpi: int = 300, fontsize: int = 18, padsize: int = 5):

    plt.cla()

    plt.tight_layout()

    assert images, 'No less than 1 images required.'

    fig, axs = plt.subplots(len(rows), len(columns),

                            figsize=(figsize[0] / INCHES_TO_PIXELS, figsize[1] / INCHES_TO_PIXELS))

    plt.subplots_adjust(wspace=padsize / INCHES_TO_PIXELS, hspace=padsize / INCHES_TO_PIXELS)

    for xi in range(len(rows)):

        for yi in range(len(columns)):

            img = images[xi][yi]

            ax = axs[yi] if len(rows) == 1 else axs[xi, yi]

            if img:

                image = load_image(img, force_background=None)

                ax.imshow(grid_transparent(image))

                if not keep_axis:

                    ax.set_xticks([])

                    ax.set_yticks([])

            else:

                ax.set_xticks([])

                ax.set_yticks([])

            if xi == 0:

                ax.set_title(columns[yi], fontsize=fontsize)

            if yi == 0:

                ax.set_ylabel(rows[xi], fontsize=fontsize)

    plt.savefig(save_as, bbox_inches='tight', pad_inches=0.02, dpi=dpi, transparent=True)

from functools import partial

from hbutils.reflection import nested_for

from tqdm.auto import tqdm

from imgutils.edge import edge_image_with_canny as edge_image

from plot import image_table

if __name__ == '__main__':

    demo_images = ['hutao.png', 'skadi.jpg']

    funcs = [

        ('canny', partial(edge_image)),

        ('canny\nbackcolor=transparent', partial(edge_image, backcolor='transparent')),

        ('canny\nbackcolor=white\nforecolor=black',

         partial(edge_image, backcolor='white', forecolor='black')),

    ]

    table = [[item] for item in demo_images]

    for (xi, origin_image), (_, func) in \

            tqdm(list(nested_for(enumerate(demo_images), funcs))):

        table[xi].append(func(origin_image))

    image_table(

        table,

        columns=['origin', *(name for name, _ in funcs)],

        rows=['' for _ in demo_images],

        save_as='canny.dat.svg',

        figsize=(1600, 980),

    )

imgutils.edge.canny

==============================

.. currentmodule:: imgutils.edge.canny

.. automodule:: imgutils.edge.canny

get_edge_by_canny

--------------------------------------

.. autofunction:: get_edge_by_canny

edge_image_with_canny

--------------------------------------

.. autofunction:: edge_image_with_canny

from functools import partial

from hbutils.reflection import nested_for

from tqdm.auto import tqdm

from imgutils.edge import edge_image_with_canny, edge_image_with_lineart, edge_image_with_lineart_anime

from plot import image_table

if __name__ == '__main__':

    demo_images = ['hutao.png', 'skadi.jpg', 'xx.jpg', 'surtr_underwear.png']

    funcs = [

        ('canny', edge_image_with_canny),

        ('lineart', edge_image_with_lineart),

        ('lineart\n(coarse)', partial(edge_image_with_lineart, coarse=True)),

        ('lineart\nanime', edge_image_with_lineart_anime)

    ]

    table = [[item] for item in demo_images]

    for (xi, origin_image), (_, func) in \

            tqdm(list(nested_for(enumerate(demo_images), funcs))):

        table[xi].append(func(origin_image, backcolor='white', forecolor='black'))

    image_table(

        table,

        columns=['origin', *(name for name, _ in funcs)],

        rows=['' for _ in demo_images],

        save_as='edge.dat.svg',

        figsize=(1800, 1350),

    )