import cv2
import numpy
import os


def get_image_paths(directory):
    # return [x.path for x in os.scandir(directory) if x.name.endswith(".jpg") or x.name.endswith(".png")]
    return [x.path for x in os.scandir(directory) if x.name.endswith(".png")]


def load_images(image_paths, convert=None):
    iter_all_images = (cv2.resize(cv2.imread(fn), (256, 256)) for fn in image_paths)
    if convert:
        iter_all_images = (convert(img) for img in iter_all_images)
    for i, image in enumerate(iter_all_images):
        if i == 0:
            all_images = numpy.empty((len(image_paths),) + image.shape, dtype=image.dtype)
        all_images[i] = image
    return all_images


def get_transpose_axes(n):
    if n % 2 == 0:
        y_axes = list(range(1, n - 1, 2))
        x_axes = list(range(0, n - 1, 2))
    else:
        y_axes = list(range(0, n - 1, 2))
        x_axes = list(range(1, n - 1, 2))
    return y_axes, x_axes, [n - 1]


def stack_images(images):
    images_shape = numpy.array(images.shape)
    new_axes = get_transpose_axes(len(images_shape))
    new_shape = [numpy.prod(images_shape[x]) for x in new_axes]
    return numpy.transpose(
        images,
        axes=numpy.concatenate(new_axes)
    ).reshape(new_shape)