image-classification-service/test/utils/stitching.py

import random
from copy import deepcopy
from itertools import chain

from funcy import rpartial, juxt

from image_prediction.stitching.split_mapper import SplitMapper, HorizontalSplitMapper, VerticalSplitMapper
from image_prediction.stitching.utils import validate_box


class BoxSplitter:
    def __init__(self, noise=None):
        self.__steps = None
        self.__noise = (0, 0) if not noise else noise

    def split_box(self, box, steps=5):
        self.__steps = steps
        return self.__split_recursively(box, 0)

    def __split_recursively(self, box, step):
        return self.__split_and_recurse(box, step) if self.__steps_left(step) else self.__base_case(box)

    def __steps_left(self, step):
        return step < self.__steps

    @staticmethod
    def __base_case(box):
        return [box]

    def __split_and_recurse(self, box, step):
        new_boxes = self.__random_split(box)
        new_boxes_per_branch = self.__tree_recurse(new_boxes, step + 1)
        return chain.from_iterable(new_boxes_per_branch)

    def __random_split(self, box):
        splitter = random.choice([self.__split_horizontal, self.__split_vertical])
        new_boxes = splitter(box)
        return new_boxes

    def __tree_recurse(self, boxes, step):
        return map(rpartial(self.__split_recursively, step + 1), boxes)

    def __split_horizontal(self, box):
        return self.__split_if_large_enough(HorizontalSplitMapper(box))

    def __split_vertical(self, box):
        return self.__split_if_large_enough(VerticalSplitMapper(box))

    def __split_if_large_enough(self, wrapped_box: SplitMapper):
        return (
            self.__get_child_boxes(wrapped_box)
            if self.__large_enough(wrapped_box)
            else self.__base_case(wrapped_box.wrapped)
        )

    def noise(self):
        return int(round(random.uniform(*self.__noise)))

    @staticmethod
    def __large_enough(wrapped_box: SplitMapper):
        return wrapped_box.dim >= 10

    def __get_child_boxes(self, wrapped_box: SplitMapper):

        split_len = random.randint(5, wrapped_box.dim - 5)
        split_point = wrapped_box.c1 + split_len

        box_left, box_right = juxt(deepcopy, deepcopy)(wrapped_box)

        noise = -self.noise()
        box_left.dim = split_len + noise
        box_right.dim = wrapped_box.dim - split_len

        box_left.c2 = split_point + noise
        box_right.c1 = split_point

        validate_box(box_left.wrapped)
        validate_box(box_right.wrapped)

        return box_left.wrapped, box_right.wrapped