# Copyright (c) OpenMMLab. All rights reserved. import math from itertools import chain, permutations import numpy as np import pytest from mmocr.datasets.pipelines.box_utils import sort_vertex, sort_vertex8 from mmocr.datasets.pipelines.crop import box_jitter, crop_img, warp_img def test_order_vertex(): dummy_points_x = [20, 20, 120, 120] dummy_points_y = [20, 40, 40, 20] expect_points_x = [20, 120, 120, 20] expect_points_y = [20, 20, 40, 40] with pytest.raises(AssertionError): sort_vertex([], dummy_points_y) with pytest.raises(AssertionError): sort_vertex(dummy_points_x, []) for perm in set(permutations([0, 1, 2, 3])): points_x = [dummy_points_x[i] for i in perm] points_y = [dummy_points_y[i] for i in perm] ordered_points_x, ordered_points_y = sort_vertex(points_x, points_y) assert np.allclose(ordered_points_x, expect_points_x) assert np.allclose(ordered_points_y, expect_points_y) def test_sort_vertex8(): dummy_points_x = [21, 21, 122, 122] dummy_points_y = [21, 39, 39, 21] expect_points = [21, 21, 122, 21, 122, 39, 21, 39] for perm in set(permutations([0, 1, 2, 3])): points_x = [dummy_points_x[i] for i in perm] points_y = [dummy_points_y[i] for i in perm] points = list(chain.from_iterable(zip(points_x, points_y))) ordered_points = sort_vertex8(points) assert np.allclose(ordered_points, expect_points) def test_box_jitter(): dummy_points_x = [20, 120, 120, 20] dummy_points_y = [20, 20, 40, 40] kwargs = dict(jitter_ratio_x=0.0, jitter_ratio_y=0.0) with pytest.raises(AssertionError): box_jitter([], dummy_points_y) with pytest.raises(AssertionError): box_jitter(dummy_points_x, []) with pytest.raises(AssertionError): box_jitter(dummy_points_x, dummy_points_y, jitter_ratio_x=1.) with pytest.raises(AssertionError): box_jitter(dummy_points_x, dummy_points_y, jitter_ratio_y=1.) box_jitter(dummy_points_x, dummy_points_y, **kwargs) assert np.allclose(dummy_points_x, [20, 120, 120, 20]) assert np.allclose(dummy_points_y, [20, 20, 40, 40]) def test_opencv_crop(): dummy_img = np.ones((600, 600, 3), dtype=np.uint8) dummy_box = [20, 20, 120, 20, 120, 40, 20, 40] cropped_img = warp_img(dummy_img, dummy_box) with pytest.raises(AssertionError): warp_img(dummy_img, []) with pytest.raises(AssertionError): warp_img(dummy_img, [20, 40, 40, 20]) assert math.isclose(cropped_img.shape[0], 20) assert math.isclose(cropped_img.shape[1], 100) def test_min_rect_crop(): dummy_img = np.ones((600, 600, 3), dtype=np.uint8) dummy_box = [20, 20, 120, 20, 120, 40, 20, 40] cropped_img = crop_img( dummy_img, dummy_box, 0., 0., ) with pytest.raises(AssertionError): crop_img(dummy_img, []) with pytest.raises(AssertionError): crop_img(dummy_img, [20, 40, 40, 20]) with pytest.raises(AssertionError): crop_img(dummy_img, dummy_box, 4, 0.2) with pytest.raises(AssertionError): crop_img(dummy_img, dummy_box, 0.4, 1.2) assert math.isclose(cropped_img.shape[0], 20) assert math.isclose(cropped_img.shape[1], 100)