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