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import numpy as np |
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import pytest |
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import torch |
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from mmdet.core.bbox import distance2bbox |
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from mmdet.core.mask.structures import BitmapMasks, PolygonMasks |
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from mmdet.core.utils import mask2ndarray |
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def dummy_raw_polygon_masks(size): |
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""" |
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Args: |
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size (tuple): expected shape of dummy masks, (N, H, W) |
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Return: |
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list[list[ndarray]]: dummy mask |
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""" |
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num_obj, heigt, width = size |
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polygons = [] |
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for _ in range(num_obj): |
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num_points = np.random.randint(5) * 2 + 6 |
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polygons.append([np.random.uniform(0, min(heigt, width), num_points)]) |
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return polygons |
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def test_mask2ndarray(): |
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raw_masks = np.ones((3, 28, 28)) |
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bitmap_mask = BitmapMasks(raw_masks, 28, 28) |
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output_mask = mask2ndarray(bitmap_mask) |
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assert np.allclose(raw_masks, output_mask) |
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raw_masks = dummy_raw_polygon_masks((3, 28, 28)) |
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polygon_masks = PolygonMasks(raw_masks, 28, 28) |
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output_mask = mask2ndarray(polygon_masks) |
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assert output_mask.shape == (3, 28, 28) |
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raw_masks = np.ones((3, 28, 28)) |
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output_mask = mask2ndarray(raw_masks) |
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assert np.allclose(raw_masks, output_mask) |
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raw_masks = torch.ones((3, 28, 28)) |
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output_mask = mask2ndarray(raw_masks) |
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assert np.allclose(raw_masks, output_mask) |
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raw_masks = [] |
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with pytest.raises(TypeError): |
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output_mask = mask2ndarray(raw_masks) |
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def test_distance2bbox(): |
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point = torch.Tensor([[74., 61.], [-29., 106.], [138., 61.], [29., 170.]]) |
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distance = torch.Tensor([[0., 0, 1., 1.], [1., 2., 10., 6.], |
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[22., -29., 138., 61.], [54., -29., 170., 61.]]) |
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expected_decode_bboxes = torch.Tensor([[74., 61., 75., 62.], |
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[0., 104., 0., 112.], |
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[100., 90., 100., 120.], |
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[0., 120., 100., 120.]]) |
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out_bbox = distance2bbox(point, distance, max_shape=(120, 100)) |
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assert expected_decode_bboxes.allclose(out_bbox) |
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out = distance2bbox(point, distance, max_shape=torch.Tensor((120, 100))) |
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assert expected_decode_bboxes.allclose(out) |
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batch_point = point.unsqueeze(0).repeat(2, 1, 1) |
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batch_distance = distance.unsqueeze(0).repeat(2, 1, 1) |
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batch_out = distance2bbox( |
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batch_point, batch_distance, max_shape=(120, 100))[0] |
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assert out.allclose(batch_out) |
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batch_out = distance2bbox( |
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batch_point, batch_distance, max_shape=[(120, 100), (120, 100)])[0] |
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assert out.allclose(batch_out) |
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batch_out = distance2bbox(point, batch_distance, max_shape=(120, 100))[0] |
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assert out.allclose(batch_out) |
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with pytest.raises(AssertionError): |
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distance2bbox( |
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batch_point, |
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batch_distance, |
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max_shape=[(120, 100), (120, 100), (32, 32)]) |
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rois = torch.zeros((0, 4)) |
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deltas = torch.zeros((0, 4)) |
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out = distance2bbox(rois, deltas, max_shape=(120, 100)) |
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assert rois.shape == out.shape |
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rois = torch.zeros((2, 0, 4)) |
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deltas = torch.zeros((2, 0, 4)) |
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out = distance2bbox(rois, deltas, max_shape=(120, 100)) |
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assert rois.shape == out.shape |
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