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import numpy as np
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import torch
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from mmaction.structures import bbox2result
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def test_bbox2result():
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bboxes = torch.tensor([[0.072, 0.47, 0.84, 0.898],
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[0.23, 0.215, 0.781, 0.534],
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[0.195, 0.128, 0.643, 0.944],
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[0.236, 0.189, 0.689, 0.74],
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[0.375, 0.371, 0.726, 0.804],
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[0.024, 0.398, 0.776, 0.719]])
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labels = torch.tensor([[-1.650, 0.515, 0.798, 1.240],
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[1.368, -1.128, 0.037, -1.087],
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[0.481, -1.303, 0.501, -0.463],
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[-0.356, 0.126, -0.840, 0.438],
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[0.079, 1.269, -0.263, -0.538],
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[-0.853, 0.391, 0.103, 0.398]])
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num_classes = 4
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result = bbox2result(bboxes, labels, num_classes)
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assert np.all(
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np.isclose(
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result[0],
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np.array([[0.072, 0.47, 0.84, 0.898, 0.515],
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[0.236, 0.189, 0.689, 0.74, 0.126],
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[0.375, 0.371, 0.726, 0.804, 1.269],
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[0.024, 0.398, 0.776, 0.719, 0.391]])))
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assert np.all(
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np.isclose(
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result[1],
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np.array([[0.072, 0.47, 0.84, 0.898, 0.798],
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[0.23, 0.215, 0.781, 0.534, 0.037],
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[0.195, 0.128, 0.643, 0.944, 0.501],
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[0.024, 0.398, 0.776, 0.719, 0.103]])))
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assert np.all(
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np.isclose(
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result[2],
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np.array([[0.072, 0.47, 0.84, 0.898, 1.24],
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[0.236, 0.189, 0.689, 0.74, 0.438],
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[0.024, 0.398, 0.776, 0.719, 0.398]])))
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result = bbox2result(bboxes, labels, num_classes, -1.0)
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assert np.all(
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np.isclose(result[0], np.array([[0.375, 0.371, 0.726, 0.804, 1.269]])))
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assert np.all(
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np.isclose(
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result[1],
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np.array([[0.23, 0.215, 0.781, 0.534, 0.037],
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[0.195, 0.128, 0.643, 0.944, 0.501]])))
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assert np.all(
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np.isclose(
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result[2],
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np.array([[0.072, 0.47, 0.84, 0.898, 1.240],
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[0.236, 0.189, 0.689, 0.74, 0.438],
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[0.024, 0.398, 0.776, 0.719, 0.398]])))
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