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66 lines
2.7 KiB
Python
66 lines
2.7 KiB
Python
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# Copyright (c) Alibaba, Inc. and its affiliates.
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import unittest
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import torch
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from easycv.core.evaluation.metrics import accuracy
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class AccuracyTest(unittest.TestCase):
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def test_2d(self):
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# bacth_size = 5, num_classes = 6
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pred = torch.tensor(
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[[0.1, 0.2, 0.3, 0.4, 0.5, 0.6], [0.2, 0.3, 0.4, 0.5, 0.6, 0.1],
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[0.3, 0.4, 0.5, 0.6, 0.1, 0.2], [0.4, 0.5, 0.6, 0.1, 0.2, 0.3],
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[0.1, 0.2, 0.3, 0.4, 0.5, 0.6]],
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dtype=torch.float32)
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target1 = torch.tensor([5, 4, 3, 2, 5], dtype=torch.int64)
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target2 = torch.tensor([0, 1, 2, 3, 5], dtype=torch.int64)
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res1 = accuracy(pred, target1, topk=1)
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res2 = accuracy(pred, target2, topk=(1, 5))
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self.assertEqual(len(res1), 1)
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self.assertEqual(int(res1[0].numpy()), 100)
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self.assertEqual(len(res2), 2)
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self.assertEqual(int(res2[0].numpy()), 20)
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self.assertEqual(int(res2[1].numpy()), 60)
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def test_4d(self):
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# bacth_size = 2, image_size = (3, 3), num_classes = 3
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# shape=(bacth_size, num_classes, image_size[0], image_size[1])
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pred = torch.tensor(
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[[[[0.1, 0.1, 0.1], [0.2, 0.2, 0.2], [0.1, 0.1, 0.1]],
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[[0.2, 0.2, 0.2], [0.1, 0.1, 0.1], [0.2, 0.2, 0.2]],
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[[0.01, 0.01, 0.01], [0.3, 0.3, 0.3], [0.3, 0.3, 0.3]]],
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[[[0.3, 0.3, 0.3], [0.3, 0.3, 0.3], [0.3, 0.3, 0.3]],
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[[0.1, 0.1, 0.1], [0.1, 0.1, 0.1], [0.1, 0.1, 0.1]],
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[[0.2, 0.2, 0.2], [0.2, 0.2, 0.2], [0.2, 0.2, 0.2]]]],
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dtype=torch.float32)
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target1 = torch.tensor([[[1, 1, 1], [2, 2, 2], [2, 2, 2]],
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[[0, 0, 0], [0, 0, 0], [0, 0, 0]]],
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dtype=torch.int64)
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res1 = accuracy(pred, target1, topk=1)
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self.assertEqual(len(res1), 1)
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self.assertEqual(res1[0], torch.tensor(100.0))
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target2 = torch.tensor([[[1, 1, 1], [255, 255, 255], [2, 2, 2]],
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[[2, 2, 2], [2, 2, 2], [2, 2, 2]]],
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dtype=torch.int64)
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res2 = accuracy(pred, target2, topk=(1, 2), ignore_index=255)
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self.assertEqual(len(res2), 2)
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self.assertEqual(res2, [torch.tensor(40.0), torch.tensor(100.0)])
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target3 = torch.tensor([[[255, 255, 255], [2, 2, 2], [0, 0, 0]],
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[[255, 1, 1], [255, 2, 2], [2, 2, 2]]],
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dtype=torch.int64)
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res3 = accuracy(pred, target3, topk=(1, 2))
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self.assertEqual(len(res3), 2)
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self.assertAlmostEqual(res3[0].numpy(), 16.6667, delta=0.001)
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self.assertAlmostEqual(res3[1].numpy(), 44.4444, delta=0.001)
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if __name__ == '__main__':
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unittest.main()
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