46 lines
1.6 KiB
Python
46 lines
1.6 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from unittest import TestCase
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import torch
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from mmengine.data import PixelData
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from mmseg.models import SegDataPreProcessor
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from mmseg.structures import SegDataSample
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class TestSegDataPreProcessor(TestCase):
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def test_init(self):
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# test mean is None
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processor = SegDataPreProcessor()
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self.assertTrue(not hasattr(processor, 'mean'))
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self.assertTrue(processor._enable_normalize is False)
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# test mean is not None
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processor = SegDataPreProcessor(mean=[0, 0, 0], std=[1, 1, 1])
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self.assertTrue(hasattr(processor, 'mean'))
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self.assertTrue(hasattr(processor, 'std'))
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self.assertTrue(processor._enable_normalize)
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# please specify both mean and std
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with self.assertRaises(AssertionError):
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SegDataPreProcessor(mean=[0, 0, 0])
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# bgr2rgb and rgb2bgr cannot be set to True at the same time
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with self.assertRaises(AssertionError):
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SegDataPreProcessor(bgr_to_rgb=True, rgb_to_bgr=True)
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def test_forward(self):
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data_sample = SegDataSample()
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data_sample.gt_sem_seg = PixelData(
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**{'data': torch.randint(0, 10, (1, 11, 10))})
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processor = SegDataPreProcessor(
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mean=[0, 0, 0], std=[1, 1, 1], size=(20, 20))
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data = {
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'inputs': torch.randint(0, 256, (3, 11, 10)),
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'data_sample': data_sample
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}
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inputs, data_samples = processor([data, data], training=True)
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self.assertEqual(inputs.shape, (2, 3, 20, 20))
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self.assertEqual(len(data_samples), 2)
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