mirror of
https://github.com/open-mmlab/mmcv.git
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d5cbf7eed1
* migrate op * migrate unittest * update build no torch * add back use_torch_vision for roi align * fix type and unit test * ignore test logging when no torch * fix no torch ci test * skip test registry * remove coverage report when no torch * fix mac ci order * install latest pillow when no torch * mv convws to brisk
53 lines
1.4 KiB
Python
53 lines
1.4 KiB
Python
# Copyright (c) Open-MMLab. All rights reserved.
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import numpy as np
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import pytest
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from numpy.testing import assert_array_equal
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import mmcv
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try:
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import torch
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except ImportError:
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torch = None
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@pytest.mark.skipif(torch is None, reason='requires torch library')
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def test_tensor2imgs():
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# test tensor obj
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with pytest.raises(AssertionError):
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tensor = np.random.rand(2, 3, 3)
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mmcv.tensor2imgs(tensor)
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# test tensor ndim
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with pytest.raises(AssertionError):
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tensor = torch.randn(2, 3, 3)
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mmcv.tensor2imgs(tensor)
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# test mean length
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with pytest.raises(AssertionError):
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tensor = torch.randn(2, 3, 5, 5)
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mmcv.tensor2imgs(tensor, mean=(1, ))
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# test std length
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with pytest.raises(AssertionError):
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tensor = torch.randn(2, 3, 5, 5)
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mmcv.tensor2imgs(tensor, std=(1, ))
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# test rgb=True
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tensor = torch.randn(2, 3, 5, 5)
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gts = [
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t.cpu().numpy().transpose(1, 2, 0).astype(np.uint8)
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for t in tensor.flip(1)
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]
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outputs = mmcv.tensor2imgs(tensor, to_rgb=True)
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for gt, output in zip(gts, outputs):
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assert_array_equal(gt, output)
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# test rgb=False
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tensor = torch.randn(2, 3, 5, 5)
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gts = [t.cpu().numpy().transpose(1, 2, 0).astype(np.uint8) for t in tensor]
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outputs = mmcv.tensor2imgs(tensor, to_rgb=False)
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for gt, output in zip(gts, outputs):
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assert_array_equal(gt, output)
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