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https://github.com/open-mmlab/mmcv.git
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2623fbf21c
* add pixel group ops * reformatting * formatting&rm auto * Add citation * Add contour expand * c++ linting * Add unit tests with Tensor * rm model.pth * rename * c++ linting * c++ linting * Rename variables
49 lines
2.5 KiB
Python
49 lines
2.5 KiB
Python
import numpy as np
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import torch
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def test_contour_expand():
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from mmcv.ops import contour_expand
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np_internal_kernel_label = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 1, 1, 0, 0, 0, 0, 2, 0],
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[0, 0, 1, 1, 0, 0, 0, 0, 2, 0],
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[0, 0, 1, 1, 0, 0, 0, 0, 2, 0],
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[0, 0, 1, 1, 0, 0, 0, 0, 2, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0,
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0]]).astype(np.int32)
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np_kernel_mask1 = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 1, 1, 1, 1, 1, 1, 1, 0],
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[0, 0, 1, 1, 1, 1, 1, 1, 1, 0],
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[0, 0, 1, 1, 1, 1, 1, 1, 1, 0],
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[0, 0, 1, 1, 1, 1, 1, 1, 1, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0,
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0]]).astype(np.uint8)
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np_kernel_mask2 = (np_internal_kernel_label > 0).astype(np.uint8)
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np_kernel_mask = np.stack([np_kernel_mask1, np_kernel_mask2])
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min_area = 1
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kernel_region_num = 3
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result = contour_expand(np_kernel_mask, np_internal_kernel_label, min_area,
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kernel_region_num)
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gt = [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 1, 2, 2, 2, 0],
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[0, 0, 1, 1, 1, 1, 2, 2, 2, 0], [0, 0, 1, 1, 1, 1, 2, 2, 2, 0],
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[0, 0, 1, 1, 1, 1, 2, 2, 2, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
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assert np.allclose(result, gt)
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np_kernel_mask_t = torch.from_numpy(np_kernel_mask)
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np_internal_kernel_label_t = torch.from_numpy(np_internal_kernel_label)
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result = contour_expand(np_kernel_mask_t, np_internal_kernel_label_t,
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min_area, kernel_region_num)
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assert np.allclose(result, gt)
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