kornia--kornia
3a2c66702c
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45 行
1.5 KiB
Python
45 行
1.5 KiB
Python
# LICENSE HEADER MANAGED BY add-license-header
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#
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# Copyright 2018 Kornia Team
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import pytest
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import torch
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import kornia
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from testing.base import BaseTester
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class TestEdgeDetector(BaseTester):
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@pytest.mark.slow
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def test_smoke(self, device, dtype):
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img = torch.rand(2, 3, 64, 64, device=device, dtype=dtype)
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net = kornia.contrib.EdgeDetectorBuilder.build(pretrained=False).to(device, dtype)
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out = net(img)
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# ResizePostProcessor returns a list, so we need to handle that
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if isinstance(out, list):
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assert len(out) == 2
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assert all(item.shape == (1, 1, 64, 64) for item in out)
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else:
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assert out.shape == (2, 1, 64, 64)
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@pytest.mark.slow
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@pytest.mark.skip(reason="issue with `ClassVar[list[int]]`")
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def test_jit(self, device, dtype):
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op = kornia.contrib.EdgeDetectorBuilder.build(pretrained=False).to(device, dtype)
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op_jit = torch.jit.script(op)
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assert op_jit is not None
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