forked from mindspore-Ecosystem/mindspore
58 lines
1.9 KiB
Python
58 lines
1.9 KiB
Python
# Copyright 2020 Huawei Technologies Co., Ltd
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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 numpy as np
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import pytest
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import mindspore
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore.ops import operations as P
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class NetIOU(nn.Cell):
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def __init__(self, mode):
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super(NetIOU, self).__init__()
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self.encode = P.IOU(mode=mode)
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def construct(self, anchor, groundtruth):
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return self.encode(anchor, groundtruth)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_iou():
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pos1 = [101, 169, 246, 429]
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pos2 = [121, 138, 304, 374]
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mode = "iou"
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pos1_box = Tensor(np.array(pos1).reshape(1, 4), mindspore.float32)
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pos2_box = Tensor(np.array(pos2).reshape(1, 4), mindspore.float32)
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expect_result = np.array(0.46551168, np.float32)
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error = np.ones(shape=[1]) * 1.0e-6
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context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
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overlaps = NetIOU(mode)
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output = overlaps(pos1_box, pos2_box)
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diff = output.asnumpy() - expect_result
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assert np.all(abs(diff) < error)
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context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU')
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overlaps = NetIOU(mode)
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output = overlaps(pos1_box, pos2_box)
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diff = output.asnumpy() - expect_result
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assert np.all(abs(diff) < error)
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