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- # Copyright 2020 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ============================================================================
-
- import numpy as np
- import pytest
-
- import mindspore
- import mindspore.context as context
- import mindspore.nn as nn
- from mindspore import Tensor
- from mindspore.ops import operations as P
-
-
- class NetBoundingBoxDecode(nn.Cell):
- def __init__(self, means=(0.0, 0.0, 0.0, 0.0), stds=(1.0, 1.0, 1.0, 1.0)):
- super(NetBoundingBoxDecode, self).__init__()
- self.decode = P.BoundingBoxDecode(max_shape=(768, 1280), means=means, stds=stds,
- wh_ratio_clip=0.016)
-
- def construct(self, anchor, groundtruth):
- return self.decode(anchor, groundtruth)
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_boundingbox_decode():
- anchor = np.array([[4, 1, 2, 1], [2, 2, 2, 3]], np.float32)
- deltas = np.array([[3, 1, 2, 2], [1, 2, 1, 4]], np.float32)
- means = (0.1, 0.1, 0.2, 0.2)
- stds = (2.0, 2.0, 3.0, 3.0)
- anchor_box = Tensor(anchor, mindspore.float32)
- deltas_box = Tensor(deltas, mindspore.float32)
- expect_deltas = np.array([[28.6500, 0.0000, 0.0000, 33.8500],
- [0.0000, 0.0000, 15.8663, 72.7000]], np.float32)
-
- error = np.ones(shape=[2, 4]) * 1.0e-4
-
- context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
- boundingbox_decode = NetBoundingBoxDecode(means, stds)
- output = boundingbox_decode(anchor_box, deltas_box)
- diff = output.asnumpy() - expect_deltas
- assert np.all(abs(diff) < error)
-
- context.set_context(mode=context.PYNATIVE_MODE, device_target='GPU')
- boundingbox_decode = NetBoundingBoxDecode(means, stds)
- output = boundingbox_decode(anchor_box, deltas_box)
- diff = output.asnumpy() - expect_deltas
- assert np.all(abs(diff) < error)
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