Pavel Esir
8c89d8d733
* added getting nms_threshold/iou_threshold from original TF RetinaNet model * iou_threshold definition added * fixed getting iou_threshold for TF NMS V2, some minor corrections * added box_encoding to NMS extractors
74 lines
2.6 KiB
Python
74 lines
2.6 KiB
Python
"""
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Copyright (C) 2018-2020 Intel Corporation
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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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http://www.apache.org/licenses/LICENSE-2.0
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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 logging as log
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import numpy as np
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from extensions.ops.non_max_suppression import NonMaxSuppression
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from mo.front.extractor import FrontExtractorOp
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class NonMaxSuppressionV2Extractor(FrontExtractorOp):
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op = 'NonMaxSuppressionV2'
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enabled = True
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@classmethod
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def extract(cls, node):
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attrs = {'sort_result_descending': 1, 'box_encoding': 'corner', 'output_type': np.int32}
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NonMaxSuppression.update_node_stat(node, attrs)
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return cls.enabled
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class NonMaxSuppressionV3Extractor(FrontExtractorOp):
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op = 'NonMaxSuppressionV3'
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enabled = True
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@classmethod
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def extract(cls, node):
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attrs = {'sort_result_descending': 1, 'box_encoding': 'corner', 'output_type': np.int32}
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NonMaxSuppression.update_node_stat(node, attrs)
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return cls.enabled
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class NonMaxSuppressionV4Extractor(FrontExtractorOp):
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op = 'NonMaxSuppressionV4'
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enabled = True
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@classmethod
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def extract(cls, node):
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pad_to_max_output_size = node.pb.attr["pad_to_max_output_size:"].b
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if not pad_to_max_output_size:
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log.warning('The attribute "pad_to_max_output_size" of node {} is equal to False which is not supported.'
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'Forcing it to be equal to True'.format(node.soft_get('name')))
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attrs = {'sort_result_descending': 1, 'box_encoding': 'corner', 'output_type': np.int32}
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NonMaxSuppression.update_node_stat(node, attrs)
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return cls.enabled
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class NonMaxSuppressionV5Extractor(FrontExtractorOp):
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op = 'NonMaxSuppressionV5'
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enabled = True
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@classmethod
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def extract(cls, node):
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pad_to_max_output_size = node.pb.attr["pad_to_max_output_size:"].b
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if not pad_to_max_output_size:
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log.warning('The attribute "pad_to_max_output_size" of node {} is equal to False which is not supported.'
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'Forcing it to be equal to True'.format(node.soft_get('name')))
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attrs = {'sort_result_descending': 1, 'box_encoding': 'corner', 'output_type': np.int32}
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NonMaxSuppression.update_node_stat(node, attrs)
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return cls.enabled
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