85 lines
2.9 KiB
Python
85 lines
2.9 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 numpy as np
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from mo.front.caffe.extractors.utils import get_canonical_axis_index
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from mo.front.common.layout import get_batch_dim, get_height_dim, get_width_dim, shape_for_layout
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from mo.front.extractor import attr_getter
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from mo.graph.graph import Node, Graph
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from mo.ops.op import Op
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class RegionYoloOp(Op):
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op = 'RegionYolo'
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def __init__(self, graph: Graph, attrs: Node):
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mandatory_props = {
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'type': __class__.op,
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'op': __class__.op,
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'version': 'opset1',
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'in_ports_count': 1,
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'out_ports_count': 1,
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'infer': RegionYoloOp.regionyolo_infer
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}
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super().__init__(graph, mandatory_props, attrs)
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def supported_attrs(self):
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return [
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'coords',
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'classes',
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'num',
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'axis',
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'end_axis',
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'do_softmax',
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'anchors',
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'mask'
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]
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def backend_attrs(self):
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return [
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'coords',
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'classes',
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'num',
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'axis',
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'end_axis',
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'do_softmax',
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('anchors', lambda node: attr_getter(node, 'anchors')),
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('mask', lambda node: attr_getter(node, 'mask'))
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]
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@staticmethod
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def regionyolo_infer(node: Node):
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input_shape = node.in_node(0).shape
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if input_shape is None:
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return
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axis = get_canonical_axis_index(input_shape, node.axis)
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end_axis = get_canonical_axis_index(input_shape, node.end_axis)
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node.axis = axis
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node.end_axis = end_axis
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if node.do_softmax:
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flat_dim = np.prod(input_shape[axis: end_axis + 1])
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node.out_node().shape = np.array([*input_shape[:axis], flat_dim, *input_shape[end_axis + 1:]])
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else:
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layout = node.graph.graph['layout']
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assert len(layout) == 4
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node.out_node().shape = shape_for_layout(layout,
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batch=input_shape[get_batch_dim(layout, 4)],
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features=(node.classes + node.coords + 1) * len(node.mask),
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height=input_shape[get_height_dim(layout, 4)],
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width=input_shape[get_width_dim(layout, 4)])
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