2 Copyright (c) 2019 Intel Corporation
4 Licensed under the Apache License, Version 2.0 (the "License");
5 you may not use this file except in compliance with the License.
6 You may obtain a copy of the License at
8 http://www.apache.org/licenses/LICENSE-2.0
10 Unless required by applicable law or agreed to in writing, software
11 distributed under the License is distributed on an "AS IS" BASIS,
12 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 See the License for the specific language governing permissions and
14 limitations under the License.
19 from mo.front.common.partial_infer.utils import int64_array
20 from mo.ops.op import Op
23 class ExperimentalDetectronDetectionOutput(Op):
24 op = 'ExperimentalDetectronDetectionOutput'
27 def __init__(self, graph, attrs):
28 mandatory_props = dict(
31 infer=__class__.infer,
36 super().__init__(graph, mandatory_props, attrs)
38 def backend_attrs(self):
40 'class_agnostic_box_regression',
41 'max_detections_per_image',
47 ('deltas_weights', lambda node: ','.join(map(str, node['deltas_weights'])))]
51 rois_num = node.max_detections_per_image
53 node.out_node(0).shape = np.array([rois_num, 4], dtype=np.int64)
54 # classes, scores, batch indices
55 for port_ind in range(1, 4):
56 if not node.out_port(port_ind).disconnected():
57 node.out_port(port_ind).data.set_shape(int64_array([rois_num]))