# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. # # 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 paddle class SegPostProcessor(paddle.nn.Layer): def forward(self, net_outputs): # label_map [NHW], score_map [NHWC] logit = net_outputs[0] outputs = paddle.argmax(logit, axis=1, keepdim=False, dtype='int32'), \ paddle.transpose(paddle.nn.functional.softmax(logit, axis=1), perm=[0, 2, 3, 1]) return outputs class ResPostProcessor(paddle.nn.Layer): def __init__(self, out_key=None): super(ResPostProcessor, self).__init__() self.out_key = out_key def forward(self, net_outputs): if self.out_key is not None: net_outputs = net_outputs[self.out_key] outputs = paddle.transpose(net_outputs, perm=[0, 2, 3, 1]) return outputs class InferSegNet(paddle.nn.Layer): def __init__(self, net): super(InferSegNet, self).__init__() self.net = net self.postprocessor = SegPostProcessor() def forward(self, x): net_outputs = self.net(x) outputs = self.postprocessor(net_outputs) return outputs class InferCDNet(paddle.nn.Layer): def __init__(self, net): super(InferCDNet, self).__init__() self.net = net self.postprocessor = SegPostProcessor() def forward(self, x1, x2): net_outputs = self.net(x1, x2) outputs = self.postprocessor(net_outputs) return outputs class InferResNet(paddle.nn.Layer): def __init__(self, net, out_key=None): super(InferResNet, self).__init__() self.net = net self.postprocessor = ResPostProcessor(out_key=out_key) def forward(self, x): net_outputs = self.net(x) outputs = self.postprocessor(net_outputs) return outputs