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- # Copyright (c) 2020 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.
- from __future__ import absolute_import
- from __future__ import division
- from __future__ import print_function
- import paddle
- from ppdet.core.workspace import register, create
- from .meta_arch import BaseArch
- __all__ = ['FCOS']
- @register
- class FCOS(BaseArch):
- """
- FCOS network, see https://arxiv.org/abs/1904.01355
- Args:
- backbone (object): backbone instance
- neck (object): 'FPN' instance
- fcos_head (object): 'FCOSHead' instance
- post_process (object): 'FCOSPostProcess' instance
- """
- __category__ = 'architecture'
- __inject__ = ['fcos_post_process']
- def __init__(self,
- backbone,
- neck,
- fcos_head='FCOSHead',
- fcos_post_process='FCOSPostProcess'):
- super(FCOS, self).__init__()
- self.backbone = backbone
- self.neck = neck
- self.fcos_head = fcos_head
- self.fcos_post_process = fcos_post_process
- @classmethod
- def from_config(cls, cfg, *args, **kwargs):
- backbone = create(cfg['backbone'])
- kwargs = {'input_shape': backbone.out_shape}
- neck = create(cfg['neck'], **kwargs)
- kwargs = {'input_shape': neck.out_shape}
- fcos_head = create(cfg['fcos_head'], **kwargs)
- return {
- 'backbone': backbone,
- 'neck': neck,
- "fcos_head": fcos_head,
- }
- def _forward(self):
- body_feats = self.backbone(self.inputs)
- fpn_feats = self.neck(body_feats)
- fcos_head_outs = self.fcos_head(fpn_feats, self.training)
- if not self.training:
- scale_factor = self.inputs['scale_factor']
- bboxes = self.fcos_post_process(fcos_head_outs, scale_factor)
- return bboxes
- else:
- return fcos_head_outs
- def get_loss(self, ):
- loss = {}
- tag_labels, tag_bboxes, tag_centerness = [], [], []
- for i in range(len(self.fcos_head.fpn_stride)):
- # labels, reg_target, centerness
- k_lbl = 'labels{}'.format(i)
- if k_lbl in self.inputs:
- tag_labels.append(self.inputs[k_lbl])
- k_box = 'reg_target{}'.format(i)
- if k_box in self.inputs:
- tag_bboxes.append(self.inputs[k_box])
- k_ctn = 'centerness{}'.format(i)
- if k_ctn in self.inputs:
- tag_centerness.append(self.inputs[k_ctn])
- fcos_head_outs = self._forward()
- loss_fcos = self.fcos_head.get_loss(fcos_head_outs, tag_labels,
- tag_bboxes, tag_centerness)
- loss.update(loss_fcos)
- total_loss = paddle.add_n(list(loss.values()))
- loss.update({'loss': total_loss})
- return loss
- def get_pred(self):
- bbox_pred, bbox_num = self._forward()
- output = {'bbox': bbox_pred, 'bbox_num': bbox_num}
- return output
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