85 lines
2.8 KiB
Python
85 lines
2.8 KiB
Python
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from ppdet.core.workspace import register, create
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from .meta_arch import BaseArch
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import paddle
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import paddle.nn.functional as F
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__all__ = ['RetinaNet']
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@register
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class RetinaNet(BaseArch):
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__category__ = 'architecture'
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def __init__(self, backbone, neck, head):
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super(RetinaNet, self).__init__()
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self.backbone = backbone
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self.neck = neck
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self.head = head
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@classmethod
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def from_config(cls, cfg, *args, **kwargs):
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backbone = create(cfg['backbone'])
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kwargs = {'input_shape': backbone.out_shape}
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neck = create(cfg['neck'], **kwargs)
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kwargs = {'input_shape': neck.out_shape}
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head = create(cfg['head'], **kwargs)
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return {
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'backbone': backbone,
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'neck': neck,
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'head': head,
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}
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def _forward(self):
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body_feats = self.backbone(self.inputs)
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neck_feats = self.neck(body_feats)
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if self.training:
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return self.head(neck_feats, self.inputs)
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else:
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head_outs = self.head(neck_feats)
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bbox, bbox_num, nms_keep_idx = self.head.post_process(
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head_outs, self.inputs['im_shape'], self.inputs['scale_factor'])
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if self.use_extra_data:
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extra_data = {} # record the bbox output before nms, such like scores and nms_keep_idx
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"""extra_data:{
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'scores': predict scores,
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'nms_keep_idx': bbox index before nms,
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}
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"""
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preds_logits = self.head.decode_cls_logits(head_outs[0])
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preds_scores = F.sigmoid(preds_logits)
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extra_data['logits'] = preds_logits
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extra_data['scores'] = preds_scores
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extra_data['nms_keep_idx'] = nms_keep_idx # bbox index before nms
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return {'bbox': bbox, 'bbox_num': bbox_num, "extra_data": extra_data}
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else:
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return {'bbox': bbox, 'bbox_num': bbox_num}
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def get_loss(self):
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return self._forward()
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def get_pred(self):
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return self._forward()
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