119 lines
3.9 KiB
Python
119 lines
3.9 KiB
Python
# Copyright (c) 2021 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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import paddle
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from .meta_arch import BaseArch
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from ppdet.core.workspace import register, create
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__all__ = ['DETR']
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# Deformable DETR, DINO use the same architecture as DETR
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@register
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class DETR(BaseArch):
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__category__ = 'architecture'
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__inject__ = ['post_process', 'post_process_semi']
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__shared__ = ['with_mask', 'exclude_post_process']
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def __init__(self,
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backbone,
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transformer='DETRTransformer',
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detr_head='DETRHead',
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neck=None,
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post_process='DETRPostProcess',
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post_process_semi=None,
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with_mask=False,
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exclude_post_process=False):
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super(DETR, self).__init__()
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self.backbone = backbone
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self.transformer = transformer
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self.detr_head = detr_head
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self.neck = neck
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self.post_process = post_process
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self.with_mask = with_mask
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self.exclude_post_process = exclude_post_process
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self.post_process_semi = post_process_semi
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@classmethod
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def from_config(cls, cfg, *args, **kwargs):
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# backbone
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backbone = create(cfg['backbone'])
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# neck
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kwargs = {'input_shape': backbone.out_shape}
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neck = create(cfg['neck'], **kwargs) if cfg['neck'] else None
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# transformer
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if neck is not None:
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kwargs = {'input_shape': neck.out_shape}
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transformer = create(cfg['transformer'], **kwargs)
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# head
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kwargs = {
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'hidden_dim': transformer.hidden_dim,
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'nhead': transformer.nhead,
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'input_shape': backbone.out_shape
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}
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detr_head = create(cfg['detr_head'], **kwargs)
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return {
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'backbone': backbone,
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'transformer': transformer,
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"detr_head": detr_head,
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"neck": neck
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}
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def _forward(self):
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# Backbone
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body_feats = self.backbone(self.inputs)
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# Neck
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if self.neck is not None:
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body_feats = self.neck(body_feats)
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# Transformer
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pad_mask = self.inputs.get('pad_mask', None)
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out_transformer = self.transformer(body_feats, pad_mask, self.inputs)
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# DETR Head
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if self.training:
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detr_losses = self.detr_head(out_transformer, body_feats,
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self.inputs)
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detr_losses.update({
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'loss': paddle.add_n(
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[v for k, v in detr_losses.items() if 'log' not in k])
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})
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return detr_losses
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else:
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preds = self.detr_head(out_transformer, body_feats)
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if self.exclude_post_process:
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bbox, bbox_num, mask = preds
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else:
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bbox, bbox_num, mask = self.post_process(
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preds, self.inputs['im_shape'], self.inputs['scale_factor'],
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paddle.shape(self.inputs['image'])[2:])
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output = {'bbox': bbox, 'bbox_num': bbox_num}
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if self.with_mask:
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output['mask'] = mask
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return output
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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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