更换文档检测模型

paddle_detection/ppdet/modeling/architectures/ttfnet.py

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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__ = ['TTFNet']
+
+
+@register
+class TTFNet(BaseArch):
+    """
+    TTFNet network, see https://arxiv.org/abs/1909.00700
+
+    Args:
+        backbone (object): backbone instance
+        neck (object): 'TTFFPN' instance
+        ttf_head (object): 'TTFHead' instance
+        post_process (object): 'BBoxPostProcess' instance
+    """
+
+    __category__ = 'architecture'
+    __inject__ = ['post_process']
+
+    def __init__(self,
+                 backbone='DarkNet',
+                 neck='TTFFPN',
+                 ttf_head='TTFHead',
+                 post_process='BBoxPostProcess'):
+        super(TTFNet, self).__init__()
+        self.backbone = backbone
+        self.neck = neck
+        self.ttf_head = ttf_head
+        self.post_process = 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}
+        ttf_head = create(cfg['ttf_head'], **kwargs)
+
+        return {
+            'backbone': backbone,
+            'neck': neck,
+            "ttf_head": ttf_head,
+        }
+
+    def _forward(self):
+        body_feats = self.backbone(self.inputs)
+        body_feats = self.neck(body_feats)
+        hm, wh = self.ttf_head(body_feats)
+        if self.training:
+            return hm, wh
+        else:
+            bbox, bbox_num = self.post_process(hm, wh, self.inputs['im_shape'],
+                                               self.inputs['scale_factor'])
+            return bbox, bbox_num
+
+    def get_loss(self, ):
+        loss = {}
+        heatmap = self.inputs['ttf_heatmap']
+        box_target = self.inputs['ttf_box_target']
+        reg_weight = self.inputs['ttf_reg_weight']
+        hm, wh = self._forward()
+        head_loss = self.ttf_head.get_loss(hm, wh, heatmap, box_target,
+                                           reg_weight)
+        loss.update(head_loss)
+        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