更换文档检测模型

paddle_detection/ppdet/modeling/architectures/yolof.py

@@ -0,0 +1,88 @@
+# 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.
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from ppdet.core.workspace import register, create
+from .meta_arch import BaseArch
+
+__all__ = ['YOLOF']
+
+
+@register
+class YOLOF(BaseArch):
+    __category__ = 'architecture'
+
+    def __init__(self,
+                 backbone='ResNet',
+                 neck='DilatedEncoder',
+                 head='YOLOFHead',
+                 for_mot=False):
+        """
+        YOLOF network, see https://arxiv.org/abs/2103.09460
+
+        Args:
+            backbone (nn.Layer): backbone instance
+            neck (nn.Layer): DilatedEncoder instance
+            head (nn.Layer): YOLOFHead instance
+            for_mot (bool): whether return other features for multi-object tracking
+                models, default False in pure object detection models.
+        """
+        super(YOLOF, self).__init__()
+        self.backbone = backbone
+        self.neck = neck
+        self.head = head
+        self.for_mot = for_mot
+
+    @classmethod
+    def from_config(cls, cfg, *args, **kwargs):
+        # backbone
+        backbone = create(cfg['backbone'])
+
+        # fpn
+        kwargs = {'input_shape': backbone.out_shape}
+        neck = create(cfg['neck'], **kwargs)
+
+        # head
+        kwargs = {'input_shape': neck.out_shape}
+        head = create(cfg['head'], **kwargs)
+
+        return {
+            'backbone': backbone,
+            'neck': neck,
+            "head": head,
+        }
+
+    def _forward(self):
+        body_feats = self.backbone(self.inputs)
+        neck_feats = self.neck(body_feats, self.for_mot)
+
+        if self.training:
+            yolo_losses = self.head(neck_feats, self.inputs)
+            return yolo_losses
+        else:
+            yolo_head_outs = self.head(neck_feats)
+            bbox, bbox_num = self.head.post_process(yolo_head_outs,
+                                                    self.inputs['im_shape'],
+                                                    self.inputs['scale_factor'])
+            output = {'bbox': bbox, 'bbox_num': bbox_num}
+            return output
+
+    def get_loss(self):
+        return self._forward()
+
+    def get_pred(self):
+        return self._forward()