更换文档检测模型

paddle_detection/ppdet/modeling/architectures/ssd.py

@@ -0,0 +1,118 @@
+# 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
+
+from ppdet.core.workspace import register, create
+from .meta_arch import BaseArch
+import paddle
+import paddle.nn.functional as F
+
+__all__ = ['SSD']
+
+
+@register
+class SSD(BaseArch):
+    """
+    Single Shot MultiBox Detector, see https://arxiv.org/abs/1512.02325
+
+    Args:
+        backbone (nn.Layer): backbone instance
+        ssd_head (nn.Layer): `SSDHead` instance
+        post_process (object): `BBoxPostProcess` instance
+    """
+
+    __category__ = 'architecture'
+    __inject__ = ['post_process']
+
+    def __init__(self, backbone, ssd_head, post_process, r34_backbone=False):
+        super(SSD, self).__init__()
+        self.backbone = backbone
+        self.ssd_head = ssd_head
+        self.post_process = post_process
+        self.r34_backbone = r34_backbone
+        if self.r34_backbone:
+            from ppdet.modeling.backbones.resnet import ResNet
+            assert isinstance(self.backbone, ResNet) and \
+                   self.backbone.depth == 34, \
+                "If you set r34_backbone=True, please use ResNet-34 as backbone."
+            self.backbone.res_layers[2].blocks[0].branch2a.conv._stride = [1, 1]
+            self.backbone.res_layers[2].blocks[0].short.conv._stride = [1, 1]
+
+    @classmethod
+    def from_config(cls, cfg, *args, **kwargs):
+        # backbone
+        backbone = create(cfg['backbone'])
+
+        # head
+        kwargs = {'input_shape': backbone.out_shape}
+        ssd_head = create(cfg['ssd_head'], **kwargs)
+
+        return {
+            'backbone': backbone,
+            "ssd_head": ssd_head,
+        }
+
+    def _forward(self):
+        # Backbone
+        body_feats = self.backbone(self.inputs)
+
+        # SSD Head
+        if self.training:
+            return self.ssd_head(body_feats, self.inputs['image'],
+                                 self.inputs['gt_bbox'],
+                                 self.inputs['gt_class'])
+        else:
+            preds, anchors = self.ssd_head(body_feats, self.inputs['image'])
+            bbox, bbox_num, nms_keep_idx = self.post_process(
+                preds, anchors, self.inputs['im_shape'],
+                self.inputs['scale_factor'])
+
+            if self.use_extra_data:
+                extra_data = {}  # record the bbox output before nms, such like scores and nms_keep_idx
+                """extra_data:{
+                            'scores': predict scores,
+                            'nms_keep_idx': bbox index before nms,
+                           }
+                           """
+                preds_logits = preds[1]  # [[1xNumBBoxNumClass]]
+                extra_data['scores'] = F.softmax(paddle.concat(
+                    preds_logits, axis=1)).transpose([0, 2, 1])
+                extra_data['logits'] = paddle.concat(
+                    preds_logits, axis=1).transpose([0, 2, 1])
+                extra_data['nms_keep_idx'] = nms_keep_idx  # bbox index before nms
+                return bbox, bbox_num, extra_data
+            else:
+                return bbox, bbox_num
+
+    def get_loss(self, ):
+        return {"loss": self._forward()}
+
+    def get_pred(self):
+        if self.use_extra_data:
+            bbox_pred, bbox_num, extra_data = self._forward()
+            output = {
+                "bbox": bbox_pred,
+                "bbox_num": bbox_num,
+                "extra_data": extra_data
+            }
+        else:
+            bbox_pred, bbox_num = self._forward()
+            output = {
+                "bbox": bbox_pred,
+                "bbox_num": bbox_num,
+            }
+        return output