Merge branch 'master' of github.com:open-mmlab/mmdetection into dcn_cpp_extension

mmdet/models/detectors/faster_rcnn.py

 from .two_stage import TwoStageDetector
+from ..registry import DETECTORS
 
 
+@DETECTORS.register_module
 class FasterRCNN(TwoStageDetector):
 
     def __init__(self,

mmdet/models/detectors/mask_rcnn.py

 from .two_stage import TwoStageDetector
+from ..registry import DETECTORS
 
 
+@DETECTORS.register_module
 class MaskRCNN(TwoStageDetector):
 
     def __init__(self,

mmdet/models/detectors/retinanet.py

 from .single_stage import SingleStageDetector
+from ..registry import DETECTORS
 
 
+@DETECTORS.register_module
 class RetinaNet(SingleStageDetector):
 
     def __init__(self,

mmdet/models/detectors/rpn.py

@@ -4,8 +4,10 @@ from mmdet.core import tensor2imgs, bbox_mapping
 from .base import BaseDetector
 from .test_mixins import RPNTestMixin
 from .. import builder
+from ..registry import DETECTORS
 
 
+@DETECTORS.register_module
 class RPN(BaseDetector, RPNTestMixin):
 
     def __init__(self,
@@ -18,7 +20,7 @@ class RPN(BaseDetector, RPNTestMixin):
         super(RPN, self).__init__()
         self.backbone = builder.build_backbone(backbone)
         self.neck = builder.build_neck(neck) if neck is not None else None
-        self.rpn_head = builder.build_anchor_head(rpn_head)
+        self.rpn_head = builder.build_head(rpn_head)
         self.train_cfg = train_cfg
         self.test_cfg = test_cfg
         self.init_weights(pretrained=pretrained)

mmdet/models/detectors/single_stage.py

@@ -2,9 +2,11 @@ import torch.nn as nn
 
 from .base import BaseDetector
 from .. import builder
+from ..registry import DETECTORS
 from mmdet.core import bbox2result
 
 
+@DETECTORS.register_module
 class SingleStageDetector(BaseDetector):
 
     def __init__(self,
@@ -18,7 +20,7 @@ class SingleStageDetector(BaseDetector):
         self.backbone = builder.build_backbone(backbone)
         if neck is not None:
             self.neck = builder.build_neck(neck)
-        self.bbox_head = builder.build_anchor_head(bbox_head)
+        self.bbox_head = builder.build_head(bbox_head)
         self.train_cfg = train_cfg
         self.test_cfg = test_cfg
         self.init_weights(pretrained=pretrained)

mmdet/models/detectors/two_stage.py

@@ -4,9 +4,11 @@ import torch.nn as nn
 from .base import BaseDetector
 from .test_mixins import RPNTestMixin, BBoxTestMixin, MaskTestMixin
 from .. import builder
+from ..registry import DETECTORS
 from mmdet.core import bbox2roi, bbox2result, build_assigner, build_sampler
 
 
+@DETECTORS.register_module
 class TwoStageDetector(BaseDetector, RPNTestMixin, BBoxTestMixin,
                        MaskTestMixin):
 
@@ -30,17 +32,17 @@ class TwoStageDetector(BaseDetector, RPNTestMixin, BBoxTestMixin,
             raise NotImplementedError
 
         if rpn_head is not None:
-            self.rpn_head = builder.build_anchor_head(rpn_head)
+            self.rpn_head = builder.build_head(rpn_head)
 
         if bbox_head is not None:
             self.bbox_roi_extractor = builder.build_roi_extractor(
                 bbox_roi_extractor)
-            self.bbox_head = builder.build_bbox_head(bbox_head)
+            self.bbox_head = builder.build_head(bbox_head)
 
         if mask_head is not None:
             self.mask_roi_extractor = builder.build_roi_extractor(
                 mask_roi_extractor)
-            self.mask_head = builder.build_mask_head(mask_head)
+            self.mask_head = builder.build_head(mask_head)
 
         self.train_cfg = train_cfg
         self.test_cfg = test_cfg

mmdet/models/mask_heads/fcn_mask_head.py

@@ -4,10 +4,12 @@ import pycocotools.mask as mask_util
 import torch
 import torch.nn as nn
 
+from ..registry import HEADS
 from ..utils import ConvModule
 from mmdet.core import mask_cross_entropy, mask_target
 
 
+@HEADS.register_module
 class FCNMaskHead(nn.Module):
 
     def __init__(self,

mmdet/models/necks/fpn.py

 import torch.nn as nn
 import torch.nn.functional as F
-from ..utils import ConvModule
 from mmcv.cnn import xavier_init
 
+from ..utils import ConvModule
+from ..registry import NECKS
+
 
+@NECKS.register_module
 class FPN(nn.Module):
 
     def __init__(self,

mmdet/models/registry.py

+import torch.nn as nn
+
+
+class Registry(object):
+
+    def __init__(self, name):
+        self._name = name
+        self._module_dict = dict()
+
+    @property
+    def name(self):
+        return self._name
+
+    @property
+    def module_dict(self):
+        return self._module_dict
+
+    def _register_module(self, module_class):
+        """Register a module.
+
+        Args:
+            module (:obj:`nn.Module`): Module to be registered.
+        """
+        if not issubclass(module_class, nn.Module):
+            raise TypeError(
+                'module must be a child of nn.Module, but got {}'.format(
+                    type(module_class)))
+        module_name = module_class.__name__
+        if module_name in self._module_dict:
+            raise KeyError('{} is already registered in {}'.format(
+                module_name, self.name))
+        self._module_dict[module_name] = module_class
+
+    def register_module(self, cls):
+        self._register_module(cls)
+        return cls
+
+
+BACKBONES = Registry('backbone')
+NECKS = Registry('neck')
+ROI_EXTRACTORS = Registry('roi_extractor')
+HEADS = Registry('head')
+DETECTORS = Registry('detector')

mmdet/models/roi_extractors/single_level.py

@@ -4,8 +4,10 @@ import torch
 import torch.nn as nn
 
 from mmdet import ops
+from ..registry import ROI_EXTRACTORS
 
 
+@ROI_EXTRACTORS.register_module
 class SingleRoIExtractor(nn.Module):
     """Extract RoI features from a single level feature map.
 

setup.py

@@ -5,14 +5,14 @@ from setuptools import find_packages, setup
 
 
 def readme():
-    with open('README.md') as f:
+    with open('README.md', encoding='utf-8') as f:
         content = f.read()
     return content
 
 
 MAJOR = 0
 MINOR = 5
-PATCH = 5
+PATCH = 6
 SUFFIX = ''
 SHORT_VERSION = '{}.{}.{}{}'.format(MAJOR, MINOR, PATCH, SUFFIX)
 
@@ -89,7 +89,7 @@ if __name__ == '__main__':
         long_description=readme(),
         keywords='computer vision, object detection',
         url='https://github.com/open-mmlab/mmdetection',
-        packages=find_packages(exclude=('configs', 'tools', 'demo',)),
+        packages=find_packages(exclude=('configs', 'tools', 'demo')),
         package_data={'mmdet.ops': ['*/*.so']},
         classifiers=[
             'Development Status :: 4 - Beta',