Update all registries and fix some ut problems

mmdet3d/models/dense_heads/centerpoint_head.py

@@ -10,12 +10,13 @@ from mmdet3d.core import (circle_nms, draw_heatmap_gaussian, gaussian_radius,
                           xywhr2xyxyr)
 from mmdet3d.core.post_processing import nms_bev
 from mmdet3d.models import builder
+from mmdet3d.models.builder import build_loss
 from mmdet3d.models.utils import clip_sigmoid
+from mmdet3d.registry import MODELS
 from mmdet.core import build_bbox_coder, multi_apply
-from ..builder import HEADS, build_loss
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class SeparateHead(BaseModule):
     """SeparateHead for CenterHead.
 
@@ -121,7 +122,7 @@ class SeparateHead(BaseModule):
         return ret_dict
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class DCNSeparateHead(BaseModule):
     r"""DCNSeparateHead for CenterHead.
 
@@ -240,7 +241,7 @@ class DCNSeparateHead(BaseModule):
         return ret
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class CenterHead(BaseModule):
     """CenterHead for CenterPoint.
 

mmdet3d/models/dense_heads/fcos_mono3d_head.py

@@ -9,15 +9,16 @@ from torch import nn as nn
 
 from mmdet3d.core import (box3d_multiclass_nms, limit_period, points_img2cam,
                           xywhr2xyxyr)
+from mmdet3d.models.builder import build_loss
+from mmdet3d.registry import MODELS
 from mmdet.core import multi_apply
 from mmdet.core.bbox.builder import build_bbox_coder
-from ..builder import HEADS, build_loss
 from .anchor_free_mono3d_head import AnchorFreeMono3DHead
 
 INF = 1e8
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class FCOSMono3DHead(AnchorFreeMono3DHead):
     """Anchor-free head used in FCOS3D.
 

mmdet3d/models/dense_heads/free_anchor3d_head.py

@@ -4,12 +4,12 @@ from mmcv.runner import force_fp32
 from torch.nn import functional as F
 
 from mmdet3d.core.bbox import bbox_overlaps_nearest_3d
-from ..builder import HEADS
+from mmdet3d.registry import MODELS
 from .anchor3d_head import Anchor3DHead
 from .train_mixins import get_direction_target
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class FreeAnchor3DHead(Anchor3DHead):
     r"""`FreeAnchor <https://arxiv.org/abs/1909.02466>`_ head for 3D detection.
 

mmdet3d/models/dense_heads/groupfree3d_head.py

@@ -14,8 +14,9 @@ from torch import nn as nn
 from torch.nn import functional as F
 
 from mmdet3d.core.post_processing import aligned_3d_nms
+from mmdet3d.registry import MODELS
 from mmdet.core import build_bbox_coder, multi_apply
-from ..builder import HEADS, build_loss
+from ..builder import build_loss
 from .base_conv_bbox_head import BaseConvBboxHead
 
 EPS = 1e-6
@@ -106,7 +107,7 @@ class GeneralSamplingModule(nn.Module):
         return new_xyz, new_features, sample_inds
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class GroupFree3DHead(BaseModule):
     r"""Bbox head of `Group-Free 3D <https://arxiv.org/abs/2104.00678>`_.
 

mmdet3d/models/dense_heads/monoflex_head.py

@@ -3,21 +3,22 @@ import torch
 from mmcv.cnn import xavier_init
 from torch import nn as nn
 
+from mmdet3d.core.bbox.builder import build_bbox_coder
 from mmdet3d.core.utils import get_ellip_gaussian_2D
+from mmdet3d.models.builder import build_loss
 from mmdet3d.models.model_utils import EdgeFusionModule
 from mmdet3d.models.utils import (filter_outside_objs, get_edge_indices,
                                   get_keypoints, handle_proj_objs)
+from mmdet3d.registry import MODELS
 from mmdet.core import multi_apply
-from mmdet.core.bbox.builder import build_bbox_coder
 from mmdet.models.utils import gaussian_radius, gen_gaussian_target
 from mmdet.models.utils.gaussian_target import (get_local_maximum,
                                                 get_topk_from_heatmap,
                                                 transpose_and_gather_feat)
-from ..builder import HEADS, build_loss
 from .anchor_free_mono3d_head import AnchorFreeMono3DHead
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class MonoFlexHead(AnchorFreeMono3DHead):
     r"""MonoFlex head used in `MonoFlex <https://arxiv.org/abs/2104.02323>`_
 

mmdet3d/models/dense_heads/parta2_rpn_head.py

@@ -5,11 +5,11 @@ from mmcv.runner import force_fp32
 
 from mmdet3d.core import limit_period, xywhr2xyxyr
 from mmdet3d.core.post_processing import nms_bev, nms_normal_bev
-from ..builder import HEADS
+from mmdet3d.registry import MODELS
 from .anchor3d_head import Anchor3DHead
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class PartA2RPNHead(Anchor3DHead):
     """RPN head for PartA2.
 

mmdet3d/models/dense_heads/pgd_head.py

@@ -8,12 +8,13 @@ from torch.nn import functional as F
 
 from mmdet3d.core import box3d_multiclass_nms, xywhr2xyxyr
 from mmdet3d.core.bbox import points_cam2img, points_img2cam
+from mmdet3d.models.builder import build_loss
+from mmdet3d.registry import MODELS
 from mmdet.core import distance2bbox, multi_apply
-from ..builder import HEADS, build_loss
 from .fcos_mono3d_head import FCOSMono3DHead
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class PGDHead(FCOSMono3DHead):
     r"""Anchor-free head used in `PGD <https://arxiv.org/abs/2107.14160>`_.
 

mmdet3d/models/dense_heads/point_rpn_head.py

@@ -7,11 +7,12 @@ from mmdet3d.core import xywhr2xyxyr
 from mmdet3d.core.bbox.structures import (DepthInstance3DBoxes,
                                           LiDARInstance3DBoxes)
 from mmdet3d.core.post_processing import nms_bev, nms_normal_bev
+from mmdet3d.models.builder import build_loss
+from mmdet3d.registry import MODELS
 from mmdet.core import build_bbox_coder, multi_apply
-from ..builder import HEADS, build_loss
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class PointRPNHead(BaseModule):
     """RPN module for PointRCNN.
 

mmdet3d/models/dense_heads/shape_aware_head.py

@@ -8,12 +8,13 @@ from mmcv.runner import BaseModule
 from torch import nn as nn
 
 from mmdet3d.core import box3d_multiclass_nms, limit_period, xywhr2xyxyr
+from mmdet3d.registry import MODELS
 from mmdet.core import multi_apply
-from ..builder import HEADS, build_head
+from ..builder import build_head
 from .anchor3d_head import Anchor3DHead
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class BaseShapeHead(BaseModule):
     """Base Shape-aware Head in Shape Signature Network.
 
@@ -164,7 +165,7 @@ class BaseShapeHead(BaseModule):
         return ret
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class ShapeAwareHead(Anchor3DHead):
     """Shape-aware grouping head for SSN.
 

mmdet3d/models/dense_heads/smoke_mono3d_head.py

@@ -2,17 +2,17 @@
 import torch
 from torch.nn import functional as F
 
+from mmdet3d.registry import MODELS
 from mmdet.core import multi_apply
 from mmdet.core.bbox.builder import build_bbox_coder
 from mmdet.models.utils import gaussian_radius, gen_gaussian_target
 from mmdet.models.utils.gaussian_target import (get_local_maximum,
                                                 get_topk_from_heatmap,
                                                 transpose_and_gather_feat)
-from ..builder import HEADS
 from .anchor_free_mono3d_head import AnchorFreeMono3DHead
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class SMOKEMono3DHead(AnchorFreeMono3DHead):
     r"""Anchor-free head used in `SMOKE <https://arxiv.org/abs/2002.10111>`_
 

mmdet3d/models/dense_heads/ssd_3d_head.py

@@ -7,12 +7,13 @@ from torch.nn import functional as F
 from mmdet3d.core.bbox.structures import (DepthInstance3DBoxes,
                                           LiDARInstance3DBoxes,
                                           rotation_3d_in_axis)
+from mmdet3d.registry import MODELS
 from mmdet.core import multi_apply
-from ..builder import HEADS, build_loss
+from ..builder import build_loss
 from .vote_head import VoteHead
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class SSD3DHead(VoteHead):
     r"""Bbox head of `3DSSD <https://arxiv.org/abs/2002.10187>`_.
 

mmdet3d/models/dense_heads/vote_head.py

@@ -6,15 +6,16 @@ from mmcv.runner import BaseModule, force_fp32
 from torch.nn import functional as F
 
 from mmdet3d.core.post_processing import aligned_3d_nms
+from mmdet3d.models.builder import build_loss
 from mmdet3d.models.losses import chamfer_distance
 from mmdet3d.models.model_utils import VoteModule
 from mmdet3d.ops import build_sa_module
+from mmdet3d.registry import MODELS
 from mmdet.core import build_bbox_coder, multi_apply
-from ..builder import HEADS, build_loss
 from .base_conv_bbox_head import BaseConvBboxHead
 
 
-@HEADS.register_module()
+@MODELS.register_module()
 class VoteHead(BaseModule):
     r"""Bbox head of `Votenet <https://arxiv.org/abs/1904.09664>`_.
 

mmdet3d/models/detectors/centerpoint.py

@@ -2,11 +2,11 @@
 import torch
 
 from mmdet3d.core import bbox3d2result, merge_aug_bboxes_3d
-from ..builder import DETECTORS
+from mmdet3d.registry import MODELS
 from .mvx_two_stage import MVXTwoStageDetector
 
 
-@DETECTORS.register_module()
+@MODELS.register_module()
 class CenterPoint(MVXTwoStageDetector):
     """Base class of Multi-modality VoxelNet."""
 

mmdet3d/models/detectors/dynamic_voxelnet.py

@@ -3,11 +3,11 @@ import torch
 from mmcv.runner import force_fp32
 from torch.nn import functional as F
 
-from ..builder import DETECTORS
+from mmdet3d.registry import MODELS
 from .voxelnet import VoxelNet
 
 
-@DETECTORS.register_module()
+@MODELS.register_module()
 class DynamicVoxelNet(VoxelNet):
     r"""VoxelNet using `dynamic voxelization <https://arxiv.org/abs/1910.06528>`_.
     """

mmdet3d/models/detectors/fcos_mono3d.py

 # Copyright (c) OpenMMLab. All rights reserved.
-from ..builder import DETECTORS
+from mmdet3d.registry import MODELS
 from .single_stage_mono3d import SingleStageMono3DDetector
 
 
-@DETECTORS.register_module()
+@MODELS.register_module()
 class FCOSMono3D(SingleStageMono3DDetector):
     r"""`FCOS3D <https://arxiv.org/abs/2104.10956>`_ for monocular 3D object detection.
 

mmdet3d/models/detectors/groupfree3dnet.py

@@ -2,11 +2,11 @@
 import torch
 
 from mmdet3d.core import bbox3d2result, merge_aug_bboxes_3d
-from ..builder import DETECTORS
+from mmdet3d.registry import MODELS
 from .single_stage import SingleStage3DDetector
 
 
-@DETECTORS.register_module()
+@MODELS.register_module()
 class GroupFree3DNet(SingleStage3DDetector):
     """`Group-Free 3D <https://arxiv.org/abs/2104.00678>`_."""
 

mmdet3d/models/detectors/h3dnet.py

@@ -2,11 +2,11 @@
 import torch
 
 from mmdet3d.core import merge_aug_bboxes_3d
-from ..builder import DETECTORS
+from mmdet3d.registry import MODELS
 from .two_stage import TwoStage3DDetector
 
 
-@DETECTORS.register_module()
+@MODELS.register_module()
 class H3DNet(TwoStage3DDetector):
     r"""H3DNet model.
 

mmdet3d/models/detectors/imvotenet.py

@@ -6,8 +6,7 @@ import torch
 
 from mmdet3d.core import bbox3d2result, merge_aug_bboxes_3d
 from mmdet3d.models.utils import MLP
-from .. import builder
-from ..builder import DETECTORS
+from mmdet3d.registry import MODELS
 from .base import Base3DDetector
 
 
@@ -53,7 +52,7 @@ def sample_valid_seeds(mask, num_sampled_seed=1024):
     return sample_inds
 
 
-@DETECTORS.register_module()
+@MODELS.register_module()
 class ImVoteNet(Base3DDetector):
     r"""`ImVoteNet <https://arxiv.org/abs/2001.10692>`_ for 3D detection."""
 
@@ -78,9 +77,9 @@ class ImVoteNet(Base3DDetector):
 
         # point branch
         if pts_backbone is not None:
-            self.pts_backbone = builder.build_backbone(pts_backbone)
+            self.pts_backbone = MODELS.build(pts_backbone)
         if pts_neck is not None:
-            self.pts_neck = builder.build_neck(pts_neck)
+            self.pts_neck = MODELS.build(pts_neck)
         if pts_bbox_heads is not None:
             pts_bbox_head_common = pts_bbox_heads.common
             pts_bbox_head_common.update(
@@ -93,9 +92,9 @@ class ImVoteNet(Base3DDetector):
             pts_bbox_head_img = pts_bbox_head_common.copy()
             pts_bbox_head_img.update(pts_bbox_heads.img)
 
-            self.pts_bbox_head_joint = builder.build_head(pts_bbox_head_joint)
-            self.pts_bbox_head_pts = builder.build_head(pts_bbox_head_pts)
-            self.pts_bbox_head_img = builder.build_head(pts_bbox_head_img)
+            self.pts_bbox_head_joint = MODELS.build(pts_bbox_head_joint)
+            self.pts_bbox_head_pts = MODELS.build(pts_bbox_head_pts)
+            self.pts_bbox_head_img = MODELS.build(pts_bbox_head_img)
             self.pts_bbox_heads = [
                 self.pts_bbox_head_joint, self.pts_bbox_head_pts,
                 self.pts_bbox_head_img
@@ -104,26 +103,26 @@ class ImVoteNet(Base3DDetector):
 
         # image branch
         if img_backbone:
-            self.img_backbone = builder.build_backbone(img_backbone)
+            self.img_backbone = MODELS.build(img_backbone)
         if img_neck is not None:
-            self.img_neck = builder.build_neck(img_neck)
+            self.img_neck = MODELS.build(img_neck)
         if img_rpn_head is not None:
             rpn_train_cfg = train_cfg.img_rpn if train_cfg \
                 is not None else None
             img_rpn_head_ = img_rpn_head.copy()
             img_rpn_head_.update(
                 train_cfg=rpn_train_cfg, test_cfg=test_cfg.img_rpn)
-            self.img_rpn_head = builder.build_head(img_rpn_head_)
+            self.img_rpn_head = MODELS.build(img_rpn_head_)
         if img_roi_head is not None:
             rcnn_train_cfg = train_cfg.img_rcnn if train_cfg \
                 is not None else None
             img_roi_head.update(
                 train_cfg=rcnn_train_cfg, test_cfg=test_cfg.img_rcnn)
-            self.img_roi_head = builder.build_head(img_roi_head)
+            self.img_roi_head = MODELS.build(img_roi_head)
 
         # fusion
         if fusion_layer is not None:
-            self.fusion_layer = builder.build_fusion_layer(fusion_layer)
+            self.fusion_layer = MODELS.build(fusion_layer)
             self.max_imvote_per_pixel = fusion_layer.max_imvote_per_pixel
 
         self.freeze_img_branch = freeze_img_branch

mmdet3d/models/detectors/imvoxelnet.py

@@ -3,11 +3,11 @@ import torch
 
 from mmdet3d.core import bbox3d2result, build_prior_generator
 from mmdet3d.models.fusion_layers.point_fusion import point_sample
+from mmdet3d.registry import MODELS
 from mmdet.models.detectors import BaseDetector
-from ..builder import DETECTORS, build_backbone, build_head, build_neck
 
 
-@DETECTORS.register_module()
+@MODELS.register_module()
 class ImVoxelNet(BaseDetector):
     r"""`ImVoxelNet <https://arxiv.org/abs/2106.01178>`_."""
 
@@ -23,12 +23,12 @@ class ImVoxelNet(BaseDetector):
                  pretrained=None,
                  init_cfg=None):
         super().__init__(init_cfg=init_cfg)
-        self.backbone = build_backbone(backbone)
-        self.neck = build_neck(neck)
-        self.neck_3d = build_neck(neck_3d)
+        self.backbone = MODELS.build(backbone)
+        self.neck = MODELS.build(neck)
+        self.neck_3d = MODELS.build(neck_3d)
         bbox_head.update(train_cfg=train_cfg)
         bbox_head.update(test_cfg=test_cfg)
-        self.bbox_head = build_head(bbox_head)
+        self.bbox_head = MODELS.build(bbox_head)
         self.n_voxels = n_voxels
         self.anchor_generator = build_prior_generator(anchor_generator)
         self.train_cfg = train_cfg

mmdet3d/models/detectors/mvx_faster_rcnn.py

@@ -3,11 +3,11 @@ import torch
 from mmcv.runner import force_fp32
 from torch.nn import functional as F
 
-from ..builder import DETECTORS
+from mmdet3d.registry import MODELS
 from .mvx_two_stage import MVXTwoStageDetector
 
 
-@DETECTORS.register_module()
+@MODELS.register_module()
 class MVXFasterRCNN(MVXTwoStageDetector):
     """Multi-modality VoxelNet using Faster R-CNN."""
 
@@ -15,7 +15,7 @@ class MVXFasterRCNN(MVXTwoStageDetector):
         super(MVXFasterRCNN, self).__init__(**kwargs)
 
 
-@DETECTORS.register_module()
+@MODELS.register_module()
 class DynamicMVXFasterRCNN(MVXTwoStageDetector):
     """Multi-modality VoxelNet using Faster R-CNN and dynamic voxelization."""