# Copyright (c) OpenMMLab. All rights reserved. import warnings from mmcv.cnn import MODELS as MMCV_MODELS from mmcv.utils import Registry from mmdet.models.builder import BACKBONES as MMDET_BACKBONES from mmdet.models.builder import DETECTORS as MMDET_DETECTORS from mmdet.models.builder import HEADS as MMDET_HEADS from mmdet.models.builder import LOSSES as MMDET_LOSSES from mmdet.models.builder import NECKS as MMDET_NECKS from mmdet.models.builder import ROI_EXTRACTORS as MMDET_ROI_EXTRACTORS from mmdet.models.builder import SHARED_HEADS as MMDET_SHARED_HEADS from mmseg.models.builder import LOSSES as MMSEG_LOSSES MODELS = Registry('models', parent=MMCV_MODELS) BACKBONES = MODELS NECKS = MODELS ROI_EXTRACTORS = MODELS SHARED_HEADS = MODELS HEADS = MODELS LOSSES = MODELS DETECTORS = MODELS VOXEL_ENCODERS = MODELS MIDDLE_ENCODERS = MODELS FUSION_LAYERS = MODELS SEGMENTORS = MODELS def build_backbone(cfg): """Build backbone.""" if cfg['type'] in BACKBONES._module_dict.keys(): return BACKBONES.build(cfg) else: return MMDET_BACKBONES.build(cfg) def build_neck(cfg): """Build neck.""" if cfg['type'] in NECKS._module_dict.keys(): return NECKS.build(cfg) else: return MMDET_NECKS.build(cfg) def build_roi_extractor(cfg): """Build RoI feature extractor.""" if cfg['type'] in ROI_EXTRACTORS._module_dict.keys(): return ROI_EXTRACTORS.build(cfg) else: return MMDET_ROI_EXTRACTORS.build(cfg) def build_shared_head(cfg): """Build shared head of detector.""" if cfg['type'] in SHARED_HEADS._module_dict.keys(): return SHARED_HEADS.build(cfg) else: return MMDET_SHARED_HEADS.build(cfg) def build_head(cfg): """Build head.""" if cfg['type'] in HEADS._module_dict.keys(): return HEADS.build(cfg) else: return MMDET_HEADS.build(cfg) def build_loss(cfg): """Build loss function.""" if cfg['type'] in LOSSES._module_dict.keys(): return LOSSES.build(cfg) elif cfg['type'] in MMDET_LOSSES._module_dict.keys(): return MMDET_LOSSES.build(cfg) else: return MMSEG_LOSSES.build(cfg) def build_detector(cfg, train_cfg=None, test_cfg=None): """Build detector.""" if train_cfg is not None or test_cfg is not None: warnings.warn( 'train_cfg and test_cfg is deprecated, ' 'please specify them in model', UserWarning) assert cfg.get('train_cfg') is None or train_cfg is None, \ 'train_cfg specified in both outer field and model field ' assert cfg.get('test_cfg') is None or test_cfg is None, \ 'test_cfg specified in both outer field and model field ' if cfg['type'] in DETECTORS._module_dict.keys(): return DETECTORS.build( cfg, default_args=dict(train_cfg=train_cfg, test_cfg=test_cfg)) else: return MMDET_DETECTORS.build( cfg, default_args=dict(train_cfg=train_cfg, test_cfg=test_cfg)) def build_segmentor(cfg, train_cfg=None, test_cfg=None): """Build segmentor.""" if train_cfg is not None or test_cfg is not None: warnings.warn( 'train_cfg and test_cfg is deprecated, ' 'please specify them in model', UserWarning) assert cfg.get('train_cfg') is None or train_cfg is None, \ 'train_cfg specified in both outer field and model field ' assert cfg.get('test_cfg') is None or test_cfg is None, \ 'test_cfg specified in both outer field and model field ' return SEGMENTORS.build( cfg, default_args=dict(train_cfg=train_cfg, test_cfg=test_cfg)) def build_model(cfg, train_cfg=None, test_cfg=None): """A function warpper for building 3D detector or segmentor according to cfg. Should be deprecated in the future. """ if cfg.type in ['EncoderDecoder3D']: return build_segmentor(cfg, train_cfg=train_cfg, test_cfg=test_cfg) else: return build_detector(cfg, train_cfg=train_cfg, test_cfg=test_cfg) def build_voxel_encoder(cfg): """Build voxel encoder.""" return VOXEL_ENCODERS.build(cfg) def build_middle_encoder(cfg): """Build middle level encoder.""" return MIDDLE_ENCODERS.build(cfg) def build_fusion_layer(cfg): """Build fusion layer.""" return FUSION_LAYERS.build(cfg)