[Feature] Support auto import modules from registry.

configs/convnext/cascade-mask-rcnn_convnext-s-p4-w7_fpn_4conv1fc-giou_amp-ms-crop-3x_coco.py

@@ -1,5 +1,6 @@
 _base_ = './cascade-mask-rcnn_convnext-t-p4-w7_fpn_4conv1fc-giou_amp-ms-crop-3x_coco.py'  # noqa
 
+# TODO: delete custom_imports after mmcls supports auto import
 # please install mmcls>=1.0
 # import mmcls.models to trigger register_module in mmcls
 custom_imports = dict(imports=['mmcls.models'], allow_failed_imports=False)

configs/convnext/cascade-mask-rcnn_convnext-t-p4-w7_fpn_4conv1fc-giou_amp-ms-crop-3x_coco.py

@@ -4,6 +4,7 @@
     '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
 ]
 
+# TODO: delete custom_imports after mmcls supports auto import
 # please install mmcls>=1.0
 # import mmcls.models to trigger register_module in mmcls
 custom_imports = dict(imports=['mmcls.models'], allow_failed_imports=False)

configs/convnext/mask-rcnn_convnext-t-p4-w7_fpn_amp-ms-crop-3x_coco.py

@@ -4,6 +4,7 @@
     '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
 ]
 
+# TODO: delete custom_imports after mmcls supports auto import
 # please install mmcls>=1.0
 # import mmcls.models to trigger register_module in mmcls
 custom_imports = dict(imports=['mmcls.models'], allow_failed_imports=False)

configs/rtmdet/classification/cspnext-s_8xb256-rsb-a1-600e_in1k.py

@@ -4,8 +4,6 @@
     'mmcls::_base_/default_runtime.py'
 ]
 
-custom_imports = dict(imports=['mmdet.models'], allow_failed_imports=False)
-
 model = dict(
     type='ImageClassifier',
     backbone=dict(

configs/timm_example/retinanet_timm-efficientnet-b1_fpn_1x_coco.py

@@ -4,9 +4,11 @@
     '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
 ]
 
-# please install mmcls>=0.20.0
+# TODO: delete custom_imports after mmcls supports auto import
+# please install mmcls>=1.0
 # import mmcls.models to trigger register_module in mmcls
 custom_imports = dict(imports=['mmcls.models'], allow_failed_imports=False)
+
 model = dict(
     backbone=dict(
         _delete_=True,

configs/timm_example/retinanet_timm-tv-resnet50_fpn_1x_coco.py

@@ -4,9 +4,11 @@
     '../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
 ]
 
-# please install mmcls>=0.20.0
+# TODO: delete custom_imports after mmcls supports auto import
+# please install mmcls>=1.0
 # import mmcls.models to trigger register_module in mmcls
 custom_imports = dict(imports=['mmcls.models'], allow_failed_imports=False)
+
 model = dict(
     backbone=dict(
         _delete_=True,

demo/image_demo.py

@@ -7,7 +7,6 @@
 from mmdet.apis import (async_inference_detector, inference_detector,
                         init_detector)
 from mmdet.registry import VISUALIZERS
-from mmdet.utils import register_all_modules
 
 
 def parse_args():
@@ -34,9 +33,6 @@ def parse_args():
 
 
 def main(args):
-    # register all modules in mmdet into the registries
-    register_all_modules()
-
     # TODO: Support inference of image directory.
     # build the model from a config file and a checkpoint file
     model = init_detector(

demo/video_demo.py

@@ -8,7 +8,6 @@
 
 from mmdet.apis import inference_detector, init_detector
 from mmdet.registry import VISUALIZERS
-from mmdet.utils import register_all_modules
 
 
 def parse_args():
@@ -37,9 +36,6 @@ def main():
         ('Please specify at least one operation (save/show the '
          'video) with the argument "--out" or "--show"')
 
-    # register all modules in mmdet into the registries
-    register_all_modules()
-
     # build the model from a config file and a checkpoint file
     model = init_detector(args.config, args.checkpoint, device=args.device)
 

demo/video_gpuaccel_demo.py

@@ -13,7 +13,6 @@
 from mmdet.apis import init_detector
 from mmdet.registry import VISUALIZERS
 from mmdet.structures import DetDataSample
-from mmdet.utils import register_all_modules
 
 try:
     import ffmpegcv
@@ -81,9 +80,6 @@ def main():
         ('Please specify at least one operation (save/show the '
          'video) with the argument "--out" or "--show"')
 
-    # register all modules in mmdet into the registries
-    register_all_modules()
-
     model = init_detector(args.config, args.checkpoint, device=args.device)
 
     # init visualizer

demo/webcam_demo.py

@@ -7,7 +7,6 @@
 
 from mmdet.apis import inference_detector, init_detector
 from mmdet.registry import VISUALIZERS
-from mmdet.utils import register_all_modules
 
 
 def parse_args():
@@ -27,9 +26,6 @@ def parse_args():
 def main():
     args = parse_args()
 
-    # register all modules in mmdet into the registries
-    register_all_modules()
-
     # build the model from a config file and a checkpoint file
     device = torch.device(args.device)
     model = init_detector(args.config, args.checkpoint, device=device)

docs/en/get_started.md

@@ -95,9 +95,7 @@ Case b: If you install MMDetection with MIM, open your python interpreter and co
 
 ```python
 from mmdet.apis import init_detector, inference_detector
-from mmdet.utils import register_all_modules
 
-register_all_modules()
 config_file = 'yolov3_mobilenetv2_8xb24-320-300e_coco.py'
 checkpoint_file = 'yolov3_mobilenetv2_320_300e_coco_20210719_215349-d18dff72.pth'
 model = init_detector(config_file, checkpoint_file, device='cpu')  # or device='cuda:0'

docs/en/notes/faq.md

@@ -10,7 +10,7 @@ We list some common troubles faced by many users and their corresponding solutio
 
   | MMDetection version |      MMCV version       |     MMEngine version     |
   | :-----------------: | :---------------------: | :----------------------: |
-  |         3.x         | mmcv>=2.0.0rc1, \<2.1.0 | mmengine>=0.3.0, \<1.0.0 |
+  |         3.x         | mmcv>=2.0.0rc4, \<2.1.0 | mmengine>=0.4.0, \<1.0.0 |
   |      3.0.0rc6       | mmcv>=2.0.0rc4, \<2.1.0 | mmengine>=0.3.0, \<1.0.0 |
   |      3.0.0rc5       | mmcv>=2.0.0rc1, \<2.1.0 | mmengine>=0.3.0, \<1.0.0 |
   |      3.0.0rc4       | mmcv>=2.0.0rc1, \<2.1.0 | mmengine>=0.3.0, \<1.0.0 |

docs/en/user_guides/inference.md

@@ -17,11 +17,8 @@ import mmcv
 from mmcv.transforms import Compose
 from mmengine.utils import track_iter_progress
 from mmdet.registry import VISUALIZERS
-from mmdet.utils import register_all_modules
 from mmdet.apis import init_detector, inference_detector
 
-# Register all modules in mmdet into the registries
-register_all_modules()
 
 # Specify the path to model config and checkpoint file
 config_file = 'configs/faster_rcnn/faster-rcnn_r50-fpn_1x_coco.py'

docs/zh_cn/get_started.md

@@ -94,9 +94,7 @@ python demo/image_demo.py demo/demo.jpg yolov3_mobilenetv2_8xb24-320-300e_coco.p
 
 ```python
 from mmdet.apis import init_detector, inference_detector
-from mmdet.utils import register_all_modules
 
-register_all_modules()
 config_file = 'yolov3_mobilenetv2_8xb24-320-300e_coco.py'
 checkpoint_file = 'yolov3_mobilenetv2_320_300e_coco_20210719_215349-d18dff72.pth'
 model = init_detector(config_file, checkpoint_file, device='cpu')  # or device='cuda:0'

docs/zh_cn/notes/faq.md

@@ -10,7 +10,8 @@
 
   | MMDetection 版本 |        MMCV 版本        |      MMEngine 版本       |
   | :--------------: | :---------------------: | :----------------------: |
-  |       3.x        | mmcv>=2.0.0rc1, \<2.1.0 | mmengine>=0.3.0, \<1.0.0 |
+  |       3.x        | mmcv>=2.0.0rc4, \<2.1.0 | mmengine>=0.4.0, \<1.0.0 |
+  |     3.0.0rc6     | mmcv>=2.0.0rc4, \<2.1.0 | mmengine>=0.3.0, \<1.0.0 |
   |     3.0.0rc5     | mmcv>=2.0.0rc1, \<2.1.0 | mmengine>=0.3.0, \<1.0.0 |
   |     3.0.0rc4     | mmcv>=2.0.0rc1, \<2.1.0 | mmengine>=0.3.0, \<1.0.0 |
   |     3.0.0rc3     | mmcv>=2.0.0rc1, \<2.1.0 | mmengine>=0.3.0, \<1.0.0 |

mmdet/__init__.py

@@ -9,7 +9,7 @@
 mmcv_maximum_version = '2.1.0'
 mmcv_version = digit_version(mmcv.__version__)
 
-mmengine_minimum_version = '0.3.0'
+mmengine_minimum_version = '0.4.0'
 mmengine_maximum_version = '1.0.0'
 mmengine_version = digit_version(mmengine.__version__)
 

mmdet/apis/inference.py

@@ -10,6 +10,7 @@
 from mmcv.ops import RoIPool
 from mmcv.transforms import Compose
 from mmengine.config import Config
+from mmengine.registry import init_default_scope
 from mmengine.runner import load_checkpoint
 
 from mmdet.registry import DATASETS
@@ -54,6 +55,8 @@ def init_detector(
         config.merge_from_dict(cfg_options)
     elif 'init_cfg' in config.model.backbone:
         config.model.backbone.init_cfg = None
+    init_default_scope(config.get('default_scope', 'mmdet'))
+
     model = MODELS.build(config.model)
     if checkpoint is None:
         warnings.simplefilter('once')

mmdet/registry.py

@@ -32,50 +32,90 @@
 from mmengine.registry import Registry
 
 # manage all kinds of runners like `EpochBasedRunner` and `IterBasedRunner`
-RUNNERS = Registry('runner', parent=MMENGINE_RUNNERS)
+RUNNERS = Registry(
+    'runner', parent=MMENGINE_RUNNERS, locations=['mmdet.engine.runner'])
 # manage runner constructors that define how to initialize runners
 RUNNER_CONSTRUCTORS = Registry(
-    'runner constructor', parent=MMENGINE_RUNNER_CONSTRUCTORS)
+    'runner constructor',
+    parent=MMENGINE_RUNNER_CONSTRUCTORS,
+    locations=['mmdet.engine.runner'])
 # manage all kinds of loops like `EpochBasedTrainLoop`
-LOOPS = Registry('loop', parent=MMENGINE_LOOPS)
+LOOPS = Registry(
+    'loop', parent=MMENGINE_LOOPS, locations=['mmdet.engine.runner'])
 # manage all kinds of hooks like `CheckpointHook`
-HOOKS = Registry('hook', parent=MMENGINE_HOOKS)
+HOOKS = Registry(
+    'hook', parent=MMENGINE_HOOKS, locations=['mmdet.engine.hooks'])
 
 # manage data-related modules
-DATASETS = Registry('dataset', parent=MMENGINE_DATASETS)
-DATA_SAMPLERS = Registry('data sampler', parent=MMENGINE_DATA_SAMPLERS)
-TRANSFORMS = Registry('transform', parent=MMENGINE_TRANSFORMS)
+DATASETS = Registry(
+    'dataset', parent=MMENGINE_DATASETS, locations=['mmdet.datasets'])
+DATA_SAMPLERS = Registry(
+    'data sampler',
+    parent=MMENGINE_DATA_SAMPLERS,
+    locations=['mmdet.datasets.samplers'])
+TRANSFORMS = Registry(
+    'transform',
+    parent=MMENGINE_TRANSFORMS,
+    locations=['mmdet.datasets.transforms'])
 
 # manage all kinds of modules inheriting `nn.Module`
-MODELS = Registry('model', parent=MMENGINE_MODELS)
+MODELS = Registry('model', parent=MMENGINE_MODELS, locations=['mmdet.models'])
 # manage all kinds of model wrappers like 'MMDistributedDataParallel'
-MODEL_WRAPPERS = Registry('model_wrapper', parent=MMENGINE_MODEL_WRAPPERS)
+MODEL_WRAPPERS = Registry(
+    'model_wrapper',
+    parent=MMENGINE_MODEL_WRAPPERS,
+    locations=['mmdet.models'])
 # manage all kinds of weight initialization modules like `Uniform`
 WEIGHT_INITIALIZERS = Registry(
-    'weight initializer', parent=MMENGINE_WEIGHT_INITIALIZERS)
+    'weight initializer',
+    parent=MMENGINE_WEIGHT_INITIALIZERS,
+    locations=['mmdet.models'])
 
 # manage all kinds of optimizers like `SGD` and `Adam`
-OPTIMIZERS = Registry('optimizer', parent=MMENGINE_OPTIMIZERS)
+OPTIMIZERS = Registry(
+    'optimizer',
+    parent=MMENGINE_OPTIMIZERS,
+    locations=['mmdet.engine.optimizers'])
 # manage optimizer wrapper
-OPTIM_WRAPPERS = Registry('optim_wrapper', parent=MMENGINE_OPTIM_WRAPPERS)
+OPTIM_WRAPPERS = Registry(
+    'optim_wrapper',
+    parent=MMENGINE_OPTIM_WRAPPERS,
+    locations=['mmdet.engine.optimizers'])
 # manage constructors that customize the optimization hyperparameters.
 OPTIM_WRAPPER_CONSTRUCTORS = Registry(
-    'optimizer constructor', parent=MMENGINE_OPTIM_WRAPPER_CONSTRUCTORS)
+    'optimizer constructor',
+    parent=MMENGINE_OPTIM_WRAPPER_CONSTRUCTORS,
+    locations=['mmdet.engine.optimizers'])
 # manage all kinds of parameter schedulers like `MultiStepLR`
 PARAM_SCHEDULERS = Registry(
-    'parameter scheduler', parent=MMENGINE_PARAM_SCHEDULERS)
+    'parameter scheduler',
+    parent=MMENGINE_PARAM_SCHEDULERS,
+    locations=['mmdet.engine.schedulers'])
 # manage all kinds of metrics
-METRICS = Registry('metric', parent=MMENGINE_METRICS)
+METRICS = Registry(
+    'metric', parent=MMENGINE_METRICS, locations=['mmdet.evaluation'])
 # manage evaluator
-EVALUATOR = Registry('evaluator', parent=MMENGINE_EVALUATOR)
+EVALUATOR = Registry(
+    'evaluator', parent=MMENGINE_EVALUATOR, locations=['mmdet.evaluation'])
 
 # manage task-specific modules like anchor generators and box coders
-TASK_UTILS = Registry('task util', parent=MMENGINE_TASK_UTILS)
+TASK_UTILS = Registry(
+    'task util', parent=MMENGINE_TASK_UTILS, locations=['mmdet.models'])
 
 # manage visualizer
-VISUALIZERS = Registry('visualizer', parent=MMENGINE_VISUALIZERS)
+VISUALIZERS = Registry(
+    'visualizer',
+    parent=MMENGINE_VISUALIZERS,
+    locations=['mmdet.visualization'])
 # manage visualizer backend
-VISBACKENDS = Registry('vis_backend', parent=MMENGINE_VISBACKENDS)
+VISBACKENDS = Registry(
+    'vis_backend',
+    parent=MMENGINE_VISBACKENDS,
+    locations=['mmdet.visualization'])
 
 # manage logprocessor
-LOG_PROCESSORS = Registry('log_processor', parent=MMENGINE_LOG_PROCESSORS)
+LOG_PROCESSORS = Registry(
+    'log_processor',
+    parent=MMENGINE_LOG_PROCESSORS,
+    # TODO: update the location when mmdet has its own log processor
+    locations=['mmdet.engine'])

requirements/mminstall.txt

@@ -1,2 +1,2 @@
-mmcv>=2.0.0rc1,<2.1.0
-mmengine>=0.1.0,<1.0.0
+mmcv>=2.0.0rc4,<2.1.0
+mmengine>=0.4.0,<1.0.0

tools/analysis_tools/analyze_results.py

@@ -7,6 +7,7 @@
 import numpy as np
 from mmengine.config import Config, DictAction
 from mmengine.fileio import load
+from mmengine.registry import init_default_scope
 from mmengine.runner import Runner
 from mmengine.structures import InstanceData, PixelData
 from mmengine.utils import ProgressBar, check_file_exist, mkdir_or_exist
@@ -15,8 +16,7 @@
 from mmdet.evaluation import eval_map
 from mmdet.registry import DATASETS, RUNNERS
 from mmdet.structures import DetDataSample
-from mmdet.utils import (register_all_modules, replace_cfg_vals,
-                         update_data_root)
+from mmdet.utils import replace_cfg_vals, update_data_root
 from mmdet.visualization import DetLocalVisualizer
 
 
@@ -348,7 +348,6 @@ def parse_args():
 
 
 def main():
-    register_all_modules()
     args = parse_args()
 
     check_file_exist(args.prediction_path)
@@ -363,6 +362,8 @@ def main():
 
     if args.cfg_options is not None:
         cfg.merge_from_dict(args.cfg_options)
+    init_default_scope(cfg.get('default_scope', 'mmdet'))
+
     cfg.test_dataloader.dataset.test_mode = True
 
     cfg.test_dataloader.pop('batch_size', 0)

tools/analysis_tools/benchmark.py

@@ -5,9 +5,9 @@
 from mmengine import MMLogger
 from mmengine.config import Config, DictAction
 from mmengine.dist import init_dist
+from mmengine.registry import init_default_scope
 from mmengine.utils import mkdir_or_exist
 
-from mmdet.utils import register_all_modules
 from mmdet.utils.benchmark import (DataLoaderBenchmark, DatasetBenchmark,
                                    InferenceBenchmark)
 
@@ -105,14 +105,13 @@ def dataset_benchmark(args, cfg, distributed, logger):
 
 
 def main():
-    register_all_modules()
-
     args = parse_args()
     cfg = Config.fromfile(args.config)
-
     if args.cfg_options is not None:
         cfg.merge_from_dict(args.cfg_options)
 
+    init_default_scope(cfg.get('default_scope', 'mmdet'))
+
     distributed = False
     if args.launcher != 'none':
         init_dist(args.launcher, **cfg.get('env_cfg', {}).get('dist_cfg', {}))