[Feature] Support auto import modules from registry (#1961)

* update mmengine version & registry path

* replace register_all_modules

* refine dekr configs

* move init_default_scope to inference apis

* fix a filename bug in visualization_hook

configs/body_2d_keypoint/dekr/coco/dekr_hrnet-w32_8xb10-140e_coco-512x512.py

@@ -31,7 +31,7 @@
 
 # codec settings
 codec = dict(
-    type='RootDisplacement',
+    type='SPR',
     input_size=(512, 512),
     heatmap_size=(128, 128),
     sigma=(4, 2),

configs/body_2d_keypoint/dekr/coco/dekr_hrnet-w48_8xb10-140e_coco-640x640.py

@@ -31,7 +31,7 @@
 
 # codec settings
 codec = dict(
-    type='RootDisplacement',
+    type='SPR',
     input_size=(640, 640),
     heatmap_size=(160, 160),
     sigma=(4, 2),

configs/body_2d_keypoint/dekr/crowdpose/dekr_hrnet-w32_8xb10-300e_crowdpose-512x512.py

@@ -31,7 +31,7 @@
 
 # codec settings
 codec = dict(
-    type='RootDisplacement',
+    type='SPR',
     input_size=(512, 512),
     heatmap_size=(128, 128),
     sigma=(4, 2),

configs/body_2d_keypoint/dekr/crowdpose/dekr_hrnet-w48_8xb5-300e_crowdpose-640x640.py

@@ -31,7 +31,7 @@
 
 # codec settings
 codec = dict(
-    type='RootDisplacement',
+    type='SPR',
     input_size=(640, 640),
     heatmap_size=(160, 160),
     sigma=(4, 2),

demo/MMPose_Tutorial.ipynb

@@ -622,18 +622,17 @@
         "import mmcv\n",
         "from mmcv import imread\n",
         "import mmengine\n",
+        "from mmengine.registry import init_default_scope\n",
         "import numpy as np\n",
         "\n",
         "from mmpose.apis import inference_topdown\n",
         "from mmpose.apis import init_model as init_pose_estimator\n",
         "from mmpose.evaluation.functional import nms\n",
         "from mmpose.registry import VISUALIZERS\n",
         "from mmpose.structures import merge_data_samples\n",
-        "from mmpose.utils import register_all_modules as register_mmpose_modules\n",
         "\n",
         "try:\n",
         "    from mmdet.apis import inference_detector, init_detector\n",
-        "    from mmdet.utils import register_all_modules as register_mmdet_modules\n",
         "    has_mmdet = True\n",
         "except (ImportError, ModuleNotFoundError):\n",
         "    has_mmdet = False\n",
@@ -656,7 +655,6 @@
         "\n",
         "\n",
         "# build detector\n",
-        "register_mmdet_modules()\n",
         "detector = init_detector(\n",
         "    det_config,\n",
         "    det_checkpoint,\n",
@@ -665,7 +663,6 @@
         "\n",
         "\n",
         "# build pose estimator\n",
-        "register_mmpose_modules()\n",
         "pose_estimator = init_pose_estimator(\n",
         "    pose_config,\n",
         "    pose_checkpoint,\n",
@@ -696,7 +693,7 @@
         "    \"\"\"Visualize predicted keypoints (and heatmaps) of one image.\"\"\"\n",
         "\n",
         "    # predict bbox\n",
-        "    register_mmdet_modules()\n",
+        "    init_default_scope(detector.cfg.get('default_scope', 'mmdet'))\n",
         "    detect_result = inference_detector(detector, img_path)\n",
         "    pred_instance = detect_result.pred_instances.cpu().numpy()\n",
         "    bboxes = np.concatenate(\n",
@@ -706,7 +703,6 @@
         "    bboxes = bboxes[nms(bboxes, 0.3)][:, :4]\n",
         "\n",
         "    # predict keypoints\n",
-        "    register_mmpose_modules()\n",
         "    pose_results = inference_topdown(pose_estimator, img_path, bboxes)\n",
         "    data_samples = merge_data_samples(pose_results)\n",
         "\n",
@@ -3476,11 +3472,6 @@
       "source": [
         "from mmengine.config import Config, DictAction\n",
         "from mmengine.runner import Runner\n",
-        "from mmpose.utils import register_all_modules\n",
-        "\n",
-        "# register all modules in mmpose into the registries\n",
-        "# do not init the default scope here because it will be init in the runner\n",
-        "register_all_modules(init_default_scope=False)\n",
         "\n",
         "# set preprocess configs to model\n",
         "cfg.model.setdefault('data_preprocessor', cfg.get('preprocess_cfg', {}))\n",
@@ -3517,7 +3508,7 @@
     },
     "gpuClass": "standard",
     "kernelspec": {
-      "display_name": "Python 3.7.13 ('pt19cu113')",
+      "display_name": "dev2.0",
       "language": "python",
       "name": "python3"
     },
@@ -3531,11 +3522,11 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.7.13"
+      "version": "3.7.13 (default, Mar 29 2022, 02:18:16) \n[GCC 7.5.0]"
     },
     "vscode": {
       "interpreter": {
-        "hash": "da739a86cd93f7808d44852bc442711db64702daf7deb8b8d6704b313da8028c"
+        "hash": "383ba00087b5a9caebf3648b758a31e474cc01be975489b58f119fa4bc17e1f8"
       }
     },
     "widgets": {

demo/bottomup_demo.py

@@ -11,7 +11,6 @@
 from mmpose.apis import inference_bottomup, init_model
 from mmpose.registry import VISUALIZERS
 from mmpose.structures import split_instances
-from mmpose.utils import register_all_modules
 
 
 def process_one_image(args, img_path, pose_estimator, visualizer,
@@ -99,9 +98,6 @@ def main():
         args.pred_save_path = f'{args.output_root}/results_' \
             f'{os.path.splitext(os.path.basename(args.input))[0]}.json'
 
-    # register all modules in mmpose into the registries
-    register_all_modules()
-
     # build the model from a config file and a checkpoint file
     if args.draw_heatmap:
         cfg_options = dict(model=dict(test_cfg=dict(output_heatmaps=True)))

demo/image_demo.py

@@ -6,7 +6,6 @@
 from mmpose.apis import inference_topdown, init_model
 from mmpose.registry import VISUALIZERS
 from mmpose.structures import merge_data_samples
-from mmpose.utils import register_all_modules
 
 
 def parse_args():
@@ -28,9 +27,6 @@ def parse_args():
 def main():
     args = parse_args()
 
-    # register all modules in mmpose into the registries
-    register_all_modules()
-
     # build the model from a config file and a checkpoint file
     if args.draw_heatmap:
         cfg_options = dict(model=dict(test_cfg=dict(output_heatmaps=True)))

demo/topdown_demo_with_mmdet.py

@@ -8,17 +8,16 @@
 import mmcv
 import mmengine
 import numpy as np
+from mmengine.registry import init_default_scope
 
 from mmpose.apis import inference_topdown
 from mmpose.apis import init_model as init_pose_estimator
 from mmpose.evaluation.functional import nms
 from mmpose.registry import VISUALIZERS
 from mmpose.structures import merge_data_samples, split_instances
-from mmpose.utils import register_all_modules as register_mmpose_modules
 
 try:
     from mmdet.apis import inference_detector, init_detector
-    from mmdet.utils import register_all_modules as register_mmdet_modules
     has_mmdet = True
 except (ImportError, ModuleNotFoundError):
     has_mmdet = False
@@ -29,7 +28,7 @@ def process_one_image(args, img_path, detector, pose_estimator, visualizer,
     """Visualize predicted keypoints (and heatmaps) of one image."""
 
     # predict bbox
-    register_mmdet_modules()
+    init_default_scope(detector.cfg.get('default_scope', 'mmdet'))
     det_result = inference_detector(detector, img_path)
     pred_instance = det_result.pred_instances.cpu().numpy()
     bboxes = np.concatenate(
@@ -39,7 +38,6 @@ def process_one_image(args, img_path, detector, pose_estimator, visualizer,
     bboxes = bboxes[nms(bboxes, args.nms_thr), :4]
 
     # predict keypoints
-    register_mmpose_modules()
     pose_results = inference_topdown(pose_estimator, img_path, bboxes)
     data_samples = merge_data_samples(pose_results)
 
@@ -146,12 +144,10 @@ def main():
             f'{os.path.splitext(os.path.basename(args.input))[0]}.json'
 
     # build detector
-    register_mmdet_modules()
     detector = init_detector(
         args.det_config, args.det_checkpoint, device=args.device)
 
     # build pose estimator
-    register_mmpose_modules()
     pose_estimator = init_pose_estimator(
         args.pose_config,
         args.pose_checkpoint,

demo/topdown_face_demo.py

@@ -14,7 +14,6 @@
 from mmpose.evaluation.functional import nms
 from mmpose.registry import VISUALIZERS
 from mmpose.structures import merge_data_samples, split_instances
-from mmpose.utils import register_all_modules as register_mmpose_modules
 
 try:
     import face_recognition
@@ -146,7 +145,6 @@ def main():
             f'{os.path.splitext(os.path.basename(args.input))[0]}.json'
 
     # build pose estimator
-    register_mmpose_modules()
     pose_estimator = init_pose_estimator(
         args.pose_config,
         args.pose_checkpoint,

mmpose/__init__.py

@@ -9,7 +9,7 @@
 mmcv_maximum_version = '2.1.0'
 mmcv_version = digit_version(mmcv.__version__)
 
-mmengine_minimum_version = '0.1.0'
+mmengine_minimum_version = '0.4.0'
 mmengine_maximum_version = '1.0.0'
 mmengine_version = digit_version(mmengine.__version__)
 

mmpose/apis/inference.py

@@ -8,6 +8,7 @@
 import torch.nn as nn
 from mmengine.config import Config
 from mmengine.dataset import Compose, pseudo_collate
+from mmengine.registry import init_default_scope
 from mmengine.runner import load_checkpoint
 from PIL import Image
 
@@ -93,6 +94,9 @@ def init_model(config: Union[str, Path, Config],
         config.model.backbone.init_cfg = None
     config.model.train_cfg = None
 
+    # register all modules in mmpose into the registries
+    init_default_scope(config.get('default_scope', 'mmpose'))
+
     model = build_pose_estimator(config.model)
     # get dataset_meta in this priority: checkpoint > config > default (COCO)
     dataset_meta = None
@@ -143,6 +147,7 @@ def inference_topdown(model: nn.Module,
         ``data_sample.pred_instances.keypoints`` and
         ``data_sample.pred_instances.keypoint_scores``.
     """
+    init_default_scope(model.cfg.get('default_scope', 'mmpose'))
     pipeline = Compose(model.cfg.test_dataloader.dataset.pipeline)
 
     if bboxes is None:

mmpose/apis/webcam/nodes/model_nodes/detector_node.py

@@ -2,14 +2,14 @@
 from typing import Dict, List, Optional, Union
 
 import numpy as np
+from mmengine.registry import init_default_scope
 
 from ...utils import get_config_path
 from ..node import Node
 from ..registry import NODES
 
 try:
     from mmdet.apis import inference_detector, init_detector
-    from mmdet.utils import register_all_modules
     has_mmdet = True
 except (ImportError, ModuleNotFoundError):
     has_mmdet = False
@@ -90,7 +90,6 @@ def __init__(self,
         self.bbox_thr = bbox_thr
 
         # Init model
-        register_all_modules()
         self.model = init_detector(
             self.model_config, self.model_checkpoint, device=self.device)
 
@@ -110,7 +109,7 @@ def process(self, input_msgs):
 
         img = input_msg.get_image()
 
-        register_all_modules()
+        init_default_scope(self.model.cfg.get('default_scope', 'mmdet'))
         preds = inference_detector(self.model, img)
         objects = self._post_process(preds)
         input_msg.update_objects(objects)

mmpose/apis/webcam/nodes/model_nodes/pose_estimator_node.py

@@ -5,7 +5,6 @@
 import numpy as np
 
 from mmpose.apis import inference_topdown, init_model
-from mmpose.utils import register_all_modules
 from ...utils import get_config_path
 from ..node import Node
 from ..registry import NODES
@@ -91,7 +90,6 @@ def __init__(self,
         self.bbox_thr = bbox_thr
 
         # Init model
-        register_all_modules()
         self.model = init_model(
             self.model_config, self.model_checkpoint, device=self.device)
 
@@ -119,7 +117,6 @@ def process(self, input_msgs):
         if len(objects) > 0:
             # Inference pose
             bboxes = np.stack([object['bbox'] for object in objects])
-            register_all_modules()
             pose_results = inference_topdown(self.model, img, bboxes)
 
             # Update objects

mmpose/engine/hooks/visualization_hook.py

@@ -150,7 +150,8 @@ def after_test_iter(self, runner: Runner, batch_idx: int, data_batch: dict,
 
             out_file = None
             if self.out_dir is not None:
-                out_file_name, postfix = os.path.basename(img_path).split('.')
+                out_file_name, postfix = os.path.basename(img_path).rsplit(
+                    '.', 1)
                 index = len([
                     fname for fname in os.listdir(self.out_dir)
                     if fname.startswith(out_file_name)