compat mmpose v0.26 (#518)

mmdeploy/codebase/mmpose/deploy/pose_detection.py

@@ -135,7 +135,6 @@ def create_input(self,
  Returns:
  tuple: (data, img), meta information for the input image and input.
  """
- from mmpose.apis.inference import _box2cs
  from mmpose.datasets.dataset_info import DatasetInfo
  from mmpose.datasets.pipelines import Compose
 
@@ -160,17 +159,12 @@ def create_input(self,
  image_size = input_shape
  else:
  image_size = np.array(cfg.data_cfg['image_size'])
- for bbox in bboxes:
- center, scale = _box2cs(cfg, bbox)
 
+ for bbox in bboxes:
  # prepare data
  data = {
  'img':
  imgs,
- 'center':
- center,
- 'scale':
- scale,
  'bbox_score':
  bbox[4] if len(bbox) == 5 else 1,
  'bbox_id':
@@ -190,6 +184,17 @@ def create_input(self,
  }
  }
 
+ # for compatibility of mmpose
+ try:
+ # for mmpose<=v0.25.1
+ from mmpose.apis.inference import _box2cs
+ center, scale = _box2cs(cfg, bbox)
+ data['center'] = center
+ data['scale'] = scale
+ except ImportError:
+ # for mmpose>=v0.26.0
+ data['bbox'] = bbox
+
  data = test_pipeline(data)
  batch_data.append(data)
 

tests/test_codebase/test_mmpose/data/model.py

@@ -1,5 +1,8 @@
 # Copyright (c) OpenMMLab. All rights reserved.
 # model settings
+import mmpose
+from packaging import version
+
 channel_cfg = dict(
  num_output_channels=17,
  dataset_joints=17,
@@ -47,6 +50,7 @@
 
 test_pipeline = [
  dict(type='LoadImageFromFile'),
+ # dict(type='TopDownGetBboxCenterScale'),
  dict(type='TopDownAffine'),
  dict(type='ToTensor'),
  dict(
@@ -61,6 +65,9 @@
  'flip_pairs'
  ]),
 ]
+# compatible with mmpose >=v0.26.0
+if version.parse(mmpose.__version__) >= version.parse('0.26.0'):
+ test_pipeline.insert(1, dict(type='TopDownGetBboxCenterScale'))
 
 dataset_info = dict(
  dataset_name='coco',

tests/test_codebase/test_mmpose/test_pose_detection.py

@@ -46,7 +46,6 @@
 
 
 def test_create_input():
- model_cfg = load_config(model_cfg_path)[0]
  deploy_cfg = mmcv.Config(
  dict(
  backend_config=dict(type=Backend.ONNXRUNTIME.value),