Deprecate ImageToTensor in image_demo (#4400)

* FPN deprecated warning

* FPN deprecated warning

* Support DefaultFormatBundle in image_demo

* Fix Multi-Scale error, ref： open-mmlab/mmsegmentation#276

* Rename variable name

mmdet/apis/inference.py

@@ -8,6 +8,7 @@
 from mmcv.runner import load_checkpoint
 
 from mmdet.core import get_classes
+from mmdet.datasets import replace_ImageToTensor
 from mmdet.datasets.pipelines import Compose
 from mmdet.models import build_detector
 
@@ -103,9 +104,13 @@ def inference_detector(model, img):
  # add information into dict
  data = dict(img_info=dict(filename=img), img_prefix=None)
  # build the data pipeline
+ cfg.data.test.pipeline = replace_ImageToTensor(cfg.data.test.pipeline)
  test_pipeline = Compose(cfg.data.test.pipeline)
  data = test_pipeline(data)
  data = collate([data], samples_per_gpu=1)
+ # just get the actual data from DataContainer
+ data['img_metas'] = [img_metas.data[0] for img_metas in data['img_metas']]
+ data['img'] = [img.data[0] for img in data['img']]
  if next(model.parameters()).is_cuda:
  # scatter to specified GPU
  data = scatter(data, [device])[0]
@@ -114,8 +119,6 @@ def inference_detector(model, img):
  assert not isinstance(
  m, RoIPool
  ), 'CPU inference with RoIPool is not supported currently.'
- # just get the actual data from DataContainer
- data['img_metas'] = data['img_metas'][0].data
 
  # forward the model
  with torch.no_grad():