[Fix] Fix mmseg.api.inference inference_segmentor

Motivation
Fix inference_segmentor not working with multiple images path or images. List[str/ndarray]

Modification
- process images if instance is list

mmseg/apis/inference.py

@@ -67,7 +67,7 @@ def __call__(self, results):
  return results
 
 
-def inference_segmentor(model, img):
+def inference_segmentor(model, imgs):
  """Inference image(s) with the segmentor.
 
  Args:
@@ -84,14 +84,23 @@ def inference_segmentor(model, img):
  test_pipeline = [LoadImage()] + cfg.data.test.pipeline[1:]
  test_pipeline = Compose(test_pipeline)
  # prepare data
- data = dict(img=img)
- data = test_pipeline(data)
- data = collate([data], samples_per_gpu=1)
+ if isinstance(imgs, list):
+ data = []
+ for img in imgs:
+ img_data = dict(img=img)
+ img_data = test_pipeline(img_data)
+ data.append(img_data)
+ data = collate(data, samples_per_gpu=len(imgs))
+ else:
+ data = dict(img=imgs)
+ data = test_pipeline(data)
+ data = collate([data], samples_per_gpu=1)
  if next(model.parameters()).is_cuda:
  # scatter to specified GPU
  data = scatter(data, [device])[0]
  else:
  data['img_metas'] = [i.data[0] for i in data['img_metas']]
+ breakpoint()
 
  # forward the model
  with torch.no_grad():