fixup tabs to spaces

efg/data/datasets/nuscenes/nuscenes.py

@@ -22,11 +22,11 @@ def drop_arrays_by_name(gt_names, used_classes):
      Drop indices of ground truth arrays that are not used in class. This is useful for dropping arrays that are used in classification or regression algorithms
      
      Args:
-     	 gt_names: List of ground truth names
-     	 used_classes: List of classes used in classification or regression algorithms
+         gt_names: List of ground truth names
+         used_classes: List of classes used in classification or regression algorithms
      
      Returns: 
-     	 np. array of indices of ground truth arrays that are not used in class ( s ) and are
+         np. array of indices of ground truth arrays that are not used in class ( s ) and are
     """
     inds = [i for i, x in enumerate(gt_names) if x not in used_classes]
     inds = np.array(inds, dtype=np.int64)
@@ -40,7 +40,7 @@ def __init__(self, config):
          Initialize the class. This is called by __init__ and should not be called directly. The purpose of this method is to set the attributes that depend on the config passed in
          
          Args:
-         	 config: Configuration object that contains the
+             config: Configuration object that contains the
         """
         super(nuScenesDetectionDataset, self).__init__(config)
         self.config = config
@@ -87,7 +87,7 @@ def _get_metadata(self):
          
          
          Returns: 
-         	 A dictionary that can be used to create the data set's metadata ( class_names mapped_class_names etc
+             A dictionary that can be used to create the data set's metadata ( class_names mapped_class_names etc
         """
         mapped_class_names = []
         # Add classes to the mapped class names.
@@ -115,7 +115,7 @@ def load_infos(self):
          
          
          Returns: 
-         	 list of dicts with information about
+             list of dicts with information about
         """
         _nusc_infos_all = pickle.load(PathManager.open(self.info_path, "rb"))
 
@@ -168,7 +168,7 @@ def __len__(self):
          
          
          Returns: 
-         	 The number of datasets in the dataset_dicts dictionary or None if there are no datasets in the dataset
+             The number of datasets in the dataset_dicts dictionary or None if there are no datasets in the dataset
         """
         return len(self.dataset_dicts)
 
@@ -177,10 +177,10 @@ def __getitem__(self, idx):
          Return data for a given index. This is a wrapper around self. __getitem__ that works in a way that does not have to be called directly.
          
          Args:
-         	 idx: index of the dataset to return. Must be in range 0.. nsweeps - 1
+             idx: index of the dataset to return. Must be in range 0.. nsweeps - 1
          
          Returns: 
-         	 tuple of ( lidar_points sweep_times
+             tuple of ( lidar_points sweep_times
         """
         info = deepcopy(self.dataset_dicts[idx])
 
@@ -260,7 +260,7 @@ def _filter_gt_by_classes(self, info):
          Filter groundtruth annotations by class. This is a helper method for : meth : ` _annotate_gts `.
          
          Args:
-         	 info: dict - like object containing annotation information to filter
+             info: dict - like object containing annotation information to filter
         """
         target = info["annotations"]
         keep = (target["gt_names"][:, None] == self.class_names).any(axis=1)
@@ -271,7 +271,7 @@ def _add_class_labels_to_annos(self, info):
          Add labels to annotations. This is used to make sure that the class labels are in the correct order
          
          Args:
-         	 info: dict - like object containing
+             info: dict - like object containing
         """
         info["annotations"]["labels"] = (
             np.array([self.class_names.index(name) + 1 for name in info["annotations"]["gt_names"]])