change to fstring

mmdet3d/datasets/pipelines/indoor_loading.py

@@ -47,10 +47,9 @@ class IndoorLoadPointsFromFile(object):
 
     def __init__(self, use_height, load_dim=6, use_dim=[0, 1, 2]):
         self.use_height = use_height
-        assert max(
-            use_dim
-        ) < load_dim, f'Expect all used dimensions < {load_dim}, ' \
-                      f'got {use_dim}'
+        assert max(use_dim) < load_dim, \
+            f'Expect all used dimensions < {load_dim}, got {use_dim}'
+
         self.load_dim = load_dim
         self.use_dim = use_dim
 

tests/test_indoor_loading.py

@@ -15,7 +15,7 @@ def test_indoor_load_points_from_file():
     sunrgbd_info = sunrgbd_info[0]
     scan_name = sunrgbd_info['point_cloud']['lidar_idx']
     sunrgbd_results['pts_filename'] = osp.join(data_path, 'lidar',
-                                               '%06d.npy' % scan_name)
+                                               f'{scan_name:06d}.npy')
     sunrgbd_results = sunrgbd_load_points_from_file(sunrgbd_results)
     sunrgbd_point_cloud = sunrgbd_results['points']
     assert sunrgbd_point_cloud.shape == (100, 4)
@@ -29,7 +29,7 @@ def test_indoor_load_points_from_file():
     scan_name = scannet_info['point_cloud']['lidar_idx']
 
     scannet_results['pts_filename'] = osp.join(data_path,
-                                               scan_name + '_vert.npy')
+                                               f'{scan_name}_vert.npy')
     scannet_results = scannet_load_data(scannet_results)
     scannet_point_cloud = scannet_results['points']
     assert scannet_point_cloud.shape == (100, 4)
@@ -63,7 +63,7 @@ def test_load_annotations3D():
         scannet_gt_bboxes_3d_mask = np.zeros((1, 1))
     scan_name = scannet_info['point_cloud']['lidar_idx']
     scannet_results['pts_instance_mask_path'] = osp.join(
-        data_path, scan_name + '_ins_label.npy')
+        data_path, f'{scan_name}_ins_label.npy')
     scannet_results['pts_semantic_mask_path'] = osp.join(
         data_path, scan_name + '_sem_label.npy')
     scannet_results['info'] = scannet_info

tools/data_converter/sunrgbd_data_utils.py

@@ -147,7 +147,7 @@ class SUNRGBDData(object):
             pc_upright_depth_subsampled = random_sampling(
                 pc_upright_depth, SAMPLE_NUM)
             np.save(
-                os.path.join(self.root_dir, 'lidar', '%06d.npy' % sample_idx),
+                os.path.join(self.root_dir, 'lidar', f'{sample_idx:06d}.npy'),
                 pc_upright_depth_subsampled)
 
             info = dict()