change dict.get, enrich assertion

mmdet3d/datasets/pipelines/indoor_loading.py

@@ -19,8 +19,8 @@ class PointsColorNormalize(object):
         self.color_mean = color_mean
 
     def __call__(self, results):
-        points = results.get('results', None)
-        assert points.shape[1] >= 6
+        points = results['points']
+        assert points.shape[1] >= 6, 'Incomplete color channel.'
         points[:, 3:6] = points[:, 3:6] - np.array(self.color_mean) / 256.0
         results['points'] = points
         return results
@@ -47,13 +47,13 @@ class LoadPointsFromFile(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
+        assert max(use_dim) < load_dim, 'Wrong dimension is used.'
         self.load_dim = load_dim
         self.use_dim = use_dim
 
     def __call__(self, results):
-        pts_filename = results.get('pts_filename', None)
-        assert osp.exists(pts_filename)
+        pts_filename = results['pts_filename']
+        assert osp.exists(pts_filename), f'{pts_filename} does not exist.'
         points = np.load(pts_filename)
         points = points.reshape(-1, self.load_dim)
         points = points[:, self.use_dim]
@@ -85,14 +85,15 @@ class LoadAnnotations3D(object):
         pass
 
     def __call__(self, results):
-        ins_labelname = results.get('ins_labelname', None)
-        sem_labelname = results.get('sem_labelname', None)
-
-        if ins_labelname is not None and sem_labelname is not None:
-            assert osp.exists(ins_labelname)
-            assert osp.exists(sem_labelname)
-            pts_instance_mask = np.load(ins_labelname)
-            pts_semantic_mask = np.load(sem_labelname)
+        pts_instance_mask_path = results['pts_instance_mask_path']
+        pts_semantic_mask_path = results['pts_semantic_mask_path']
+
+        assert osp.exists(pts_instance_mask_path
+                          ), f'{pts_instance_mask_path} does not exist.'
+        assert osp.exists(pts_semantic_mask_path
+                          ), f'{pts_semantic_mask_path} does not exist.'
+        pts_instance_mask = np.load(pts_instance_mask_path)
+        pts_semantic_mask = np.load(pts_semantic_mask_path)
         results['pts_instance_mask'] = pts_instance_mask
         results['pts_semantic_mask'] = pts_semantic_mask
 

tests/test_indoor_loading.py

@@ -37,8 +37,6 @@ def test_load_points_from_file():
 
 def test_load_annotations3D():
     sunrgbd_info = mmcv.load('./tests/data/sunrgbd/sunrgbd_infos.pkl')[0]
-    sunrgbd_load_annotations3D = LoadAnnotations3D()
-    sunrgbd_results = dict()
     if sunrgbd_info['annos']['gt_num'] != 0:
         sunrgbd_gt_bboxes_3d = sunrgbd_info['annos']['gt_boxes_upright_depth']
         sunrgbd_gt_labels = sunrgbd_info['annos']['class'].reshape(-1, 1)
@@ -47,16 +45,9 @@ def test_load_annotations3D():
         sunrgbd_gt_bboxes_3d = np.zeros((1, 6), dtype=np.float32)
         sunrgbd_gt_labels = np.zeros((1, 1))
         sunrgbd_gt_bboxes_3d_mask = np.zeros((1, 1))
-    sunrgbd_results['gt_bboxes_3d'] = sunrgbd_gt_bboxes_3d
-    sunrgbd_results['gt_labels'] = sunrgbd_gt_labels
-    sunrgbd_results['gt_bboxes_3d_mask'] = sunrgbd_gt_bboxes_3d_mask
-    sunrgbd_results = sunrgbd_load_annotations3D(sunrgbd_results)
-    sunrgbd_gt_boxes = sunrgbd_results.get('gt_bboxes_3d', None)
-    sunrgbd_gt_lbaels = sunrgbd_results.get('gt_labels', None)
-    sunrgbd_gt_boxes_mask = sunrgbd_results.get('gt_bboxes_3d_mask', None)
-    assert sunrgbd_gt_boxes.shape == (3, 7)
-    assert sunrgbd_gt_lbaels.shape == (3, 1)
-    assert sunrgbd_gt_boxes_mask.shape == (3, 1)
+    assert sunrgbd_gt_bboxes_3d.shape == (3, 7)
+    assert sunrgbd_gt_labels.shape == (3, 1)
+    assert sunrgbd_gt_bboxes_3d_mask.shape == (3, 1)
 
     scannet_info = mmcv.load('./tests/data/scannet/scannet_infos.pkl')[0]
     scannet_load_annotations3D = LoadAnnotations3D()
@@ -71,10 +62,10 @@ def test_load_annotations3D():
         scannet_gt_labels = np.zeros((1, 1))
         scannet_gt_bboxes_3d_mask = np.zeros((1, 1))
     scan_name = scannet_info['point_cloud']['lidar_idx']
-    scannet_results['ins_labelname'] = osp.join(data_path,
-                                                scan_name + '_ins_label.npy')
-    scannet_results['sem_labelname'] = osp.join(data_path,
-                                                scan_name + '_sem_label.npy')
+    scannet_results['pts_instance_mask_path'] = osp.join(
+        data_path, 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
     scannet_results['gt_bboxes_3d'] = scannet_gt_bboxes_3d
     scannet_results['gt_labels'] = scannet_gt_labels