[Fix] fix instance statistics when only detecting a single class (#2003)

Author: JingweiZhang12

configs/centerpoint/centerpoint_voxel0075_second_secfpn_8xb4-cyclic-20e_nus-3d.py

@@ -89,7 +89,6 @@
     dict(type='ObjectRangeFilter', point_cloud_range=point_cloud_range),
     dict(type='ObjectNameFilter', classes=class_names),
     dict(type='PointShuffle'),
-    dict(type='DefaultFormatBundle3D', class_names=class_names),
     dict(
         type='Pack3DDetInputs',
         keys=['points', 'gt_bboxes_3d', 'gt_labels_3d'])

mmdet3d/datasets/det3d_dataset.py

@@ -255,8 +255,9 @@ def parse_ann_info(self, info: dict) -> Optional[dict]:
             ann_info['instances'] = info['instances']
 
             for label in ann_info['gt_labels_3d']:
-                cat_name = self.metainfo['classes'][label]
-                self.num_ins_per_cat[cat_name] += 1
+                if label != -1:
+                    cat_name = self.metainfo['classes'][label]
+                    self.num_ins_per_cat[cat_name] += 1
 
         return ann_info
 
@@ -336,12 +337,16 @@ def _show_ins_var(self, old_labels: np.ndarray, new_labels: torch.Tensor):
         """
         ori_num_per_cat = dict()
         for label in old_labels:
-            cat_name = self.metainfo['classes'][label]
-            ori_num_per_cat[cat_name] = ori_num_per_cat.get(cat_name, 0) + 1
+            if label != -1:
+                cat_name = self.metainfo['classes'][label]
+                ori_num_per_cat[cat_name] = ori_num_per_cat.get(cat_name,
+                                                                0) + 1
         new_num_per_cat = dict()
         for label in new_labels:
-            cat_name = self.metainfo['classes'][label]
-            new_num_per_cat[cat_name] = new_num_per_cat.get(cat_name, 0) + 1
+            if label != -1:
+                cat_name = self.metainfo['classes'][label]
+                new_num_per_cat[cat_name] = new_num_per_cat.get(cat_name,
+                                                                0) + 1
         content_show = [['category', 'new number', 'ori number']]
         for cat_name, num in ori_num_per_cat.items():
             new_num = new_num_per_cat.get(cat_name, 0)
@@ -387,9 +392,16 @@ def prepare_data(self, index: int) -> Optional[dict]:
                 return None
 
         if self.show_ins_var:
-            self._show_ins_var(
-                ori_input_dict['ann_info']['gt_labels_3d'],
-                example['data_samples'].gt_instances_3d.labels_3d)
+            if 'ann_info' in ori_input_dict:
+                self._show_ins_var(
+                    ori_input_dict['ann_info']['gt_labels_3d'],
+                    example['data_samples'].gt_instances_3d.labels_3d)
+            else:
+                print_log(
+                    "'ann_info' is not in the input dict. It's probably that "
+                    'the data is not in training mode',
+                    'current',
+                    level=30)
 
         return example