Merge branch 'indoor_dataset_fix_bug' into 'master'

Indoor dataset fix bug

See merge request open-mmlab/mmdet.3d!42

mmdet3d/datasets/custom_3d.py

@@ -43,7 +43,7 @@ class Custom3DDataset(Dataset):
         input_dict = dict(pts_filename=pts_filename)
 
         if not self.test_mode:
-            annos = self.get_ann_info(index, sample_idx)
+            annos = self.get_ann_info(index)
             input_dict['ann_info'] = annos
             if len(annos['gt_bboxes_3d']) == 0:
                 return None

mmdet3d/datasets/scannet_dataset.py

@@ -26,17 +26,16 @@ class ScanNetDataset(Custom3DDataset):
         pts_filename = osp.join(self.data_root, f'{sample_idx}_vert.npy')
         return pts_filename
 
-    def get_ann_info(self, index, sample_idx):
+    def get_ann_info(self, index):
         # Use index to get the annos, thus the evalhook could also use this api
         info = self.data_infos[index]
         if info['annos']['gt_num'] != 0:
             gt_bboxes_3d = info['annos']['gt_boxes_upright_depth']  # k, 6
             gt_labels_3d = info['annos']['class']
-            gt_bboxes_3d_mask = np.ones_like(gt_labels_3d, dtype=np.bool)
         else:
-            gt_bboxes_3d = np.zeros((1, 6), dtype=np.float32)
-            gt_labels_3d = np.zeros(1, dtype=np.bool)
-            gt_bboxes_3d_mask = np.zeros(1, dtype=np.bool)
+            gt_bboxes_3d = np.zeros((0, 6), dtype=np.float32)
+            gt_labels_3d = np.zeros(0, )
+        sample_idx = info['point_cloud']['lidar_idx']
         pts_instance_mask_path = osp.join(self.data_root,
                                           f'{sample_idx}_ins_label.npy')
         pts_semantic_mask_path = osp.join(self.data_root,
@@ -45,7 +44,6 @@ class ScanNetDataset(Custom3DDataset):
         anns_results = dict(
             gt_bboxes_3d=gt_bboxes_3d,
             gt_labels_3d=gt_labels_3d,
-            gt_bboxes_3d_mask=gt_bboxes_3d_mask,
             pts_instance_mask_path=pts_instance_mask_path,
             pts_semantic_mask_path=pts_semantic_mask_path)
         return anns_results

mmdet3d/datasets/sunrgbd_dataset.py

@@ -25,20 +25,16 @@ class SUNRGBDDataset(Custom3DDataset):
                                 f'{sample_idx:06d}.npy')
         return pts_filename
 
-    def get_ann_info(self, index, sample_idx):
+    def get_ann_info(self, index):
         # Use index to get the annos, thus the evalhook could also use this api
         info = self.data_infos[index]
         if info['annos']['gt_num'] != 0:
             gt_bboxes_3d = info['annos']['gt_boxes_upright_depth']  # k, 6
             gt_labels_3d = info['annos']['class']
-            gt_bboxes_3d_mask = np.ones_like(gt_labels_3d, dtype=np.bool)
         else:
-            gt_bboxes_3d = np.zeros((1, 6), dtype=np.float32)
-            gt_labels_3d = np.zeros(1, dtype=np.bool)
-            gt_bboxes_3d_mask = np.zeros(1, dtype=np.bool)
+            gt_bboxes_3d = np.zeros((0, 7), dtype=np.float32)
+            gt_labels_3d = np.zeros(0, )
 
         anns_results = dict(
-            gt_bboxes_3d=gt_bboxes_3d,
-            gt_labels_3d=gt_labels_3d,
-            gt_bboxes_3d_mask=gt_bboxes_3d_mask)
+            gt_bboxes_3d=gt_bboxes_3d, gt_labels_3d=gt_labels_3d)
         return anns_results