support FILTER_EMPTY_BOXES_FOR_TRAIN and DISABLE_NLZ_FLAG_ON_POINTS for WOD by...

support FILTER_EMPTY_BOXES_FOR_TRAIN and DISABLE_NLZ_FLAG_ON_POINTS for WOD by default, eval with sample_interval=1

pcdet/datasets/waymo/waymo_dataset.py

@@ -161,6 +161,7 @@ class WaymoDataset(DatasetTemplate):
         point_features = np.load(lidar_file)  # (N, 7): [x, y, z, intensity, elongation, NLZ_flag]
 
         points_all, NLZ_flag = point_features[:, 0:5], point_features[:, 5]
+        if not self.dataset_cfg.get('DISABLE_NLZ_FLAG_ON_POINTS', False):
             points_all = points_all[NLZ_flag == -1]
         points_all[:, 3] = np.tanh(points_all[:, 3])
         return points_all
@@ -200,6 +201,12 @@ class WaymoDataset(DatasetTemplate):
             else:
                 gt_boxes_lidar = annos['gt_boxes_lidar']
 
+            if self.training and self.dataset_cfg.get('FILTER_EMPTY_BOXES_FOR_TRAIN', False):
+                mask = (annos['num_points_in_gt'] > 0)  # filter empty boxes
+                annos['name'] = annos['name'][mask]
+                gt_boxes_lidar = gt_boxes_lidar[mask]
+                annos['num_points_in_gt'] = annos['num_points_in_gt'][mask]
+
             input_dict.update({
                 'gt_names': annos['name'],
                 'gt_boxes': gt_boxes_lidar,

tools/cfgs/dataset_configs/waymo_dataset.yaml

@@ -11,9 +11,12 @@ DATA_SPLIT: {
 
 SAMPLED_INTERVAL: {
     'train': 5,
-    'test': 5
+    'test': 1
 }
 
+FILTER_EMPTY_BOXES_FOR_TRAIN: True
+DISABLE_NLZ_FLAG_ON_POINTS: True
+
 USE_SHARED_MEMORY: False
 SHARED_MEMORY_FILE_LIMIT: 35000  # set it based on the size of your shared memory