bugfixed: inference and generate results on KITTI test set

pcdet/datasets/dataset.py

@@ -101,7 +101,7 @@ class DatasetTemplate(torch_data.Dataset):
         data_dict = self.data_processor.forward(
             data_dict=data_dict
         )
-        data_dict.pop('gt_names')
+        data_dict.pop('gt_names', None)
 
         return data_dict
 

pcdet/datasets/kitti/kitti_dataset.py

@@ -318,11 +318,10 @@ class KittiDataset(DatasetTemplate):
         return annos
 
     def evaluation(self, det_annos, class_names, **kwargs):
-        assert 'annos' in self.kitti_infos[0].keys()
-        from .kitti_object_eval_python import eval as kitti_eval
+        if 'annos' not in self.kitti_infos[0].keys():
+            return None, {}
 
-        if 'annos' not in self.kitti_infos[0]:
-            return 'None', {}
+        from .kitti_object_eval_python import eval as kitti_eval
 
         eval_det_annos = copy.deepcopy(det_annos)
         eval_gt_annos = [copy.deepcopy(info['annos']) for info in self.kitti_infos]

tools/eval_utils/eval_utils.py

@@ -8,9 +8,9 @@ from pcdet.utils import common_utils
 
 def statistics_info(cfg, ret_dict, metric, disp_dict):
     for cur_thresh in cfg.MODEL.POST_PROCESSING.RECALL_THRESH_LIST:
-        metric['recall_roi_%s' % str(cur_thresh)] += ret_dict['roi_%s' % str(cur_thresh)]
-        metric['recall_rcnn_%s' % str(cur_thresh)] += ret_dict['rcnn_%s' % str(cur_thresh)]
-    metric['gt_num'] += ret_dict['gt']
+        metric['recall_roi_%s' % str(cur_thresh)] += ret_dict.get('roi_%s' % str(cur_thresh), 0)
+        metric['recall_rcnn_%s' % str(cur_thresh)] += ret_dict.get('rcnn_%s' % str(cur_thresh), 0)
+    metric['gt_num'] += ret_dict.get('gt', 0)
     min_thresh = cfg.MODEL.POST_PROCESSING.RECALL_THRESH_LIST[0]
     disp_dict['recall_%s' % str(min_thresh)] = \
         '(%d, %d) / %d' % (metric['recall_roi_%s' % str(min_thresh)], metric['recall_rcnn_%s' % str(min_thresh)], metric['gt_num'])