updates

Author: Haozhe Qi

llava/action/ek_eval.py

@@ -350,7 +350,7 @@ def collate_fn(batch):
         from llava.action.generate_interval_pred import  get_lookup_dict
         if eval_args.test_type.startswith('temporal_cot'):
             lookup_table = get_lookup_dict(eval_args.val_metadata, 
-                                           'GT_random_narration',
+                                           eval_args.action_representation,
                                            test_type = eval_args.test_type, 
                                            pseudo_folder = eval_args.pseudo_folder)
 

llava/train/train.py

@@ -1290,8 +1290,10 @@ def _get_item(self, i) -> Dict[str, torch.Tensor]:
                     start_timestamp = round(float(self.list_data_dict[i]['start_timestamp']), 2)
                     end_timestamp = round(float(self.list_data_dict[i]['end_timestamp']), 2)
                     uid = f"{vid}_{start_timestamp}_{end_timestamp}"
-                    if True:
+                    if 'narration' in self.eval_args.action_representation:
                         meta_data = self.train_triple_lookup_narration.get(uid, None)
+                    elif 'official_key' in self.eval_args.action_representation:
+                        meta_data = self.train_triple_lookup_official.get(uid, None)
                     # if 'official_key' in sources[0]['question_type']:
                     #     meta_data = self.train_triple_lookup_official.get(uid, None)
                     # elif 'GT_random_narration' in sources[0]['question_type']: