fix(num_frames): compatible to the old model also.

Author: Kin-Zhang

2_eval.py

@@ -46,7 +46,11 @@ def main(cfg):
     trainer = pl.Trainer(logger=wandb_logger, devices=1)
     # NOTE(Qingwen): search & check: def eval_only_step_(self, batch, res_dict)
     trainer.validate(model = mymodel, \
-                     dataloaders = DataLoader(HDF5Dataset(cfg.dataset_path + f"/{cfg.av2_mode}", n_frames=checkpoint_params.cfg.num_frames, eval=True, leaderboard_version=cfg.leaderboard_version), batch_size=1, shuffle=False))
+                     dataloaders = DataLoader( \
+                                            HDF5Dataset(cfg.dataset_path + f"/{cfg.av2_mode}", \
+                                                        n_frames=checkpoint_params.cfg.num_frames  if 'num_frames' in checkpoint_params.cfg else 2, \
+                                                        eval=True, leaderboard_version=cfg.leaderboard_version), \
+                                            batch_size=1, shuffle=False))
     wandb.finish()
 
 if __name__ == "__main__":

3_vis.py

@@ -49,7 +49,9 @@ def main(cfg):
     trainer = pl.Trainer(logger=wandb_logger, devices=1)
     # NOTE(Qingwen): search & check in pl_model.py : def test_step(self, batch, res_dict)
     trainer.test(model = mymodel, \
-                 dataloaders = DataLoader(HDF5Dataset(cfg.dataset_path, n_frames=checkpoint_params.cfg.num_frames), batch_size=1, shuffle=False))
+                 dataloaders = DataLoader(\
+                     HDF5Dataset(cfg.dataset_path, n_frames=checkpoint_params.cfg.num_frames if 'num_frames' in checkpoint_params.cfg else 2), \
+                    batch_size=1, shuffle=False))
     wandb.finish()
 
 if __name__ == "__main__":

conf/eval.yaml

@@ -4,7 +4,7 @@ checkpoint: /home/kin/model_zoo/deflow.ckpt
 av2_mode: val # [val, test]
 save_res: False # [True, False]
 
-leaderboard_version: 2 # [1, 2]
+leaderboard_version: 1 # [1, 2]
 supervised_flag: True # [True, False], whether you use any label from the dataset
 
 # no need to change