Error encountered during testing script execution

[BaptFontaine]

I am encountering an error when attempting to run the testing script after successfully training the model on the S3DIS dataset. The error message I'm receiving is as follows:
Traceback (most recent call last):
File "tools/test.py", line 149, in
main()
File "tools/test.py", line 145, in main
runner.test()
File "/home/baptiste/miniconda3/envs/OF3D/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1823, in test
metrics = self.test_loop.run() # type: ignore
File "/home/baptiste/miniconda3/envs/OF3D/lib/python3.8/site-packages/mmengine/runner/loops.py", line 443, in run
self.run_iter(idx, data_batch)
File "/home/baptiste/miniconda3/envs/OF3D/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/home/baptiste/miniconda3/envs/OF3D/lib/python3.8/site-packages/mmengine/runner/loops.py", line 464, in run_iter
self.runner.call_hook(
File "/home/baptiste/miniconda3/envs/OF3D/lib/python3.8/site-packages/mmengine/runner/runner.py", line 1841, in call_hook
raise TypeError(f'{e} in {hook}') from None
TypeError: add_datasample() got an unexpected keyword argument 'vis_task' in <mmdet3d.engine.hooks.visualization_hook.Det3DVisualizationHook object at 0x7fa091151640>

This error occurs when executing the testing script with the following command:
python tools/test.py configs/oneformer3d_1xb2_s3dis-area-5.py work_dirs/oneformer3d_1xb2_s3dis-area-5/epoch_512.pth --show-dir results/oneformer3d_1xb2_s3dis-area-5 --task lidar_det

I seek assistance in either resolving this error or finding an alternative method to save the results generated by the testing script. Any guidance or suggestions would be appreciated.

[oneformer3d-contributor]

Yes, these code is not ready from mmdetecion3d visualization, mainly because we predict three types of segmentation masks simultaniously. You can simply save the input and the output from predict function and then visualize them.

[jiachen0212]

Yes, these code is not ready from mmdetecion3d visualization, mainly because we predict three types of segmentation masks simultaniously. You can simply save the input and the output from predict function and then visualize them.

will the code add mmdetecion3d visualization? we also need to predict the orientation of 3D objects~

[oneformer3d-contributor]

Unfortunately no plans for adding object detection or visualization to this repo.