ZikangZhou / HiVT

[CVPR 2022] HiVT: Hierarchical Vector Transformer for Multi-Agent Motion Prediction
https://openaccess.thecvf.com/content/CVPR2022/papers/Zhou_HiVT_Hierarchical_Vector_Transformer_for_Multi-Agent_Motion_Prediction_CVPR_2022_paper.pdf
Apache License 2.0
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How to obtain the ADE/FDE/MR result of test set? #38

Open WenchuanSUN1 opened 1 year ago

WenchuanSUN1 commented 1 year ago

I would like to express my appreciation for your work on the HiVT project. I have been using HiVT for my research, and it has been a valuable tool for my experiments. I am currently working on evaluating the performance of HiVT on the test set of Argoverse. However, I cannot correct load test set data. I always meet the error:

HiVT2/models/hivt.py", line 129, in validation_step
    l2_norm = (torch.norm(y_hat[:, :, :, : 2] - data.y, p=2, dim=-1) * reg_mask).sum(dim=-1)  # [F, N]
TypeError: unsupported operand type(s) for -: 'Tensor' and 'NoneType'

I would greatly appreciate it if you could provide some guidance or assistance.

nanybeih commented 10 months ago

@WenchuanSUN1 I meet the same error. Do u have solved this problem? I would greatly appreciate it if you could provide some guidance. Thank u very much.

yyjs666 commented 10 months ago

The test set of Argoverse contains only the information for the first 2s, so data.y does not exist(NoneType)

WenchuanSUN1 commented 10 months ago

The test set of Argoverse contains only the information for the first 2s, so data.y does not exist(NoneType)

I appreciate your feedback. However, it has come to my attention that a number of widely-recognized methods, as detailed in their respective publications, have conducted experiments utilizing the Argoverse test dataset. Hence, it is reasonable to infer that standard experiments at the data level should be feasible, as exemplified by TNT, LaneConv, and JEAN.

Uestc-Young commented 2 months ago

The test set of Argoverse contains only the information for the first 2s, so data.y does not exist(NoneType)

I appreciate your feedback. However, it has come to my attention that a number of widely-recognized methods, as detailed in their respective publications, have conducted experiments utilizing the Argoverse test dataset. Hence, it is reasonable to infer that standard experiments at the data level should be feasible, as exemplified by TNT, LaneConv, and JEAN.

Maybe you can put your output to Argoversev1 leaderboard, and you can get the metrics(ade, fde, mr, etc.) through the official website. There is also a function in argoverse-api to help you submit to the leaderboard, I suppose the function should be:

from argoverse.evaluation.competition_util import generate_forecasting_h5