evaluate the conditional prediction result

[Yang-Li-2000]

I am not sure which 6 groups should I merge. When running the evaluation command, it generates 6 predicted trajectories for each scenario. However, in result() in class MotionMetrics in src/waymo_tutorial.py, only 1 trajectory is left for each scenario. The shape of prediction_trajectory in result() in class MotionMetrics is [num_scenarios, 80, 2]. image

At the same time, in REDAME.md, --eval_rst_saving_number can have 6 different values (from 0 to 5).

Should I merge 6 predicted trajectories for a fixed eval_rst_saving_number or merge predicted trajectories generated using 6 different eval_rst_saving_number?

Additionally, when merging the trajectory of the influencer and the trajectory of the reactor, how should I permute them? The shape of the merged trajectories is (num_scenarios, 6, n=2, 80, 2). Is [:, :, 0, :] for influencers and [:, :, 1, :] for reactors? Or, is there a different way to arrange influencer trajectory and reactor trajectory?

How should I merge the scores of the influencer and the scores of the reactor? Should I multiply them or stack them?