Unable to reproduce the results obtained in the paper

[bazyagami]

Hello, I am currently trying to reproduce the results of VAD_tiny version and I'm unable to do so. Here's the results am getting :
-------------- Motion Prediction --------------
EPA_car: -0.04155641348197631
EPA_pedestrian: -1.1379246161005119
ADE_car: 2.906290054321289
ADE_pedestrian: 1.791144847869873
FDE_car: 4.5987725257873535
FDE_pedestrian: 2.769331693649292
MR_car: 0.2698412698412698
MR_pedestrian: 0.6610169491525424

-------------- Planning --------------
gt_car:4.503418636452432
gt_pedestrian:2.099042781793319
cnt_ade_car:0.06583317054112131
cnt_ade_pedestrian:0.03731197499511623
cnt_fde_car:0.06153545614377808
cnt_fde_pedestrian:0.034577065833170544
hit_car:0.044930650517679235
hit_pedestrian:0.011721039265481539
fp_car:0.44149247899980465
fp_pedestrian:3.3787849189294783
ADE_car:0.20511303842067719
ADE_pedestrian:0.06863386929035187
FDE_car:0.2829875648021698
FDE_pedestrian:0.09575536847114563
MR_car:0.016604805626098847
MR_pedestrian:0.022856026567689
plan_L2_1s:2.202318344513195
plan_L2_2s:3.6597831307854727
plan_L2_3s:5.149097903307153
plan_obj_col_1s:0.0
plan_obj_col_2s:9.767532721234616e-05
plan_obj_col_3s:0.0001953506602465955
plan_obj_box_col_1s:0.004493065051767923
plan_obj_box_col_2s:0.01684899394412971
plan_obj_box_col_3s:0.03477241705231984
fut_valid_flag:1.0

I have followed the similar commands as given in the docs and the code was working all fine! the only problem that is occurring is with respect to the recreation of the results using the pre-trained checkpoints.

The command used to run the eval :
CUDA_VISIBLE_DEVICES=0 python /mnt/work/VAD/VAD/tools/test.py /mnt/work/VAD/VAD/projects/configs/VAD/VAD_tiny_e2e.py /mnt/work/VAD/VAD/VAD_tiny.pth --launcher none --eval bbox --tmpdir tmp

[hyzhou404]

Hi, have you solve the problem? I am facing the same problem

[Fengtao22]

Check #18.
Change:
img_norm_cfg = dict(
mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)

[hyzhou404]

Check #18. Change: img_norm_cfg = dict( mean=[103.530, 116.280, 123.675], std=[1.0, 1.0, 1.0], to_rgb=False)

Thanks a lot!